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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Engineer - **Company:** Initiate Government Solutions - **Location:** Washington, DC, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Microsoft Azure, Clinical Data Repository, Cloud Computing, Cloud Engineering, Continuous Integration, Information Engineering, Data Governance, Distributed Computing Environment, Python (Programming Language), Machine Learning, Natural Language Processing, Scrum Methodology, Release Management, Remote Access Technology, Tensorflow, Zero Trust Network Access, Azure Machine Learning, Enterprise Data Management, Cloud Platform System, Pytorch, Large Language Models, Prompt Engineering, Generative AI, Infrastructure as Code (IaC), Git, Web Filtering, Data Lakes, Scikit Learn, Machine Learning Operations, Text Analysis, Software Version Control, Devsecops, Databricks - **Published:** August 5, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=49a898dceb75831a ## About the Role * 5+ years of experience designing, developing, and deploying AI/ML solutions in cloud environments. * Hands-on experience with: Azure Machine Learning, Azure AI Services, Databricks, Python, ML frameworks such as TensorFlow, PyTorch, or Scikit-Learn, Azure DevOps and CI/CD pipelines * Experience developing and deploying NLP, machine learning, and predictive analytics solutions. * Strong understanding of data engineering, cloud architecture, and distributed data processing. * Experience with Git-based source control and DevSecOps methodologies. * Ability to obtain and maintain a Public Trust * Ability to work in the United States without sponsorship Preferred Qualifications and Core Competencies: * Direct experience deploying AI/ML or data science solutions within a federal government agency. * Experience supporting Department of Veterans Affairs (VA), Veterans Health Administration (VHA), Centers for Medicare & Medicaid Services (CMS), or other federal healthcare environments. * Experience with Generative AI, LLMs, Retrieval-Augmented Generation (RAG), prompt engineering, and AI governance frameworks. * Experience with Lakehouse architectures, Delta Lake, and enterprise data platforms. * Familiarity with Zero Trust Architecture (ZTA), RMF, ATO processes, and federal cybersecurity requirements. * Knowledge of healthcare datasets, clinical analytics, or healthcare data privacy requirements * Active Public Trust, * Integrity, Honesty, and Ethics: We conduct our business with the highest level of ethics. Doing things like being accountable for mistakes, accepting helpful criticism, and following through on commitments to ourselves, each other, and our customers. * Empathy, Emotional Intelligence: How we interact with others including peers, colleagues, stakeholders, and customers' matters. We take collective responsibility to create an environment where colleagues and customers feel valued, included, and respected. We work within a diverse, integrated, and collaborative team to drive towards accomplishing the larger mission. We conscientiously and meticulously learn about our customers' and end-users' business drivers and challenges to ensure solutions meet not only technical needs but also support their mission. * Strong Work Ethic (Reliability, Dedication, Productivity): We are driven by a strong, self-motivated, and results-driven work ethic. We are reliable, accountable, proactive, and tenacious and will do what it takes to get the job done. * Life-Long Learner (Curious, Perspective, Goal Oriented): We challenge ourselves to continually learn and improve ourselves. We strive to be an expert in our field, continuously honing our craft, and finding solutions where others see problems. ## Description This is a remote access assignment. The Candidate will work remotely daily and will remotely access customer systems and therein use approved customer provided communications systems. Travel is not required; however, the candidate may be required to attend onsite client meetings as requested. The AI/ML Engineer will play a critical role in designing, deploying, scaling, and supporting production-grade AI/ML solutions within a secure and governed Azure cloud environment. This position will help enable predictive analytics, Natural Language Processing (NLP), generative AI capabilities, and advanced model development supporting improved healthcare outcomes and operational efficiencies for Veterans, their families, and caregivers. Responsibilities and Duties (Included but not limited to): * Design, implement, and maintain scalable AI/ML infrastructure using Azure Machine Learning, Databricks, Azure AI Services, and related cloud technologies. * Develop and deploy predictive models, NLP solutions, and generative AI capabilities supporting enterprise business and healthcare use cases. * Build reusable AI/ML frameworks, templates, and accelerators for model development, training, validation, deployment, and monitoring. * Support AI/ML onboarding and adoption across customer workgroups utilizing shared analytics and AI capabilities. * Integrate AI/ML workloads within secure DevSecOps environments using Infrastructure as Code (IaC) and automated security controls. * Develop monitoring capabilities for model performance, bias detection, drift monitoring, and operational health management. * Ensure AI/ML solutions align with zero-trust architecture and security requirements. * Design and deploy generative AI use cases utilizing Large Language Models (LLMs), prompt orchestration, guardrails, content filtering, and human-in-the-loop validation. * Implement NLP and text analytics solutions for structured and unstructured data sources, including healthcare and operational datasets. * Collaborate with data engineers and analytics teams to operationalize AI-generated insights and integrate AI outputs into business processes. * Adhere to customer's Trustworthy AI principles, privacy requirements, cybersecurity policies, and Risk Management Framework (RMF) controls. * Support model governance, documentation, audit readiness, and AI risk assessment activities. * Ensure compliance with federal regulations, accessibility standards, and enterprise data governance policies. * Participate in Agile ceremonies including sprint planning, daily standups, retrospectives, backlog grooming, and release planning. * Other duties as assigned ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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