Senior AI/ML Engineer

Essential qualifications:

• 5+ years of engineering, including 2+ years on production retrieval-augmented generation (RAG) or search systems.
• Embeddings, vector databases (Vertex AI Vector Search, pgvector or similar), hybrid search and rerankers.
• LLM evaluation methods and tooling (Ragas, DeepEval, custom judges, golden-set design).
• Strong Python, from prototype through to production code.
   

Desirable qualifications:

• An information retrieval or NLP research background.
• Vertex AI Search, BigQuery, and in-context learning optimization (for example, DSPy).
• Structured report generation and citation grounding.

Key responsibilities:

• Build hybrid retrieval over enterprise sources (vector and keyword search), with reranking and permission-aware filtering.
• Build the precedent store: index decision points with human decisions and rewards, and retrieve the right examples at runtime.
• Deliver report generation and explanation layers with source attribution.
• Build automated evaluation: golden datasets, LLM-as-judge, regression suites, and A/B tests of few-shot strategies.
• Apply the dynamic few-shot approach to the LLM stage of alert triage.

Project Description:

GlobalLogic takes an opportunity to partner with a leading global threat intelligence platform to design and deliver an enterprise-scale, Human-in-the-Loop (HITL) AI agent platform. The initiative centers on accelerating expert analyst decision-making by augmenting high-complexity threat intelligence workflows with cutting-edge generative and agentic AI systems.