Technology

Senior GenAI Engineer

Goldenpick Technologies LLCUnited States🇺🇸United StatesPosted Oct 5, 2026

Quick Overview

Seniority

Mid Senior

Work mode

Hybrid

Location

United States

Posted

22 hours ago

DockerFastAPIAWSAzureGPTGitGoogle CloudLLMPhoenixPythonREST

Role: Senior GenAI Engineer
Location : Remote

Responsibilities

Design, develop and maintain scalable backend services and APIs using Python and FastAPI.
Build and integrate LLM-powered features using OpenAI GPT and Anthropic Claude models.
Develop and maintain MCP (Model Context Protocol) servers using FastMCP to expose enterprise tools and data to AI agents.
Create and extend Skills and Plugins that enhance LLM capabilities for business-specific workflows.
Design and implement Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking, embedding and retrieval strategies.
Build agentic solutions using LLM orchestration frameworks such as LangChain, LangGraph or similar.
Work with vector databases to support semantic search and knowledge retrieval.
Implement observability and diagnostics for LLM applications: tracing, logging, evaluation, token and cost tracking, latency and quality monitoring.
Own the full application lifecycle: development, testing, deployment and production support.
Use AI-assisted development tools (Claude, Codex) to accelerate delivery while maintaining code quality.
Collaborate with client stakeholders, architects and business analysts to translate requirements into working solutions.
Ensure solutions meet enterprise standards for security, data privacy and responsible AI use.

Skills Must have

4+ years of professional software development experience with a strong focus on Python.
Solid experience building production REST APIs with FastAPI (or a comparable framework).
Hands-on experience integrating LLMs (OpenAI GPT, Anthropic Claude) into real applications, including prompt engineering, tool/function calling and structured outputs.
Practical experience with MCP servers (FastMCP preferred) and LLM tool ecosystems (Skills, Plugins).
Proven experience designing and implementing RAG pipelines.
Experience building agentic workflows with orchestration frameworks such as LangChain, LangGraph, LlamaIndex or similar.
Hands-on experience with at least one vector database (e.g., Pinecone, Weaviate, Qdrant, Chroma, pgvector, Azure AI Search).
Experience with observability and diagnostics for LLM systems (e.g., LangSmith, Langfuse, Arize Phoenix, OpenTelemetry).
Experience deploying and running applications in production: Docker, CI/CD, and at least one major cloud platform (AWS, Azure or Google Cloud Platform).
Daily, confident use of modern development tools including VS Code and AI coding assistants such as Claude and Codex.
Strong understanding of software engineering best practices: clean code, testing, code review, version control (Git).
Upper-Intermediate (B2) or higher English, with the ability to communicate directly with US-based stakeholders.