Job Description RESPONSIBILITIES • Design and implement agentic AI systems that enable autonomous decision-making, workflow orchestration, and mission process optimization—with appropriate guardrails and human oversight. • Develop Generative AI applications for summarization, extraction, predictive insights, and conversational interfaces. • Build and maintain scalable data pipelines integrating structured and unstructured data to support analytics and AI workloads. • Apply advanced statistical and machine learning techniques to decision support and policy/program evaluation. • Lead AI initiatives spanning Retrieval-Augmented Generation (RAG) and evaluation, Re-ranking strategies, and retrieval quality optimization. • Perform prompt engineering, safety patterns, and defensive design. • Integrate knowledge graphs and develop graph-enhanced retrieval solutions. • Create and fine-tune embeddings and LLMs to enhance domain performance, accuracy, and robustness. • Develop entity graphs using entity resolution techniques to enable graph analytics and improved retrieval. • Collaborate across engineering, security, and stakeholder teams to prototype rapidly, iterate responsibly, and deliver mission-ready outcomes. • Lead deployment in AWS cloud environments utilizing Infrastructure-as-Code, DevOps/DevSecOps, and operational excellence practices. • Own and drive the technical foundation and delivery process for mission AI solutions, including system architecture, tooling, engineering and delivery standards, and hands-on technical leadership. REQUIREMENTS • Must be able to OBTAIN and MAINTAIN a Federal or DoD "PUBLIC TRUST"; candidates must obtain approved adjudication of their PUBLIC TRUST prior to onboarding with the client. Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred. • Bachelor’s degree in Engineering, IT, Computer Science, or related field (or equivalent experience). • Minimum EIGHT (8) years in solutions architecture, software engineering, data engineering, and/or applied ML with a track record of delivering production systems. • Strong Python proficiency and strong SQL skills (data modeling, query optimization). • Experience designing and delivering cloud-based AI/ML solutions end-to-end (ingestion, modeling, deployment, monitoring) in secure environments. • Hands-on experience with AI application frameworks such as LangChain, Haystack, crewAI, or similar. • Strong knowledge of core Python ML/data libraries: NumPy, Pandas, Scikit-learn, NLTK, OpenCV. • Familiarity with deep learning frameworks such as PyTorch or TensorFlow. • Experience with search technologies such as Elasticsearch or OpenSearch. • Experience with relational databases (PostgreSQL, Oracle) and in-memory analytics engines (DuckDB). • Experience using cloud SDKs (e.g., Boto3) and building reliable integrations with cloud services. • Familiarity with agentic AI frameworks such as AWS Strands Agents, PydanticAI, and related orchestration patterns. • Advanced prompt engineering skills for complex reasoning workflows beyond code generation. • Experience with asynchronous Python development (asyncio, concurrency, reliability). • Experience with MCP servers and tool-calling within agentic workflows (tool governance, security considerations).
