Senior Platform Engineer (FedD239)

Senior Platform EngineerAI Engineering | Forward Deployed EngineeringRole DescriptionDefense Unicorns is seeking a senior AI Agentic Engineer to embed with a government team and its technology partners building an emerging AI-powered engineering ecosystem.This role will focus on designing, integrating, and operationalizing AI agents and agentic workflows within a secure enterprise environment. The engineer will work across large language models, agent frameworks, enterprise data, APIs, developer tooling, and platform services to turn AI capabilities into reliable, mission-relevant workflows.The ideal candidate is a hands-on engineer who understands both the capabilities and limitations of modern AI systems and can rapidly translate emerging technologies into working solutions. They should be comfortable experimenting with new models and agent frameworks, integrating agents with enterprise systems and tools, evaluating performance and reliability, and working alongside platform engineers and commercial technology partners.This is not a research-only role. The focus is on moving from AI concepts and prototypes to secure, useful, repeatable agentic capabilities that can operate in production environments.ResponsibilitiesDesign, build, and integrate AI agents and multi-agent workflows using modern LLM and agentic technologies.Develop agent capabilities that interact with enterprise applications, APIs, data sources, developer tools, and mission systems.Integrate models, agents, tools, and enterprise data into secure workflows that can be deployed in controlled and classified environments.Work with LLMs, RAG, embeddings, vector databases, tool/function calling, structured outputs, MCP, and related technologies.Develop mechanisms for agents to securely discover, access, reason over, and act upon approved enterprise data and services.Prototype and rapidly evaluate emerging models, agent frameworks, and AI capabilities to determine where they can create measurable mission or engineering value.Develop evaluation and testing frameworks for agent accuracy, reliability, safety, latency, cost, and task completion.Implement guardrails and policy controls governing agent behavior, tool access, data access, and human approval points.Integrate agentic capabilities with CI/CD and DevSecOps workflows to support repeatable development, testing, deployment, and lifecycle management.Collaborate with platform engineers to operationalize AI workloads within Kubernetes/OpenShift environments.Work with commercial AI and technology partners to integrate their capabilities into the broader engineering ecosystem.Troubleshoot issues across models, agent frameworks, APIs, data sources, networking, identity, and infrastructure.Develop reusable patterns for agent deployment, configuration, observability, evaluation, and lifecycle management.Document architectures, integration patterns, agent specifications, evaluation results, and operational procedures.Identify recurring AI engineering challenges that can be standardized, automated, or productized into reusable capabilities.Stay current with rapidly evolving agentic AI technologies and assess their applicability to secure government environments.Minimum Experience and QualificationsActive TS/SCI clearance.Hands-on experience building applications or systems using large language models and generative AI.Experience designing and implementing AI agents or agentic workflows.Strong programming experience in Python and/or another modern programming language.Experience integrating AI systems with APIs, enterprise applications, databases, and external tools.Experience with one or more agent frameworks or orchestration approaches.Working knowledge of RAG, embeddings, vector databases, tool/function calling, structured outputs, and prompt engineering.Experience developing software in a Git-based, automated CI/CD environment.Ability to rapidly prototype, test, troubleshoot, and iterate in ambiguous environments.Strong understanding of software engineering fundamentals, including testing, version control, APIs, debugging, and system design.Ability to work effectively alongside platform engineers, government personnel, and multiple technology vendors.Preferred Experience and QualificationsExperience with MCP (Model Context Protocol) and tool-based agent architectures.Experience with multi-agent systems and agent orchestration.Experience with OpenAI, Anthropic, Google, NVIDIA, or comparable foundation model ecosystems.Experience with NVIDIA NIM, NeMo, or similar AI inference/model-serving technologies.Experience with Red Hat OpenShift AI or Kubernetes-based AI platforms.Experience with agent evaluation and observability frameworks.Experience implementing AI guardrails, policy enforcement, human-in-the-loop workflows, or AI safety controls.Experience with LangGraph, LangChain, LlamaIndex, Semantic Kernel, or comparable frameworks.Experience with RAG pipelines, vector databases, knowledge graphs, and enterprise search.Experience deploying AI systems in Secret or TS/SCI environments.Experience with disconnected or air-gapped AI environments.Experience integrating AI into developer/DevSecOps workflows.Familiarity with GitLab, Jira, Confluence, Xacta, or similar enterprise engineering and compliance tools.Experience working with GPUs, model serving, inference optimization, or AI infrastructure.Familiarity with UDS, Zarf, Pepr, Iron Bank, or similar secure software delivery technologies.Experience taking AI prototypes into repeatable, production-ready capabilities.Ability to evaluate new AI technologies quickly and make pragmatic build/buy/integrate decisions.What Success Looks LikeAgentic capabilities move from prototype to mission use quickly, with working agents integrated into real government workflows rather than remaining isolated demos.Agents reliably connect to approved enterprise data, tools, and services, with appropriate identity, permissions, guardrails, and human-in-the-loop controls.AI capabilities are measurable and trustworthy, with repeatable evaluation methods for accuracy, reliability, task completion, security, and operational performance.Reusable agent patterns emerge, reducing the engineering required to build and deploy the next agent or AI-enabled workflow.AI integrates cleanly with the broader platform architecture, working effectively across the data, DevSecOps, Kubernetes/OpenShift, model, and application layers rather than creating another technology silo.The engineer becomes a trusted AI technical advisor to the Mission Hero, proactively identifying where agentic technology can create mission value-and equally important, where AI is not the right solution.Full compensation packages are based on candidate experience. Compensation ranges are established using national benchmarking data and apply across all geographic locations within the United States. Remote - USA$148,750 - $201,250USDWho We AreDefense Unicorns delivers mission value by streamlining software delivery so our customers can focus on the most important challenges. We share a vision of freedom and security for the advancement of progress and innovation. Our commitment to this vision, and to our mission-driven customers, means a commitment to speed, user experience and optionality, without compromising security. Our team is composed of innovators, software engineers, and veterans with decades of experience delivering technology programs across the federal market.What We DoWe create and deliver secure solutions for continuous software integration and delivery. Defense Unicorns consolidates the best practices for security pipelines, testing, and deployment automation in order to meet the high security requirements valued by mission owners. Our solutions are agnostic by design and we believe that growing a robust ecosystem of secure, cloud-native software solutions can help enterprise customers inside and outside the federal market buy and integrate software more easily.Who We ServeDefense Unicorns’ customers are mission-focused leaders across public and private enterprises. We proudly support defense and civil agencies across the U.S. government and we work closely with the creators of leading-edge software solutions to deliver value to the mission-owner by improving the security and consumability of commercial software products.What We Work OnKubernetesCloud Environments (AWS/GCP and Azure)Infrastructure-as-code (like Terraform/Pulumi)Continuous Delivery and automation toolingGitOpsContainersCNCF projects and open source products and packagesHelm/Kustomize-Value Stream MappingBuilding and improving security deliveryBuilding Kubernetes and cloud native applicationsBenefits Our Unicorns EnjoyHealth:Medical/Dental/VisionPremiums are 100% Company PaidHealth Savings AccountLife InsuranceDisability InsuranceFinancial:401k Retirement PlanCompany Stock OptionsHome Office BudgetLeave:We offer all full-time Unicorns Flexible Time Off (FTO) plus all Federal Holidays, one week for Thanksgiving, and two weeks for Christmas and New Year’sPaid Parental LeaveLearning:Reimbursement for approved trainings/subscriptionsConferences (travel, lodging, and fees)Don’t have all the preferred experience or qualifications? Studies show that underrepresented groups like women and people of color are less likely to apply to jobs if they don’t meet every requirement listed. At Defense Unicorns, we’re committed to diversity. If you’re enthusiastic about the role but don’t match every criteria, we encourage you to apply. You could be the perfect fit for this or another role! Defense Unicorns is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, sex, sexual orientation, gender identity or expression, age, national origin, veteran status, genetic information, union status and/or beliefs, or any other characteristic protected by federal, state, or local law.CCPA DISCLOSURE Senior Platform EngineerAI Engineering | Forward Deployed EngineeringRole DescriptionDefense Unicorns is seeking a senior AI Agentic Engineer to embed with a government team and its technology partners building an emerging AI-powered engineering ecosystem.This role will focus on designing, integrating, and operationalizing AI agents and agentic workflows within a secure enterprise environment. The engineer will work across large language models, agent frameworks, enterprise data, APIs, developer tooling, and platform services to turn AI capabilities into reliable, mission-relevant workflows.The ideal candidate is a hands-on engineer who understands both the capabilities and limitations of modern AI systems and can rapidly translate emerging technologies into working solutions. They should be comfortable experimenting with new models and agent frameworks, integrating agents with enterprise systems and tools, evaluating performance and reliability, and working alongside platform engineers and commercial technology partners.This is not a research-only role. The focus is on moving from AI concepts and prototypes to secure, useful, repeatable agentic capabilities that can operate in production environments.ResponsibilitiesDesign, build, and integrate AI agents and multi-agent workflows using modern LLM and agentic technologies.Develop agent capabilities that interact with enterprise applications, APIs, data sources, developer tools, and mission systems.Integrate models, agents, tools, and enterprise data into secure workflows that can be deployed in controlled and classified environments.Work with LLMs, RAG, embeddings, vector databases, tool/function calling, structured outputs, MCP, and related technologies.Develop mechanisms for agents to securely discover, access, reason over, and act upon approved enterprise data and services.Prototype and rapidly evaluate emerging models, agent frameworks, and AI capabilities to determine where they can create measurable mission or engineering value.Develop evaluation and testing frameworks for agent accuracy, reliability, safety, latency, cost, and task completion.Implement guardrails and policy controls governing agent behavior, tool access, data access, and human approval points.Integrate agentic capabilities with CI/CD and DevSecOps workflows to support repeatable development, testing, deployment, and lifecycle management.Collaborate with platform engineers to operationalize AI workloads within Kubernetes/OpenShift environments.Work with commercial AI and technology partners to integrate their capabilities into the broader engineering ecosystem.Troubleshoot issues across models, agent frameworks, APIs, data sources, networking, identity, and infrastructure.Develop reusable patterns for agent deployment, configuration, observability, evaluation, and lifecycle management.Document architectures, integration patterns, agent specifications, evaluation results, and operational procedures.Identify recurring AI engineering challenges that can be standardized, automated, or productized into reusable capabilities.Stay current with rapidly evolving agentic AI technologies and assess their applicability to secure government environments.Minimum Experience and QualificationsActive TS/SCI clearance.Hands-on experience building applications or systems using large language models and generative AI.Experience designing and implementing AI agents or agentic workflows.Strong programming experience in Python and/or another modern programming language.Experience integrating AI systems with APIs, enterprise applications, databases, and external tools.Experience with one or more agent frameworks or orchestration approaches.Working knowledge of RAG, embeddings, vector databases, tool/function calling, structured outputs, and prompt engineering.Experience developing software in a Git-based, automated CI/CD environment.Ability to rapidly prototype, test, troubleshoot, and iterate in ambiguous environments.Strong understanding of software engineering fundamentals, including testing, version control, APIs, debugging, and system design.Ability to work effectively alongside platform engineers, government personnel, and multiple technology vendors.Preferred Experience and QualificationsExperience with MCP (Model Context Protocol) and tool-based agent architectures.Experience with multi-agent systems and agent orchestration.Experience with OpenAI, Anthropic, Google, NVIDIA, or comparable foundation model ecosystems.Experience with NVIDIA NIM, NeMo, or similar AI inference/model-serving technologies.Experience with Red Hat OpenShift AI or Kubernetes-based AI platforms.Experience with agent evaluation and observability frameworks.Experience implementing AI guardrails, policy enforcement, human-in-the-loop workflows, or AI safety controls.Experience with LangGraph, LangChain, LlamaIndex, Semantic Kernel, or comparable frameworks.Experience with RAG pipelines, vector databases, knowledge graphs, and enterprise search.Experience deploying AI systems in Secret or TS/SCI environments.Experience with disconnected or air-gapped AI environments.Experience integrating AI into developer/DevSecOps workflows.Familiarity with GitLab, Jira, Confluence, Xacta, or similar enterprise engineering and compliance tools.Experience working with GPUs, model serving, inference optimization, or AI infrastructure.Familiarity with UDS, Zarf, Pepr, Iron Bank, or similar secure software delivery technologies.Experience taking AI prototypes into repeatable, production-ready capabilities.Ability to evaluate new AI technologies quickly and make pragmatic build/buy/integrate decisions.What Success Looks LikeAgentic capabilities move from prototype to mission use quickly, with working agents integrated into real government workflows rather than remaining isolated demos.Agents reliably connect to approved enterprise data, tools, and services, with appropriate identity, permissions, guardrails, and human-in-the-loop controls.AI capabilities are measurable and trustworthy, with repeatable evaluation methods for accuracy, reliability, task completion, security, and operational performance.Reusable agent patterns emerge, reducing the engineering required to build and deploy the next agent or AI-enabled workflow.AI integrates cleanly with the broader platform architecture, working effectively across the data, DevSecOps, Kubernetes/OpenShift, model, and application layers rather than creating another technology silo.The engineer becomes a trusted AI technical advisor to the Mission Hero, proactively identifying where agentic technology can create mission value-and equally important, where AI is not the right solution.Full compensation packages are based on candidate experience. Compensation ranges are established using national benchmarking data and apply across all geographic locations within the United States. Remote - USA$148,750 - $201,250USDWho We AreDefense Unicorns delivers mission value by streamlining software delivery so our customers can focus on the most important challenges. We share a vision of freedom and security for the advancement of progress and innovation. Our commitment to this vision, and to our mission-driven customers, means a commitment to speed, user experience and optionality, without compromising security. Our team is composed of innovators, software engineers, and veterans with decades of experience delivering technology programs across the federal market.What We DoWe create and deliver secure solutions for continuous software integration and delivery. Defense Unicorns consolidates the best practices for security pipelines, testing, and deployment automation in order to meet the high security requirements valued by mission owners. Our solutions are agnostic by design and we believe that growing a robust ecosystem of secure, cloud-native software solutions can help enterprise customers inside and outside the federal market buy and integrate software more easily.Who We ServeDefense Unicorns’ customers are mission-focused leaders across public and private enterprises. We proudly support defense and civil agencies across the U.S. government and we work closely with the creators of leading-edge software solutions to deliver value to the mission-owner by improving the security and consumability of commercial software products.What We Work OnKubernetesCloud Environments (AWS/GCP and Azure)Infrastructure-as-code (like Terraform/Pulumi)Continuous Delivery and automation toolingGitOpsContainersCNCF projects and open source products and packagesHelm/Kustomize-Value Stream MappingBuilding and improving security deliveryBuilding Kubernetes and cloud native applicationsBenefits Our Unicorns EnjoyHealth:Medical/Dental/VisionPremiums are 100% Company PaidHealth Savings AccountLife InsuranceDisability InsuranceFinancial:401k Retirement PlanCompany Stock OptionsHome Office BudgetLeave:We offer all full-time Unicorns Flexible Time Off (FTO) plus all Federal Holidays, one week for Thanksgiving, and two weeks for Christmas and New Year’sPaid Parental LeaveLearning:Reimbursement for approved trainings/subscriptionsConferences (travel, lodging, and fees)Don’t have all the preferred experience or qualifications? Studies show that underrepresented groups like women and people of color are less likely to apply to jobs if they don’t meet every requirement listed. At Defense Unicorns, we’re committed to diversity. If you’re enthusiastic about the role but don’t match every criteria, we encourage you to apply. You could be the perfect fit for this or another role! Defense Unicorns is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, sex, sexual orientation, gender identity or expression, age, national origin, veteran status, genetic information, union status and/or beliefs, or any other characteristic protected by federal, state, or local law.CCPA DISCLOSURE Senior Platform EngineerAI Engineering | Forward Deployed EngineeringRole DescriptionDefense Unicorns is seeking a senior AI Agentic Engineer to embed with a government team and its technology partners building an emerging AI-powered engineering ecosystem.This role will focus on designing, integrating, and operationalizing AI agents and agentic workflows within a secure enterprise environment. The engineer will work across large language models, agent frameworks, enterprise data, APIs, developer tooling, and platform services to turn AI capabilities into reliable, mission-relevant workflows.The ideal candidate is a hands-on engineer who understands both the capabilities and limitations of modern AI systems and can rapidly translate emerging technologies into working solutions. They should be comfortable experimenting with new models and agent frameworks, integrating agents with enterprise systems and tools, evaluating performance and reliability, and working alongside platform engineers and commercial technology partners.This is not a research-only role. The focus is on moving from AI concepts and prototypes to secure, useful, repeatable agentic capabilities that can operate in production environments.ResponsibilitiesDesign, build, and integrate AI agents and multi-agent workflows using modern LLM and agentic technologies.Develop agent capabilities that interact with enterprise applications, APIs, data sources, developer tools, and mission systems.Integrate models, agents, tools, and enterprise data into secure workflows that can be deployed in controlled and classified environments.Work with LLMs, RAG, embeddings, vector databases, tool/function calling, structured outputs, MCP, and related technologies.Develop mechanisms for agents to securely discover, access, reason over, and act upon approved enterprise data and services.Prototype and rapidly evaluate emerging models, agent frameworks, and AI capabilities to determine where they can create measurable mission or engineering value.Develop evaluation and testing frameworks for agent accuracy, reliability, safety, latency, cost, and task completion.Implement guardrails and policy controls governing agent behavior, tool access, data access, and human approval points.Integrate agentic capabilities with CI/CD and DevSecOps workflows to support repeatable development, testing, deployment, and lifecycle management.Collaborate with platform engineers to operationalize AI workloads within Kubernetes/OpenShift environments.Work with commercial AI and technology partners to integrate their capabilities into the broader engineering ecosystem.Troubleshoot issues across models, agent frameworks, APIs, data sources, networking, identity, and infrastructure.Develop reusable patterns for agent deployment, configuration, observability, evaluation, and lifecycle management.Document architectures, integration patterns, agent specifications, evaluation results, and operational procedures.Identify recurring AI engineering challenges that can be standardized, automated, or productized into reusable capabilities.Stay current with rapidly evolving agentic AI technologies and assess their applicability to secure government environments.Minimum Experience and QualificationsActive TS/SCI clearance.Hands-on experience building applications or systems using large language models and generative AI.Experience designing and implementing AI agents or agentic workflows.Strong programming experience in Python and/or another modern programming language.Experience integrating AI systems with APIs, enterprise applications, databases, and external tools.Experience with one or more agent frameworks or orchestration approaches.Working knowledge of RAG, embeddings, vector databases, tool/function calling, structured outputs, and prompt engineering.Experience developing software in a Git-based, automated CI/CD environment.Ability to rapidly prototype, test, troubleshoot, and iterate in ambiguous environments.Strong understanding of software engineering fundamentals, including testing, version control, APIs, debugging, and system design.Ability to work effectively alongside platform engineers, government personnel, and multiple technology vendors.Preferred Experience and QualificationsExperience with MCP (Model Context Protocol) and tool-based agent architectures.Experience with multi-agent systems and agent orchestration.Experience with OpenAI, Anthropic, Google, NVIDIA, or comparable foundation model ecosystems.Experience with NVIDIA NIM, NeMo, or similar AI inference/model-serving technologies.Experience with Red Hat OpenShift AI or Kubernetes-based AI platforms.Experience with agent evaluation and observability frameworks.Experience implementing AI guardrails, policy enforcement, human-in-the-loop workflows, or AI safety controls.Experience with LangGraph, LangChain, LlamaIndex, Semantic Kernel, or comparable frameworks.Experience with RAG pipelines, vector databases, knowledge graphs, and enterprise search.Experience deploying AI systems in Secret or TS/SCI environments.Experience with disconnected or air-gapped AI environments.Experience integrating AI into developer/DevSecOps workflows.Familiarity with GitLab, Jira, Confluence, Xacta, or similar enterprise engineering and compliance tools.Experience working with GPUs, model serving, inference optimization, or AI infrastructure.Familiarity with UDS, Zarf, Pepr, Iron Bank, or similar secure software delivery technologies.Experience taking AI prototypes into repeatable, production-ready capabilities.Ability to evaluate new AI technologies quickly and make pragmatic build/buy/integrate decisions.What Success Looks LikeAgentic capabilities move from prototype to mission use quickly, with working agents integrated into real government workflows rather than remaining isolated demos.Agents reliably connect to approved enterprise data, tools, and services, with appropriate identity, permissions, guardrails, and human-in-the-loop controls.AI capabilities are measurable and trustworthy, with repeatable evaluation methods for accuracy, reliability, task completion, security, and operational performance.Reusable agent patterns emerge, reducing the engineering required to build and deploy the next agent or AI-enabled workflow.AI integrates cleanly with the broader platform architecture, working effectively across the data, DevSecOps, Kubernetes/OpenShift, model, and application layers rather than creating another technology silo.The engineer becomes a trusted AI technical advisor to the Mission Hero, proactively identifying where agentic technology can create mission value-and equally important, where AI is not the right solution. Full compensation packages are based on candidate experience. Compensation ranges are established using national benchmarking data and apply across all geographic locations within the United States. Remote - USA$148,750 - $201,250USD Full compensation packages are based on candidate experience. Compensation ranges are established using national benchmarking data and apply across all geographic locations within the United States. Remote - USA$148,750 - $201,250USD Full compensation packages are based on candidate experience. Compensation ranges are established using national benchmarking data and apply across all geographic locations within the United States. Full compensation packages are based on candidate experience. Compensation ranges are established using national benchmarking data and apply across all geographic locations within the United States. Who We AreDefense Unicorns delivers mission value by streamlining software delivery so our customers can focus on the most important challenges. We share a vision of freedom and security for the advancement of progress and innovation. Our commitment to this vision, and to our mission-driven customers, means a commitment to speed, user experience and optionality, without compromising security. Our team is composed of innovators, software engineers, and veterans with decades of experience delivering technology programs across the federal market.What We DoWe create and deliver secure solutions for continuous software integration and delivery. Defense Unicorns consolidates the best practices for security pipelines, testing, and deployment automation in order to meet the high security requirements valued by mission owners. Our solutions are agnostic by design and we believe that growing a robust ecosystem of secure, cloud-native software solutions can help enterprise customers inside and outside the federal market buy and integrate software more easily.Who We ServeDefense Unicorns’ customers are mission-focused leaders across public and private enterprises. We proudly support defense and civil agencies across the U.S. government and we work closely with the creators of leading-edge software solutions to deliver value to the mission-owner by improving the security and consumability of commercial software products.What We Work OnKubernetesCloud Environments (AWS/GCP and Azure)Infrastructure-as-code (like Terraform/Pulumi)Continuous Delivery and automation toolingGitOpsContainersCNCF projects and open source products and packagesHelm/Kustomize-Value Stream MappingBuilding and improving security deliveryBuilding Kubernetes and cloud native applicationsBenefits Our Unicorns EnjoyHealth:Medical/Dental/VisionPremiums are 100% Company PaidHealth Savings AccountLife InsuranceDisability InsuranceFinancial:401k Retirement PlanCompany Stock OptionsHome Office BudgetLeave:We offer all full-time Unicorns Flexible Time Off (FTO) plus all Federal Holidays, one week for Thanksgiving, and two weeks for Christmas and New Year’sPaid Parental LeaveLearning:Reimbursement for approved trainings/subscriptionsConferences (travel, lodging, and fees)Don’t have all the preferred experience or qualifications? Studies show that underrepresented groups like women and people of color are less likely to apply to jobs if they don’t meet every requirement listed. At Defense Unicorns, we’re committed to diversity. If you’re enthusiastic about the role but don’t match every criteria, we encourage you to apply. You could be the perfect fit for this or another role! Defense Unicorns is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, sex, sexual orientation, gender identity or expression, age, national origin, veteran status, genetic information, union status and/or beliefs, or any other characteristic protected by federal, state, or local law.CCPA DISCLOSURE

• Active TS/SCI clearance.
• Hands-on experience building applications or systems using large language models and generative AI.
• Experience designing and implementing AI agents or agentic workflows.
• Strong programming experience in Python and/or another modern programming language.
• Experience integrating AI systems with APIs, enterprise applications, databases, and external tools.
• Experience with one or more agent frameworks or orchestration approaches.
• Working knowledge of RAG, embeddings, vector databases, tool/function calling, structured outputs, and prompt engineering.
• Experience developing software in a Git-based, automated CI/CD environment.
• Ability to rapidly prototype, test, troubleshoot, and iterate in ambiguous environments.
• Strong understanding of software engineering fundamentals, including testing, version control, APIs, debugging, and system design.
• Ability to work effectively alongside platform engineers, government personnel, and multiple technology vendors., * Experience with MCP (Model Context Protocol) and tool-based agent architectures.
• Experience with multi-agent systems and agent orchestration.
• Experience with OpenAI, Anthropic, Google, NVIDIA, or comparable foundation model ecosystems.
• Experience with NVIDIA NIM, NeMo, or similar AI inference/model-serving technologies.
• Experience with Red Hat OpenShift AI or Kubernetes-based AI platforms.
• Experience with agent evaluation and observability frameworks.
• Experience implementing AI guardrails, policy enforcement, human-in-the-loop workflows, or AI safety controls.
• Experience with LangGraph, LangChain, LlamaIndex, Semantic Kernel, or comparable frameworks.
• Experience with RAG pipelines, vector databases, knowledge graphs, and enterprise search.
• Experience deploying AI systems in Secret or TS/SCI environments.
• Experience with disconnected or air-gapped AI environments.
• Experience integrating AI into developer/DevSecOps workflows.
• Familiarity with GitLab, Jira, Confluence, Xacta, or similar enterprise engineering and compliance tools.
• Experience working with GPUs, model serving, inference optimization, or AI infrastructure.
• Familiarity with UDS, Zarf, Pepr, Iron Bank, or similar secure software delivery technologies.
• Experience taking AI prototypes into repeatable, production-ready capabilities.
• Ability to evaluate new AI technologies quickly and make pragmatic build/buy/integrate decisions.

Full compensation packages are based on candidate experience. Compensation ranges are established using national benchmarking data and apply across all geographic locations within the United States.

Remote - USA

$148,750 - $201,250USD, * Medical/Dental/Vision

• Premiums are 100% Company Paid
• Health Savings Account
• Life Insurance
• Disability Insurance

Financial:

• 401k Retirement Plan
• Company Stock Options
• Home Office Budget

Leave:

• We offer all full-time Unicorns Flexible Time Off (FTO) plus all Federal Holidays, one week for Thanksgiving, and two weeks for Christmas and New Year’s
• Paid Parental Leave

Learning:

• Reimbursement for approved trainings/subscriptions
• Conferences (travel, lodging, and fees)

Defense Unicorns is seeking a senior AI Agentic Engineer to embed with a government team and its technology partners building an emerging AI-powered engineering ecosystem., Defense Unicorns delivers mission value by streamlining software delivery so our customers can focus on the most important challenges. We share a vision of freedom and security for the advancement of progress and innovation. Our commitment to this vision, and to our mission-driven customers, means a commitment to speed, user experience and optionality, without compromising security. Our team is composed of innovators, software engineers, and veterans with decades of experience delivering technology programs across the federal market., We create and deliver secure solutions for continuous software integration and delivery. Defense Unicorns consolidates the best practices for security pipelines, testing, and deployment automation in order to meet the high security requirements valued by mission owners. Our solutions are agnostic by design and we believe that growing a robust ecosystem of secure, cloud-native software solutions can help enterprise customers inside and outside the federal market buy and integrate software more easily.

Who We Serve

Defense Unicorns’ customers are mission-focused leaders across public and private enterprises. We proudly support defense and civil agencies across the U.S. government and we work closely with the creators of leading-edge software solutions to deliver value to the mission-owner by improving the security and consumability of commercial software products.