AI/ML Engineer/Forward Deployed Engineer

The AI/ML Engineer (Forward Deployed Engineer/FDE) Specialist bridges gaps between product teams, security, business units, and cloud engineering- This resource should apply platform-agnostic engineering practices and evaluate AI/LLM capabilities based on business need, security requirements, data classification, interoperability, sustainability, and total cost of ownership rather than defaulting to a single cloud, model, or vendor ecosystem. Provides FDE methodology and best practices to client staff for knowledge transfer sessions and skill growth. Supports IT and other AI initiative at the client.

This role is intended to bring advanced, forward-looking technical capability to the client and partner agencies while remaining flexible, platform-agnostic, and outcomes-focused. The consultant should be able to work at the intersection of modern software engineering, cloud-native architecture, AI-enabled development, automation, security, and agency mission delivery. Rather than prescribing a specific cloud platform, LLM provider, or toolchain, the role should emphasize the ability to evaluate technologies based on business need, security posture, data sensitivity, interoperability, cost, operational maturity, and long-term sustainability.

The ideal candidate should help the client and agencies understand what is possible with modern technology, translate emerging capabilities into practical delivery patterns, and coach internal teams on how to adopt those capabilities responsibly. This includes helping teams turn ambiguous problems into practical, AI-enabled workflows, while exploring AI, automation, APIs, integration patterns, DevSecOps, and reusable components. Focus on rapid prototyping and delivering value without assuming any single vendor or solution is always the right fit. The goal is to raise technical fluency, accelerate modernization, and build internal capability while preserving architectural flexibility. The role should be aspirational in terms of skill level and innovation, but not overly prescriptive in terms of specific products, platforms, or implementation methods.

Deliverables:

• Production-ready code, pipelines, infrastructure templates, and documentation.
• Architecture diagrams, operational runbooks, and security compliance mappings.
• AI-assisted development workflows and accelerators.
• Knowledge transfer sessions and training for agency development staff.

Key Activities/Responsibilities:

• Deliver high-quality application, Application Programming Interface (API), Model Context Protocol (MCP), and automation components using cloud-native architectures.
• Develop rapid prototypes, pilots, and production systems using modern engineering patterns.
• Integrate systems across agencies using secure, scalable, human-in-the-loop workflows.
• Implement DevSecOps automation (CI/CD, IaC, container orchestration, cloud pipelines).
• Collaborate directly with agency stakeholders to gather requirements and convert them into working software.
• Deploy AI-enabled development workflows and LLM-assisted capabilities.
• Troubleshoot complex production issues and lead root-cause analysis.
• Mentor agency developers, maturing internal capability and reducing vendor reliance.
• Provide documentation, architectural guidance, and knowledge transfer.
• Rapidly build AI-powered tools using existing systems, and create new applications where needed, to move from experimentation to real impact.
• Comfort working across cloud environments and internal enterprise systems.

• Minimum of 8 years of hands-on software engineering experience.
• Minimum of 8 years of expertise in modern cloud platforms.
• Minimum of 8 years of strong proficiency in: TypeScript/JavaScript, Python, or C#; Modern UI frameworks (React, Angular, Web Components).
• Minimum of 8 years of experience with integrating APIs (LLMs, internal services, data platforms).
• Minimum of 8 years of experience with CI/CD platforms using GitHub Actions, Azure DevOps, or equivalent including building and deploying applications.
• Minimum of 8 years of experience with infrastructure as code and automating environments (e.g., Terraform, ARM/Bicep, or similar tools. Experience working directly with customers or frontline operational teams to build and improve solutions.
• Minimum of 8 years of experience with Extend tools like Salesforce, Appian, ServiceNow, etc. Demonstrated success delivering systems end-to-end from design ? deploy.
• Minimum of 8 years of understanding of security frameworks (NIST, Zero Trust, TX-RAMP expectations).
• Minimum of 8 years of excellent communication and cross-functional collaboration skills.
• Minimum of 8 years of ability to decide when NOT to use low-code.
• Minimum of 8 years of ability to identify high-value use cases and ability to observe workflows.
• Bachelor’s degree in Computer Science, Engineering, or related field OR equivalent experience (10+ years) in hands-on modern engineering roles., * Experience in state government, regulated environments, or multi-agency integration projects.
• Prior FDE or technical field engineering experience at a software platform company.
• Experience designing, evaluating, or implementing AI-enabled workflows using commercial, open-source, or government-approved LLM platforms, including patterns such as retrieval-augmented generation, agentic workflows, model evaluation, prompt management, human-in-the-loop review, and responsible AI controls.
• Experience with shared technical services or modernization programs (e.g., TSS/MSI).
• Experience producing reusable components, design systems, developer tooling.
• Ability to compare AI/LLM options using objective criteria such as data sensitivity, hosting model, latency, cost, accuracy, explainability, auditability, security controls, integration complexity, and operational sustainability.
• CISSP, CCSP, or CISM.
• Kubernetes certifications (CKA/CKAD).
• TOGAF or architecture certifications.
• Scrum Master or SAFe Agile certs.
• TX-RAMP knowledge or auditor training.
• Cloud architecture, DevOps, AI, security, or Kubernetes certifications from one or more major providers, such as Azure, AWS, Google Cloud, Kubernetes, HashiCorp, ISC2, ISACA, or equivalent.

What We Offer:

• Great work life balance
• Altruistic work
• Hybrid working arrangement
• Competitive compensation and benefits including health, dental, vision, life and accident insurance, disability insurance and more!

Luna Data Solutions has an immediate long-term contract position opening for an AI/ML Engineer/Forward Deployed Engineer (FDE) resource with our public sector industry client located in Austin, TX. *This is a hybrid role in which this resource must work onsite THREE days/week, and remotely TWO days/week. All candidates must be currently local/close to the Austin, TX area.