Senior Generative AI Software Developer with a strong foundation in working with large language models (LLMs) and a keen interest in building intelligent,

Senior Generative AI Software Developer with a strong foundation in working with large language models (LLMs) and a keen interest in building intelligent, agentic systems - RITM0169299

1 year contract, possibilities of extensions. Hybrid in office, 3 days/week in Richmond Office

Must Have:

• 5+ years of software development experience, including recent work with LLMs or AI integration.
• Proficiency in Python and experience with AI/ML frameworks (e.g., OpenAI SDKs, LangChain, Hugging Face)
• Experience in C#, .NET Core, and object-oriented design
• Interest and understanding of agent-based design concepts and tools (AutoGen, Semantic Kernel, etc.)
• Familiarity with RAG, GraphRAG, embeddings, and vector databases such as Cosmos DB, pgvector, or Qdrant.
• Experience deploying solutions to the cloud (Azure preferred)
• Knowledge of APIs, CI/CD pipelines, Git, and Agile software development practices
• Ability to synthesize complexity and communicate AI capabilities clearly to diverse audiences
• Bachelor’s degree in Computer Science or a related STEM field

Specific Responsibilities and Deliverables:

• Design and build applications using OpenAI, Azure OpenAI, and open-source LLMs
• Develop and optimize Retrieval-Augmented Generation (RAG) pipelines
• Explore and implement foundational patterns for multi-agent AI systems using tools like AutoGen, LangChain, or Semantic Kernel
• Integrate LLMs into enterprise workflows and digital products
• Use vector databases such as Qdrant, pgvector, and Cosmos DB
• Leverage Azure AI services and models to enhance capabilities and performance
• Collaborate with product teams and data scientists to test, refine, and deliver AI use cases
• Develop prompt strategies, memory handling, and task chaining
• Maintain clear documentation of models, architecture, and decision-making
• Stay current with research and best practices in generative and agentic AI
• Collaborate with cross-functional teams to transition validated concepts to production
• Participate in Agile ceremonies, code reviews, and DevOps practices
• Maintain technical documentation and participate in system architecture decisions
• Provide mentorship to junior developers and support knowledge sharing

Deliverables:

• Prototypes and fully developed, production-grade applications that demonstrate generative and agentic AI capabilities
• Integration of LLM-based solutions into existing enterprise environments
• Documentation of models, prompts, workflows, and architectures
• Regular stakeholder updates and demo presentations
• Contributions to reusable components and AI development patterns