Software Engineer AI

Ai Integration & Development

Design and implement LLM-based features and pipelines using frameworks such as LangChain and LangGraph. Build and maintain Retrieval-Augmented Generation (RAG) systems, including vector store management, chunking strategies, embedding pipelines, and retrieval optimization.

Duties & Responsibilities

• Rapidly explore and evaluate new AI capabilities, tools, and approaches. Translate ambiguous problem statements into working prototypes that demonstrate value and inform product direction.
• Meet regularly with IT colleagues, product owners, and stakeholders to understand business needs and translate them into well-scoped AI engineering solutions. Communicate tradeoffs clearly across technical and non-technical audiences.
• Maintain and improve existing AI-integrated systems, troubleshoot pipeline failures, and take corrective action on issues related to retrieval quality, prompt behavior, or model outputs.
• Contribute to project teams by delivering on assigned tasks and action items, participating in agile ceremonies, and supporting delivery against team goals.

Requirements

• Core Competencies:
  • Proficiency in Python for AI/ML development and backend service integration.
  • Hands-on experience with LangChain and/or LangGraph for building agentic and multi-step LLM workflows.
  • Strong understanding of RAG pipelines end-to-end: document ingestion, chunking, embedding, vector storage, and query-time retrieval.
  • Familiarity with leading LLM providers and APIs (e.g., OpenAI, Anthropic, Azure OpenAI, AWS Bedrock).
  • Experience with evaluation and testing of AI systems, including retrieval quality metrics, LLM output assessment, and regression testing for prompt changes.
  • Understanding of AI observability and experimentation tooling (e.g., LangSmith, Weights & Biases, or equivalent).
  • Solid foundation in software engineering practices: version control (Git), CI/CD, and containerization (Docker).
  • Effective communication skills with the ability to explain AI system behavior and limitations to non-technical stakeholders.
• Senior Software Engineer:
  • Associate degree in Computer Science or MIS with a minimum of 4 years experience; or Bachelor degree in Computer Science, or MIS, with a minimum of 2 years of experience; or a Master degree in Computer Science, MIS, with minimum 1 year of experience; or relevant Business or IT experience of minimum of 4 years.
  • Hands-on experience building and shipping software in Python, with working knowledge of REST API development and integration patterns.
  • Practical understanding of RAG architectures, including embedding models, vector databases (e.g., FAISS, Chroma, Pinecone, Weaviate), and retrieval strategies.
  • Familiarity with prompt engineering techniques, including few-shot prompting, chain-of-thought, and system prompt design.
  • Knowledge of software development lifecycle and experience working on agile project teams.
• Principal Software Engineer:
  • Associate degree in Computer Science, MIS or a related field with a minimum of 7 years experience; or Bachelor degree in Computer Science, or MIS, with a minimum of 5 years of experience; or a Master degree in Computer Science, MIS, with minimum 3 years of experience; or relevant Business or IT experience of minimum of 7 years.
  • Minimum of 4 years of programming preferred.
  • Experience with agentic AI patterns including tool use, multi-agent orchestration, memory management, and reasoning loops using LangGraph or similar frameworks.
  • Exposure to healthcare data standards (e.g., FHIR/HL7) and regulated or privacy-sensitive environments.
  • Experience with structured output generation, function calling, and tool-augmented LLMs.
  • Comfort working with AI-assisted development environments (e.g., GitHub Copilot, Cursor) while maintaining code quality and security standards.
  • Comfort with lightweight discovery methods such as analytics, user interviews, and partnering with design and UX research to validate AI-driven solutions.
  • Interest in responsible AI practices, including bias evaluation, content moderation, and ethical deployment considerations.

Eligibility Requirements

• Must be legally authorized to work in the United States without restriction.
• Must be willing to take a drug test and post-offer physical (if required).
• Must be 18 years of age or older.