Artificial Intelligence Engineer

Core Responsibilities

• Advanced RAG & Search Pipelines: Architect hybrid retrieval systems utilizing vector embeddings, semantic search, lexical indexing (BM25), reranking, metadata filtering, chunking strategies, and grounding mechanics.

• Knowledge & Graph Representation: Design entity resolution, relationship inference models, and dynamic knowledge graphs to map software entities, code ownership, controls, vulnerabilities, and provenance.

• Code Intelligence Systems: Build deep code-indexing tooling leveraging AST parsing, call graphs, reference resolution, and compiler/LSP protocol primitives.

• Data Ingestion & Pipelines: Construct low-latency ingestion mechanisms that normalize, enrich, and continually sync structured and unstructured context across complex enterprise data streams.

• Evaluation & System Health Tracking: Establish robust evaluation frameworks to benchmark retrieval precision/recall, minimize hallucinations, enforce citation accuracy, track system health, and optimize latency/cost trade-offs in live releases.

• Cross-Functional Synergy: Partner with Product, Platform, and Cyber Security teams to translate ambiguous enterprise requirements into production-grade knowledge infrastructure.

What You’ll Bring

• Core Software Engineering: Strong background in building complex backend, data, or AI infrastructure in high-scale environments.

• Applied IR & RAG Depth: Demonstrated experience deploying production search, vector databases, dense/sparse hybrid retrieval, reranking models, and LLM orchestration tools.

• Information Retrieval Foundations: Mastery of indexing, query expansion, relevance scoring metrics, BM25 algorithms, and search evaluation strategies.

• Code Intelligence & Parsing: Hands-on expertise with AST-level parsing, symbol resolution, control/data-flow analysis, or LSP integrations.

• Data Systems: Experience processing multi-source structured and unstructured data (code repositories, ticket systems, event logs, APIs, and relational/non-relational stores).

• Security & Multi-Tenancy: Deep instincts regarding tenant isolation, granular authorization controls, data leakage prevention, and provenance tracking.

• Startup Mindset: Ability to execute autonomously in fast-paced environments, balancing high-level architectural judgment with rapid implementation.