Senior Agentic AI Software Engineer
Senior engineer builds autonomous AI agents and retrieval systems to modernize legacy software for federal healthcare, delivering explainable, traceable answers from decades of source code.
- Compensation
- $140K–$180K / yr
- Location
- United States - Remote
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- 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.
Nice to have
- 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.
Full description
Location: United States – Remote
Clearance: Ability to obtain and maintain a Public Trust
LTS is seeking a Senior Agentic AI Software Engineer to build the intelligence behind the platform—the autonomous agents, orchestration layers, retrieval pipelines, reasoning workflows, and backend services that transform complex legacy software into actionable engineering knowledge.
The Agentic AI platform is designed to help engineers understand, analyze, and modernize one of the most consequential legacy software systems still operating today.
Our platform enables engineers to ask questions in plain English and receive explainable, verifiable answers traced directly back to decades of production source code. Rather than replacing engineers, we're building AI that accelerates engineering through transparency, traceability, and intelligent reasoning.
We're building an AI-native engineering platform supporting the modernization of mission-critical healthcare systems serving millions of Veterans nationwide. Every response generated by the platform must be explainable, grounded in evidence, and trusted by engineers responsible for maintaining software that millions of people quietly depend on every day.
The platform is designed for deployment across federal enterprise environments and is being engineered to align with FedRAMP security controls, Zero Trust principles, and federal compliance requirements.
The product has executive sponsorship, committed users, and a customer investing in long-term modernization. Our engineering team is intentionally small. Every engineer has meaningful ownership, significant technical influence, and the opportunity to help define how AI transforms software engineering.
We don't simply build AI-powered software—we build software with AI. This is not another chatbot.
Using LLMs, autonomous agents, AI-assisted development, parallel workflows, and model-driven engineering is simply how we work.
What You’ll Do:Build Intelligent Agentic Systems
- 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.
Engineer Enterprise Retrieval & Knowledge Systems
- Design and optimize Retrieval-Augmented Generation (RAG) pipelines including document ingestion, embeddings, hybrid retrieval, reranking, semantic search, context engineering, and prompt orchestration.