Agentic AI Developer

Job Description:

Agentic AI Developer

Location:

Charlotte, NC (preferred for hybrid work; open to remote for strong candidates

Build and ship production agentic AI features agents, tools, prompts, evals, and integrations against an established reference architecture.

Required Qualifications:

" 3 8 years of experience in software development or data engineering
" Hands-on experience in Generative AI or LLM-based applications
" Experience building APIs, microservices, or distributed systems
" Bachelor s or Master s degree in Computer Science, AI/ML, Data Science, or related field

Key roles:
" Implement agents and sub-agents (planner, executor, critic, router) using Claude Agent SDK / Lang Graph
" Build tools and MCP integrations, design clean tool schemas, idempotent operations, and robust error handling.
" Implement RAG pipelines: ingestion, chunking, embedding (Bedrock Titan), hybrid retrieval, citation rendering.
" Develop Fast API/Python services exposing agent capabilities (sync + streaming); integrate with SQL (Postgres) and object stores (S3).
" Write evaluation harnesses (golden sets, regression suites, LLM-as-judge) and trace/observe agent runs.
" Implement guardrails: input/output validation, schema enforcement, rate limiting, prompt-injection defenses.
" Participate in code reviews, pairing, and architecture discussions; own quality of the code you ship.
" Strong Python (FastAPI, async, Pydantic) or Node/Type Script equivalent.
" Hands-on with at least one agent framework (Claude Agent SDK / Lang Graph / Auto Gen).
" Practical experience with LLM tool/function calling, structured outputs, streaming.
" RAG implementation experience (pgvector / FAISS / Open Search).
"Git, CI/CD, containerization (Docker), and cloud basics (AWS preferred).

Roles/Responsibilities:
" Implement single-agent and multi-agent systems using frameworks such as Lang Chain, Semantic Kernel, CrewAI, Auto Gen, or similar
" Build applications using LLMs (Azure OpenAI, OpenAI, Anthropic, etc.)
" Implement Retrieval-Augmented Generation (RAG) pipelines
" Enable agents to coordinate and collaborate in multi-agent ecosystems
" Build secure, scalable APIs and microservices to support AI agents
" Develop evaluation frameworks for agent performance (accuracy, hallucination detection, response quality)
" Monitor system behavior and continuously improve reliability
" Optimize performance for latency, cost, and scalability Years of

Experience:

8 Years of Experience