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AI Engineer - Agentic Workflows - Clearance

United States, Washington, DC area, Houston 160000.00 - 205000.00 USD / Year · Job Posted February 14, 2026
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Job Description

Cognitive Space builds next-generation AI systems that help “supercharge satellite operations” through its CNTIENT platform. We are seeking an engineer who thrives in a dynamic, fast-paced environment and enjoys taking ideas from theory into production deployments. You will play a critical role in designing and shipping production-grade, tool-using, multi-agent LLM systems that can coordinate specialized components (e.g., planning, retrieval, decisioning, and execution) to complete complex, multi-step workflows in operational environments. This role is for a hands-on builder who can translate ambiguous workflow requirements into reliable multi-agent behavior, robust tool integrations, and measurable outcomes. Experience deploying and optimizing LLM solutions, including open-source model deployments and work in controlled or mission environments, is strongly valued.

Job Responsibility

  • Design and build LLM-based agents that can plan and execute multi-step workflows (task decomposition, state management, memory, and controlled autonomy)
  • Implement and maintain a robust tool interface layer (tool schemas/contracts, structured I/O, validation, retries, idempotency, and safe execution boundaries)
  • Integrate agents with internal and external systems: APIs, databases, queues, and operational services, ensuring reliable action-taking and traceability
  • Develop evaluation and regression testing for agent behavior (scenario suites, golden traces, automated quality gates) to reduce drift and ensure predictable performance
  • Establish observability for agent runs (tracing, failure analysis, latency/cost monitoring, tool-call success rates) and drive continuous improvements
  • Containerize and deploy agent services and decision-making capabilities for production and edge environments, as applicable
  • Collaborate with cross-functional teams to identify and prioritize agentic automation opportunities tied to key milestones and requirements
  • Implement safety and governance controls (permissions, policy checks, audit logs, and appropriate handling of sensitive data) aligned to operational constraints

Requirements

  • US Citizenship
  • Active TS/SCI clearance preferred or must be able to obtain and maintain a TS/SCI Clearance
  • Preferred Security+ Certification
  • Bachelor’s/Master's/Ph.D. in a relevant field: Computer Science, Engineering, Applied Math, Statistics, etc.
  • 2–5+ years of professional experience as an AI Engineer, ML Engineer, Software Engineer (Applied AI), Applied Scientist, or similar role
  • Strong programming skills in Python
  • experience with production services, APIs, and containerization (Docker/Kubernetes) is strongly preferred
  • Experience deploying and operating workloads on AWS (e.g., IAM, VPC, EC2, EKS/ECS, Lambda, S3, CloudWatch), including security, monitoring, and cost-aware design
  • Hands-on experience building LLM applications in production
  • Experience with ML/LLM frameworks and ecosystems (e.g., PyTorch/TensorFlow familiarity
  • LangChain/Strands/Bedrock familiarity
  • vector databases/search) consistent with an applied engineering role
  • Strong debugging and analytical skills: ability to diagnose failures across model behavior, tool execution, and system integration
  • Ability to convey complex technical behavior and trade-offs in a clear, practical manner

Nice to have

  • Prefer experience in space/satellite/aerospace domains, mission operations, systems engineering, or adjacent operational environments
  • Prefer experience with offline/online evaluation methodologies and building reusable test harnesses for AI behavior

What we offer

  • Equity in the form of options
  • Flexible Time-Off policy and company holidays
  • Cost-effective health care, dental, and vision with company contributions
  • 401k matching plan with company match
  • Life insurance
  • Short-term and long-term disability

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