Artificial Intelligence and Machine Learning Engineer

About the Role

As an experienced engineer, your ability to design and build practical agentic systems that turn manual workflows into AI-enabled solutions makes you an integral part of delivering mission-focused outcomes. We need your technical depth, product mindset, and problem-solving drive to support National Security. In this role, you will define, design, and deliver mission-relevant agentic AI prototypes in fast, iterative development cycles. You will collaborate with product leads, solution architects, and engineers to build, test, and deploy agent-based solutions that solve high-priority client challenges. You will apply best-fit frameworks and patterns, including agent orchestration, tool use, memory, and retrieval, while balancing solution quality, reliability, and cost. You will be part of a small, high-performing team operating in a 4-week prototype lifecycle, where priorities shift quickly and multiple efforts may run in parallel. Success in this role requires adaptability, clear communication, strong execution, and ownership from concept through delivery.

Key Responsibilities

• Define, design, and deliver mission-relevant agentic AI prototypes.
• Build, test, and deploy agent-based solutions.
• Apply best-fit frameworks and patterns, including agent orchestration, tool use, memory, and retrieval.
• Own technical delivery end-to-end in short-cycle environments, from design through deployment.
• Follow code review practices, document work, and maintain clean and reusable code.

Requirements & Tech Stack

• Experience building and delivering agentic AI applications in production or prototype environments.
• Experience implementing agent orchestration frameworks.
• Experience designing and implementing agent loops, tool-calling workflows, and multi-agent interaction patterns.
• Knowledge of LLM platforms and providers, including AWS Bedrock and OpenAI or Ollama.
• Knowledge of prompt engineering techniques for reliability, controllability, and task performance.
• Knowledge of MCP usage and development, including integration of external tools and capabilities.
• Ability to own technical delivery end to end in short-cycle environments, from design through deployment.
• Ability to follow code review practices, document work, and maintain clean and reusable code.
• HS diploma or GED.

Nice to Have

• Experience implementing retrieval patterns for agentic systems, including RAG or GraphRAG.
• Experience building agentic evaluation frameworks, test harnesses, or quality benchmarks.
• Experience implementing observability for agentic systems, such as traces, telemetry, and failure analysis.
• Knowledge of session and chat memory management strategies across multi-turn workflows.
• Ability to design and document lightweight APIs that expose agent capabilities to downstream systems.
• Bachelor's degree in Computer Science, Engineering, or a related Technical field.

Compensation

• Projected compensation range: $99,000.00 to $225,000.00 (annualized USD).

Work Model

• Roles may be listed as Remote, Hybrid, or Onsite, with varying expectations for in-person collaboration. Virtual employees are generally expected to have their cameras on during meetings.

Candidate AI Usage Policy

• The use of artificial intelligence (AI) or other tools to assist with responses during interviews is prohibited unless permission is explicitly provided.