Staff AI Engineer

Role overview A digital experience platform organization is hiring a Staff AI Engineer to join its Data & Intelligence function. The role focuses on building the retrieval, knowledge graph, and inference layers that turn more than a decade of operational, product, and customer data into actionable signals, and on shipping the agentic and deterministic systems that act on those signals. It is a senior, hands-on individual contributor position spanning observability, the core data platform, and insights, where most time is spent designing and shipping production code rather than managing.

Responsibilities

- Write and ship production AI code daily as an active engineering contributor, lifting team capability through the quality of the work itself. - Lead retrieval work that makes customer context queryable at speed, including semantic search, indexing, and knowledge graph approaches, with an early priority of resolving a full customer context in a single request. - Build the inference and signal layer: models and processors that read from an Iceberg-based lakehouse, write scored inference back, and expose signals through contracts other teams can build against. - Turn detected conditions such as churn risk, entitlement mismatch, or expansion opportunities into workflows that act, with human review where appropriate. - Choose the right tool per workload, balancing large models, small fine-tuned models, and deterministic code, and manage inference cost as a first-class concern. - Own evaluation and observability for AI systems so a signal is shown to be sound before anyone acts on it.

Requirements

- Senior IC track record of shipping high-quality code and system designs, with mentoring that happens organically through the work rather than through meetings. - Experience with retrieval systems, semantic search, indexing, and knowledge graph approaches over large data platforms. - Familiarity with lakehouse architectures (Iceberg or similar), inference pipelines, and writing scored outputs back to data systems. - Strong communication skills, able to present AI system design to engineers and executive stakeholders alike. - Comfort working across shifting priorities and unfamiliar problem spaces, with most output being shared capability consumed by multiple teams. - AI-native working style: treats AI as an extension of the workflow, fluent with AI-assisted coding tools, and comfortable connecting agents to real systems.

Nice to have

- Prior experience standing up shared data or ML capability that other teams built on top of. - Small and fine-tuned model work, including distilling task-specific models to replace general-model calls at scale. - Observability data fluency, including OpenTelemetry and making high-volume logs, metrics, and traces queryable. - Data governance instincts around access control, lineage, and data residency, treated as part of the design. - Familiarity with enterprise SaaS or content management systems and agentic development workflows such as MCP.

Benefits and work setup

- Pay range: $150,000–$200,000 USD. - Core benefits include competitive healthcare coverage, wellness programs, flexible time off, parental leave, and recognition programs.