Senior AI Engineer

Note: This is a Hybrid Role - 3 days per week in our office in McLean VA

• Architect and build multi-agent systems and autonomous workflows for document analysis requirement extraction RFP response generation and procurement pipeline automation.
• Design and implement agentic orchestration using frameworks such as LangGraph AutoGen CrewAI or custom-built solutions tailored to Rohirrims platform requirements.
• Develop tool-using reasoning and planning capabilities that enable agents to decompose complex acquisition problems into executable subtasks.
• Build robust human-in-the-loop and approval gates for high-stakes decision points within automated workflows.

• Design and optimize Retrieval-Augmented Generation (RAG) pipelines to ground agent outputs in authoritative procurement data regulations (FAR/DFARS) past performance records and institutional knowledge.
• Implement advanced retrieval strategies including hybrid search re-ranking and context-aware chunking across large heterogeneous document corpora.
• Develop document parsing and structuring pipelines for RFPs SOWs PWS solicitations and other complex government acquisition artifacts.

• Select and integrate appropriate LLMs (commercial and open-source) for specific agent tasks balancing capability latency cost and security requirements.
• Build evaluation frameworks to systematically test agent accuracy hallucination rates and task completion against procurement-specific benchmarks.
• Implement prompt engineering best practices including structured outputs chain-of-thought reasoning and few-shot prompting optimized for acquisition workflows.

• Collaborate with platform engineers to deploy agents in production with observability logging tracing and graceful failure handling.
• Contribute to shared tooling internal SDKs and reusable agent components that accelerate development across the engineering team.
• Participate in architecture reviews code reviews and technical planning sessions with a focus on scalability and maintainability.

• 8 years of software engineering experience with at least 1 year focused on LLM applications AI agents or applied ML systems in production.
• Strong Python proficiency; experience building production-grade AI/ML pipelines.
• Hands-on experience with LLM orchestration frameworks (LangChain LangGraph AutoGen or equivalent).
• Deep understanding of RAG architectures vector databases (Pinecone Weaviate pgvector or similar) and embedding models.
• Experience integrating APIs from frontier model providers and tuning prompts for structured and reliable results
• Strong software engineering fundamentals: clean architecture testing observability and version control best practices.

• Experience building AI products for regulated enterprise environments.
• Familiarity with federal acquisition regulations (FAR DFARS) or proposal management processes.
• Experience with fine-tuning or instruction-tuning open-source LLMs (LLaMA Mistral etc.).
• Knowledge of secure-by-design principles and air-gapped or FedRAMP-compliant deployment environments.
• Active Secret or TS/SCI security clearance (or ability and eligibility to obtain).
• Experience with cloud infrastructure on AWS Azure or GCP; containerization with Docker/Kubernetes.

• A collaborative IC that is excellent at giving and receiving technical feedback communicating trade-offs clearly and elevating teammates.
• Ability to help define how agentic AI gets implemented in a SaaS company

Required Experience:

Senior IC