Implement AI components within existing systems and workflows to support operational use.
Design and manage interfaces and APIs that connect AI models to enterprise platforms.
Ensure reliable production performance by monitoring data flows, validating system interactions, and resolving integration issues.
Collaborate with software, data, and platform engineering teams to maintain stable and efficient AI deployment across the enterprise.
Prepare, maintain, and execute a System Engineering Plan (SEP) for managing all systems architecture and system engineering related aspects of the program.
Conduct systems engineering activities required to specify, build, and maintain system engineering designs for the System.
Design, prepare, and document systems engineering and cybersecurity artifacts for the System.
Establish and maintain an existing System Requirements management environment and associated system requirements management process for the System.
Support the Government in recommending and conducting enterprise system architecture activities to fully define and scope the System.
Define, document, maintain, and promulgate APIs and technical standards for using and interoperating within and outside the System.
Design, engineer, integrate, and continuously improve the underlying infrastructure of the System.
Identify, prepare, track, secure, and integrate government, commercial, and open-source tools and services into the System.
Design, architect, engineer, and continuously improve the user interface (UI) and user experience (UX) components of the Platform.
Design, build, and maintain services and products to effectively make production-ready AI/ML models accessible for customer use.
Design, architect, engineer, and continuously improve all aspects of cybersecurity elements of the System.
Perform site reliability engineering to build and maintain a reliable, scalable, and efficient System.

Requirements

Active Top Secret (TS) clearance with SCI eligibility.
Bachelor’s degree in Computer Science, Engineering, Information Systems, Artificial Intelligence, or related technical discipline and 8–12 years of relevant experience OR Master’s degree in a related field and 6–10 years of relevant experience.
Experience with designing and managing interfaces and APIs for AI models.
Proficiency in monitoring data flows, validating system interactions, and resolving integration issues.
Experience with cloud environments, network, data storage, logging, and auditing functions.
Knowledge of cybersecurity policies and requirements, including NIST security controls and Zero Trust compliance.
Experience with DevSecOps/Factory functions and mission spaces.
Ability to design and maintain system engineering and cybersecurity artifacts.
Experience developing Agentic AI solutions, including autonomous planning–execution–reflection loops, multi-agent collaboration and coordination, and tool usage patterns including API integration, retrieval-augmented generation (RAG), and memory/context management.
Solid understanding and hands-on experience with generative AI models including prompt engineering, chain-of-thought reasoning, and Natural Language Processing (NLP) tasks such as entity extraction, summarization, and semantic search.
Working knowledge of Large Language Models (LLMs) and agent frameworks such as LangChain, LangGraph, CrewAI, A2A, MCP, or AutoGen.
Experience using vector databases (e.g., Pinecone, Weaviate, FAISS).

Benefits

Health and Wellness programs
Income Protection
Paid Leave
Retirement

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI components implementationAPI design and managementdata flow monitoringsystem interaction validationintegration issue resolutionsystem engineeringcybersecurity artifact documentationDevSecOpsAgentic AI solutions developmentNatural Language Processing

Soft Skills

collaborationproblem-solvingcommunicationorganizational skillsattention to detail

Certifications

Top Secret (TS) clearance with SCI eligibility