GenAI & AI/ML Architect - LLM Apps, RAG & LangChain

Zenith System Solutions; Denver (CO); On-site; USD 120,000 - 190,000; Full time

Job summary

Zenith System Solutions in Denver, CO seeks a skilled AI/ML software engineer with strong Python and GenAI experience to deliver LLM-based applications. You will work with LangChain and LangGraph, design RAG solutions, and implement streaming, tool calls, and agent orchestration patterns.

The role requires you to act as a technical SME with clear communication to stakeholders, and to contribute to design, testing, and deployment of cloud AI services, APIs, and observability practices.

Qualifications

• Strong Python software engineering experience with hands‑on GenAI, AI/ML, or LLM‑based application delivery.
• Experience with LangChain, LangGraph, or equivalent agentic AI frameworks.
• Strong understanding of LLM APIs, tool calling, prompt engineering, structured outputs, streaming, and agent orchestration patterns.
• Experience designing RAG solutions using embeddings, vector search, hybrid retrieval, re‑ranking, and answer generation.
• Ability to operate as a technical SME with strong communication, consulting, solution design, and stakeholder‑facing skills.
• Experience with network operations, anomaly detection, incident analysis, telecommunications, or enterprise operations use cases preferred.
• Working knowledge of cloud AI services, APIs, databases, observability, testing, and production deployment practices.

Skills

Python

GenAI

LLM APIs

prompt engineering

LangChain

LangGraph

agent orchestration

RAG

vector search

hybrid retrieval

Tools

LangChain

LangGraph

Job description

Zenith System Solutions in Denver, CO seeks a skilled AI/ML software engineer with strong Python and GenAI experience to deliver LLM-based applications. You will work with LangChain and LangGraph, design RAG solutions, and implement streaming, tool calls, and agent orchestration patterns.

The role requires you to act as a technical SME with clear communication to stakeholders, and to contribute to design, testing, and deployment of cloud AI services, APIs, and observability practices.