Senior Agentic AI Software Engineer

• Design, develop, and deploy autonomous and multi-agent AI systems capable of reasoning, planning, tool use, workflow automation, and human-in-the-loop collaboration.
• Build intelligent orchestration pipelines coordinating LLMs, specialized agents, enterprise tools, and structured reasoning workflows.
• Develop reusable agent architectures and orchestration patterns that accelerate intelligent application development across the platform.

• Design and optimize Retrieval-Augmented Generation (RAG) pipelines including document ingestion, embeddings, hybrid retrieval, reranking, semantic search, context engineering, and prompt orchestration.
• Integrate AI systems with source code repositories, enterprise documentation, APIs, structured data, and knowledge repositories.
• Ensure every AI-generated response is explainable, evidence-based, and traceable to authoritative sources.

• Design and implement scalable backend services, APIs, and cloud-native applications supporting enterprise AI workloads.
• Develop distributed systems capable of serving low-latency AI experiences while maintaining security, reliability, and observability.
• Optimize performance, latency, throughput, model quality, and infrastructure cost across production AI systems.

• Implement testing, evaluation, monitoring, observability, guardrails, and LLMOps practices to ensure AI systems remain trustworthy and production-ready.
• Continuously evaluate emerging models, frameworks, and engineering practices to improve platform capabilities.
• Build AI systems that behave predictably in highly regulated enterprise environments.

• Partner closely with AI architects, platform engineers, front-end engineers, designers, and product leaders to deliver cohesive AI-powered experiences.
• Mentor engineers through technical leadership, architecture discussions, design reviews, and collaborative problem solving.
• Help establish engineering standards, reusable frameworks, and best practices across the AI engineering organization.

• Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Engineering, or a related technical discipline (or equivalent professional experience).
• 7+ years of professional software engineering experience designing and building distributed production systems.
• At least 3 years designing, developing, and deploying production AI applications beyond proof-of-concept environments.
• Strong proficiency in Python and modern backend software engineering.
• Experience building enterprise APIs, microservices, and cloud-native applications.
• Hands-on experience developing applications powered by Large Language Models (LLMs) and Generative AI.
• Experience building Agentic AI solutions using frameworks such as LangGraph, LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or comparable technologies.
• Strong experience designing Retrieval-Augmented Generation (RAG) architectures including embeddings, vector search, hybrid retrieval, reranking, context engineering, and grounding techniques.
• Experience integrating AI systems with enterprise APIs, databases, cloud platforms, and business applications.
• Experience with Docker, Kubernetes, Git, CI/CD pipelines, and modern DevOps practices.
• Strong understanding of software architecture, testing, observability, debugging, and production operations.
• Excellent communication skills with the ability to explain complex technical concepts to both engineering and business stakeholders.
• Ability to solve difficult engineering problems from first principles.
• Ability to think deeply about system architecture, reliability, and scalability.
• Passionate about explainability as model performance.
• Ability to move comfortably between distributed systems, AI frameworks, and product engineering.
• Willingness to take ownership of ambiguous, high-impact technical challenges.
• Background with using AI coding assistants, autonomous agents, and model-driven engineering workflows.
• A technically skilled engineer with a preference for building products that create lasting impact over incremental feature development.

• Experience developing multi-agent AI systems and collaborative agent workflows.
• Experience with OpenAI, Azure OpenAI, Anthropic Claude, Google Vertex AI, AWS Bedrock, or open-source LLMs.
• Experience with vector databases such as Pinecone, Weaviate, Qdrant, Milvus, or Azure AI Search.
• Experience implementing LLMOps or MLOps practices.
• Familiarity with graph databases, knowledge graphs, or dependency analysis.
• Experience working with software engineering tools, code intelligence platforms, or developer productivity products.
• Experience building AI systems in healthcare, Federal Government, or other highly regulated environments.
• Familiarity with Responsible AI, AI governance, privacy, security, and compliance best practices.
• Experience using AI coding assistants and autonomous agents as part of daily software development.

• The Opportunity to support high-visibility federal missions
• A culture that values innovation, growth, and collaboration
• Access to cutting-edge tools and technologies
• Comprehensive benefits for you and your family
• A career path that rewards ambition and performance

If you’re ready to push boundaries, sharpen your skills, and join a team that is passionate about building what’s next, we’d love to meet you. Apply today and let’s build a future together!