Lead AI Engineer

Role: Lead GenAI/AI-ML SME

Location: Denver, Colorado (onsite client interview and worksite)

Duration: 12+ Months

Our client is seeking a Lead GenAI/AI-ML Subject Matter Expert (SME) to help design and deliver an agentic AI program focused on network anomaly detection, investigation, and operational intelligence. This role will provide technical leadership across LLM-powered agents, retrieval-augmented generation, prompt engineering, and AI solution design while partnering with architecture, data, product, and client stakeholders.

Responsibilities:

• Serve as the AI/ML SME for a network anomaly agentic AI program, advising on solution design, technical direction, and implementation approach.
• 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, documentation, incident history, knowledge bases, and operational procedures.
• Lead prompt engineering, tool-calling, agent routing, structured outputs, and evaluation patterns for reliable AI-assisted network operations.
• Partner with architects, engineers, data teams, product owners, and client stakeholders to convert business and network operations needs into actionable AI capabilities.
• Support code reviews, architecture discussions, sprint delivery, documentation, and knowledge sharing across the GenAI engineering team.

Requirements and Skills:

• 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, and incident analysis. Telecommunications or enterprise operations use cases preferred.
• Working knowledge of cloud AI services, APIs, databases, observability, testing, and production deployment practices.

Preferred Certifications:

• 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.

Tech Stack:

Primary Technologies:

• Core AI/GenAI Python, LLMs, LangChain, LangGraph, RAG, prompt engineering, and tool calling agents.
• Network Anomaly Program.
• Network anomaly detection, incident triage, root-cause investigation, operational intelligence.
• Data and search vector search, embeddings, hybrid retrieval, OpenSearch, Pinecone, pgvector, and PostgreSQL.

Secondary Skills:

• Cloud AI services, observability, testing, and production deployment practices.
• Lead GenAI / AI-ML SME – Network Anomaly Agentic Program.