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Job Description
Build, deploy, and optimize full-stack AI-powered applications using LLMs, intelligent agents, and machine learning.
Responsibilities
- Design and scale Retrieval-Augmented Generation (RAG) pipelines, vector search systems, and LLM evaluation workflows.
- Create AI agents with frameworks such as LangChain, AutoGen, LlamaIndex, or LangGraph.
- Ingest and process unstructured and structured data (parsing, chunking, embeddings, retrieval).
- Develop intuitive user experiences powered by LLMs and AI agents for real-time workflows.
- Integrate enterprise AI tools such as Claude, GPT‑4/4o, ChatGPT Enterprise, Copilot, Glean, and Shelf.
- Drive document automation and multilingual natural‑language processing (summarization, translation, named‑entity recognition).
- Implement observability, governance, and responsible‑AI practices in compliance with regulations.
- Collaborate with IT, data, compliance, and business leaders to deliver business‑facing solutions.
Qualifications
- 5+ years in software engineering or data science, with 1+ year in GenAI, LLM, or Agentic AI.
- Proficiency in Python, REST APIs, React/Node.js, and cloud‑native infrastructure (Docker, CI/CD).
- Hands‑on experience with AWS AI services (Bedrock, SageMaker, Textract, Translate, etc.).
- Strong knowledge of LLMs, embeddings, prompt engineering, and tool use.
- Proven ability to prototype, iterate, and scale AI‑enabled features.
- Familiarity with compliance/regulatory needs in insurance or financial services (preferred).
- AI‑first developer mindset: using AI for scaffolding, testing, and refactoring code.
- Bachelor of Computer Science (required).
Salary: $85,000–$105,000 per year.