Staff AI Engineer: End-to-End LLM Architect (Hybrid)

Relativity; Alton (IL); Hybrid; USD 174,000 - 262,000; Full time

Job summary

Relativity is seeking a hands-on Staff Engineer to own how Discovery systems are built, evaluated, and operated. You will shepherd end-to-end inference paths, from retrieval to outputs, and ensure robust observability in a multi-tenant cloud environment.

You will define evaluation metrics, optimize latency budgets, and collaborate across domains—engineering, product, and design—to deliver defensible, scalable solutions for legal data processing at scale.

Qualifications

• 7+ years building and operating large-scale distributed cloud systems.
• 3+ years shipping production model-backed systems.
• Depth across LLMs, RAG, agentic workflows, and vector/hybrid search.
• Owned an evaluation practice with eval sets, metrics and gates.
• Architecture accountability across cloud services in multi-tenant SaaS.
• Quantitative reasoning for model behavior including accuracy, latency, cost.
• Strong technical leadership and the ability to present tradeoffs to executives.

Responsibilities

• Staff engineers set technical direction across teams and build the hardest parts from prototype through production.
• Own the inference path end to end including retrieval, context construction, routing, and observability.
• Set the evaluation bar with gold sets, offline suites, CI gates, and online telemetry.
• Own token economics and latency budgets; decide routing, caching, and model tier based on data.
• Design for reuse by decoupling capability logic from delivery harness via interface contracts.
• Architect the data and retrieval layer including indexing, embedding, and hybrid search.
• Engineer defensibility with citation fidelity, confidentiality controls, and auditability.
• Lead root-cause analysis, publish learnings, and raise engineering standards.
• Collaborate across domains with Applied Science, Product, Design, and peers to drive closure.

Skills

Distributed systems

Production ML models

LLMs & RAG

Evaluation practice

Cloud architecture

Quantitative reasoning

Technical leadership

Job description

Relativity is seeking a hands-on Staff Engineer to own how Discovery systems are built, evaluated, and operated. You will shepherd end-to-end inference paths, from retrieval to outputs, and ensure robust observability in a multi-tenant cloud environment.

You will define evaluation metrics, optimize latency budgets, and collaborate across domains—engineering, product, and design—to deliver defensible, scalable solutions for legal data processing at scale.