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

We are 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.

Role Summary
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. 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, 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
Category Primary Technologies
Core AI / GenAI: Python, LLMs, LangChain, LangGraph, RAG, prompt engineering, 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, PostgreSQL
Secondary Skills: Cloud AI services, observability, testing, and production deployment
practices. Lead GenAI / AI-ML SME - Network Anomaly Agentic Program