Staff AI Engineer - AI Infrastructure & Agentic Platform

Evolving the AI knowledge platform - taking the retrieval, indexing, and synthesis layer (currently semantic RAG + re-ranking + HyDE) to an organization-wide platform serving both internal engineering tools and customer-facing capabilities.

Architecting and operating agentic infrastructure on AWS - multi-step, tool-using AI systems that plan, retrieve, and act on complex queries and operational events, with cost guardrails and observability built in from day one.

Designing and building graph-based, relationship-aware retrieval across the organization's data sources, enabling multi-hop queries and letting agents accumulate organizational knowledge over time. This is on our roadmap, not in production - you will define the approach.

Partnering with product engineering to define the AI platform API surface, translating infrastructure primitives into developer-ready abstractions.

Building reference agent implementations on the platform - operational-incident triage, customer support, and future agentic use cases - grounding each agent's reasoning in institutional knowledge.

Owning the AI infrastructure cost model: monitoring compute, model, and storage spend, flagging anomalies, and proposing guardrails to keep workloads within defined budgets.

7+ years of professional software engineering experience, with at least 2 years building and operating production AI/LLM application systems - not research, not prototyping, not demos.

Retrieval engineering beyond the basics. Our stack already includes re-ranking and HyDE; we need someone who has worked at or above that level: hybrid search, re-ranking, query transformation, context-window management, and evaluation of retrieval quality in production.

Working experience with agentic frameworks and multi-step reasoning loops - tool use, iteration control, cost governance, and model routing trade-offs.

Production-grade software engineering fluency (strict typing, testing, async/concurrency, modern toolchain) in Go, Python, or TypeScript, with the ability to ramp into another quickly.

Hands-on experience operating AI workloads on a managed cloud AI platform (AWS Bedrock or Azure AI Foundry), including the identity/secrets model and model access governance. Bedrock preferred given our AWS stack.

Hands-on Terraform experience - able to author and provision new infrastructure independently, not just modify existing modules.

Familiarity with production observability for AI systems: metrics, structured logging for model spend and latency, and evaluation harnesses to detect regressions.

Understanding of HIPAA-style data-handling requirements in a regulated SaaS environment. Prior healthcare experience is a plus, not a requirement.

ShiftKey is an equal opportunity employer and is committed to embracing diverse and individual perspectives shaping our culture and contributing to the solutions that transform the world. We actively work to create an inclusive environment for employees to thrive.

ShiftKey does not discriminate based on race, religion, color, sex, gender, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status, or any other basis covered by applicable law. All employment is decided based on qualifications, merit, and business needs. ShiftKey is committed to providing reasonable accommodation to applicants with a mental or physical disability, please contact: accommodations@shiftkey.com