Lead GenAI / AI-ML SME- Contract - Hybrid inCentennial, CO

Elite Technical; Centennial (CO); On-site; USD 180,000 - 280,000; Full time

Job summary

Unknown Telecom Company is seeking two Lead GenAI / AI-ML SME professionals to drive technical strategy for a high-visibility agentic AI program in the telecom space. You will architect solutions at the intersection of large language models and real-world network operations, with direct influence on monitoring, diagnosing, and improving infrastructure.

You will define how AI works, serving as the SME for network anomaly detection, guiding engineering teams, and ensuring architecture decisions

Qualifications

• Proven experience delivering GenAI/LLM-based applications.
• Strong Python software engineering background.
• Experience with LangChain or similar frameworks.
• Experience with LLM APIs, tool calling, and prompts.
• Nice to have cloud AI services knowledge.

Responsibilities

• Architect/design AI/LLM SME for anomaly agentic program.
• Build LLM-powered agents and multi-agent workflows for anomaly detection.
• Develop RAG capabilities linking data sources into an intelligence layer.
• Lead prompt engineering, tool-calling, and agent routing practices.
• Collaborate with architects, data teams, stakeholders to translate needs.
• Drive code reviews and sprint delivery with GenAI team.

Skills

Python

LangChain/LangGraph

LLM APIs & tool calling

RAG & embeddings

Cloud AI services

Tools

LangChain

LangGraph

Job description

Lead GenAI / AI-ML SME

Our client, a multinational telecom technology company, is looking for two Lead GenAI / AI-ML SME's to drive technical strategy on a high-visibility agentic AI program. This is a chance to architect solutions that sit at the intersection of large language models and real-world network operations, with direct influence on how the company's infrastructure is monitored, diagnosed, and improved.

Why This Role Matters:

You will not just implement AI, you will define how it works. As the go-to SME for a network anomaly detection initiative, you will guide technical direction, mentor engineering teams, and see your architecture decisions deployed at scale. This is a high-impact, high-visibility position for someone who wants ownership over cutting-edge GenAI systems rather than a narrow slice of one.

What You Will Do:

• Serve as the AI/ML SME for a network anomaly agentic AI program, shaping solution design and implementation strategy from the ground up
• Design and build LLM-powered agents and multi-agent workflows for anomaly detection, triage, root-cause investigation, and operational insight generation
• Develop RAG capabilities that connect network data, documentation, incident history, and knowledge bases into a unified intelligence layer
• Lead the technical playbook for prompt engineering, tool-calling, agent routing, structured outputs, and evaluation frameworks that keep AI-assisted operations reliable and trustworthy
• Partner with architects, engineers, data teams, product owners, and client stakeholders to translate business and network operations needs into working AI capabilities
• Drive code reviews, architecture discussions, and sprint delivery while sharing knowledge across the broader GenAI engineering team

Required Skills

Required:

• 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.

• Working knowledge of cloud AI services, APIs, databases, observability, testing, and production deployment practices.

Preferred:

• Experience with network operations, anomaly detection, incident analysis, telecommunications, or enterprise operations use cases preferred.

• AWS, Azure, or Google Cloud AI/ML certification preferred.

• Relevant certification or training in artificial intelligence, machine learning, data engineering, cloud architecture, or software engineering preferred.

• Network, telecom, or operations-focused certifications are a plus.