AI Engineer - Agentic Workflows - Clearance

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 indesigning 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 andoptimizingLLM solutions,including open-source model deployments and work in controlled or mission environments,is strongly valued.LocationWashington, DC area, Houston – hybrid in the office 2–3 times per week.What you will be doingDesign and build LLM-based agents that can plan and execute multi-step workflows (task decomposition, state management, memory, and controlled autonomy).Implement andmaintaina 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 toidentifyand prioritize agentic automation opportunities tied to key milestones and requirements.Implement safety and governance controls (permissions, policy checks, audit logs, andappropriate handlingof sensitive data) aligned to operational constraints.What you will needActive 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; experiencewith production services, APIs, and containerization (Docker/Kubernetes) is strongly preferred.Experience deploying and operating workloads onAWS(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, including several of: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.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.One of the most interesting aspects of working at a startup company is gaining equity, which means our success is your success. In addition to equity in the form of options, we also offer:Flexible Time‑Off policy and company holidaysCost‑effective health care, dental, and vision with company contributions401k matching plan with company matchLife insuranceShort‑term and long‑term disability$160,000 - $205,000We value job‑related knowledge and skills, education, and experience. That's why we will determine your actual level and base salary on a case‑by‑case basis, considering these factors. We believe this will ensure fair and competitive compensation for you.#J-18808-Ljbffr

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 indesigning 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 andoptimizingLLM solutions,including open-source model deployments and work in controlled or mission environments,is strongly valued.LocationWashington, DC area, Houston – hybrid in the office 2–3 times per week.What you will be doingDesign and build LLM-based agents that can plan and execute multi-step workflows (task decomposition, state management, memory, and controlled autonomy).Implement andmaintaina 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 toidentifyand prioritize agentic automation opportunities tied to key milestones and requirements.Implement safety and governance controls (permissions, policy checks, audit logs, andappropriate handlingof sensitive data) aligned to operational constraints.What you will needActive 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; experiencewith production services, APIs, and containerization (Docker/Kubernetes) is strongly preferred.Experience deploying and operating workloads onAWS(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, including several of: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.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.One of the most interesting aspects of working at a startup company is gaining equity, which means our success is your success. In addition to equity in the form of options, we also offer:Flexible Time‑Off policy and company holidaysCost‑effective health care, dental, and vision with company contributions401k matching plan with company matchLife insuranceShort‑term and long‑term disability$160,000 - $205,000We value job‑related knowledge and skills, education, and experience. That's why we will determine your actual level and base salary on a case‑by‑case basis, considering these factors. We believe this will ensure fair and competitive compensation for you.#J-18808-Ljbffr

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