Senior AI Developer

Contributions

• Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi-agent workflows, RAG pipelines, and specialized AI microservices.
• Implement reusable AI components, libraries, and APIs that streamline application development and accelerate delivery across programs.
• Integrate AI models with enterprise systems, APIs, data platforms, vector databases, and cloud-native services to deliver scalable mission capabilities.
• Drive iterative experimentation, prototyping, and model improvement cycles in collaboration with Data Scientists and AI Evaluation Scientists.
• Design and implement advanced prompt strategies, context management layers, retrieval systems, and LLM orchestration logic.
• Build scalable inference services, optimize model performance, and collaborate with LLMOps to enable robust deployment, monitoring, and continuous improvement.
• Translate user needs and mission workflows into intuitive, reliable AI-powered features through active partnership with designers and product teams.
• Implement secure-by-design and trustworthy AI practices, including safety guardrails, input sanitization, content filtering, and integration of evaluation metrics.
• Contribute to internal AI frameworks, code patterns, and shared accelerators that raise delivery quality across the AI & Data Exploitation Practice.
• Mentor junior developers, conduct code reviews, and support engineering excellence across multi-disciplinary AI delivery teams.
• Stay current with emerging AI techniques, libraries, foundation models, and agent frameworks, evaluating their applicability to client missions.

• Ability to hold a position of public trust with the U.S. government.
• Bachelor’s, Master’s, or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related field.
• 5+ years of hands‑on software engineering experience, with at least 2+ years focused on AI/ML, generative AI, or LLM‑driven application development.
• Strong proficiency in Python and modern AI frameworks such as PyTorch, Tensor Flow, Hugging Face Transformers, Lang Chain, Llama Index, or similar.
• Demonstrated ability to design and develop production‑grade AI applications, including APIs, back‑end services, orchestration logic, and front‑end integrations when needed.
• Experience implementing RAG architectures, embeddings, vector stores, and context retrieval patterns.
• Familiarity with multi‑agent orchestration frameworks, prompt engineering strategies, and advanced LLM interaction design.
• Strong understanding of cloud platforms (AWS, Azure, GCP), including compute, serverless services, and security fundamentals for AI workloads.
• Working knowledge of containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for AI‑based systems.
• Experience with structured and unstructured data, document processing, and application integration with existing enterprise systems.
• Understanding of responsible AI principles including safety, fairness, privacy, and model risk mitigation.
• Strong analytical and communication skills with the ability to collaborate across engineering, design, and mission domains.
• Proven experience mentoring teammates and raising the technical bar of development teams.
• Must be in the office 3 days per week.