Lead GenAI / AI-ML SME – Network Anomaly Agentic Program

Zenith System Solutions; Denver (CO); On-site; USD 150,000 - 210,000; Full time

Job summary

Zenith System Solutions in Denver seeks a hands-on GenAI/AI-ML SME to architect AI solutions for network anomaly use cases. You will lead LLM agent development, design RAG workflows, and guide multi‑agent orchestration while collaborating with client teams.

The role emphasizes production-grade AI delivery, consulting skills, and ability to translate operations requirements into scalable agentic capabilities. Onsite work and client interactions are required.

Qualifications

• Hands-on AI/ML SME with strong software engineering discipline.
• 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 work as a technical SME with strong communication, consulting, solution design, and stakeholder management skills.
• Working knowledge of cloud AI services, APIs, databases, observability, testing, and production deployment practices.
• Experience with network operations, anomaly detection, incident analysis, telecommunications, or enterprise operations is preferred.

Responsibilities

• Serve as the AI/ML SME for a network anomaly Agentic AI program, providing guidance on solution design, technical direction, and implementation approaches.
• Design and develop LLM‑powered agents and multi‑agent workflows for network anomaly detection, triage, root‑cause investigation, and operational insight generation.
• Build RAG capabilities using network data, technical documentation, incident history, knowledge bases, and operational procedures.
• Lead prompt engineering, tool calling, agent routing, structured outputs, and evaluation methods to ensure reliable AI‑assisted network operations.
• Collaborate with architects, engineers, data teams, product owners, and client stakeholders to translate business and network operations requirements into actionable AI capabilities.
• Support code reviews, architecture discussions, sprint delivery, technical documentation, and knowledge sharing across the GenAI engineering team.

Skills

Python

LangChain

LangGraph

LLM APIs

RAG design

Prompt engineering

Agentic AI

Cloud AI services

Tools

APIs integration

Job description

Role:Lead GenAI / AI-ML SME – Network Anomaly Agentic Program

Job ID: DOX1JP00011511

Employment Type: Full Time

Work Mode: Onsite – Client Interview and Worksite

Role Overview

The ideal candidate is a hands-on AI/ML SME with strong software engineering discipline, deep GenAI delivery experience, and the consulting skills needed to translate network operations requirements into scalable Agentic AI capabilities. Production monitoring experience is a valuable secondary skill, but the primary focus is AI solution architecture, LLM agent development, RAG design, and network anomaly use‑case delivery.

Job Duties and Responsibilities

• Serve as the AI/ML SME for a network anomaly Agentic AI program, providing guidance on solution design, technical direction, and implementation approaches.
• Design and develop LLM‑powered agents and multi‑agent workflows for network anomaly detection, triage, root‑cause investigation, and operational insight generation.
• Build RAG capabilities using network data, technical documentation, incident history, knowledge bases, and operational procedures.
• Lead prompt engineering, tool calling, agent routing, structured outputs, and evaluation methods to ensure reliable AI‑assisted network operations.
• Collaborate with architects, engineers, data teams, product owners, and client stakeholders to translate business and network operations requirements into actionable AI capabilities.
• Support code reviews, architecture discussions, sprint delivery, technical documentation, and knowledge sharing across the GenAI engineering team.

Required Qualifications and Skills

• Strong Python software engineering experience with hands‑on delivery of GenAI, AI/ML, or LLM‑based applications.
• 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 work as a technical SME with strong communication, consulting, solution design, and stakeholder management skills.
• Working knowledge of cloud AI services, APIs, databases, observability, testing, and production deployment practices.
• Experience with network operations, anomaly detection, incident analysis, telecommunications, or enterprise operations is preferred.

Preferred Certifications

• AWS, Azure, or Google Cloud AI/ML certification.
• Relevant certifications or training in artificial intelligence, machine learning, data engineering, cloud architecture, or software engineering.
• Network, telecom, or operations‑focused certifications.

Primary Skills

Core AI / GenAI

• Python
• LangChain and LangGraph
• Retrieval-Augmented Generation (RAG)
• Tool‑calling agents and multi‑agent workflows