Staff AI Engineer - AI Infrastructure & Agentic Platform is a AI Infrastructure Engineer role (full-time). with ShiftKey. in REMOTE, WARSAW, PL. Compensation shown: $237K–$256K (est.). Imported listing (source: feeny.ai). Apply on the employer's site (feeny.ai).
Imported listing (source: feeny.ai) · Apply on feeny.ai
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Imported job description
Sourced from feeny.ai
ShiftKey is building an AI-native healthcare workforce marketplace and seeks a Staff AI Engineer to own its AI infrastructure layer. You will architect and operate agentic infrastructure on AWS, evolve the retrieval and knowledge platform, and define the AI platform API surface. This role offers high autonomy and organization-wide influence in a regulated (HIPAA) environment.
Responsibilities
Evolve the AI knowledge platform, including retrieval, indexing, and synthesis layers (semantic RAG, re-ranking, HyDE) into an organization-wide platform.
Architect and operate agentic infrastructure on AWS, building multi-step, tool-using AI systems with cost guardrails and observability.
Design and build graph-based, relationship-aware retrieval across organizational data sources for multi-hop queries.
Partner with product engineering to define the AI platform API surface and developer-ready abstractions.
Build reference agent implementations for operational-incident triage, customer support, and future use cases.
Own the AI infrastructure cost model, monitoring compute, model, and storage spend and proposing guardrails.
Requirements
7+ years of professional software engineering experience, with at least 2 years building and operating production AI/LLM application systems.
ShiftKey operates a digital healthcare workforce marketplace connecting licensed independent professionals with healthcare facilities. Its technology supports shift discovery and booking, credential visibility, scheduling, payments, workforce analytics, and direct facility-to-professional engagement.
Retrieval engineering experience beyond basics: 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, including tool use, iteration control, cost governance, and model routing trade-offs.
Production-grade software engineering fluency in Go, Python, or TypeScript, with 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 identity/secrets model and model access governance.
Hands-on Terraform experience, able to author and provision new infrastructure independently.
Familiarity with production observability for AI systems: metrics, structured logging for model spend and latency, and evaluation harnesses.
Understanding of HIPAA-style data-handling requirements in a regulated SaaS environment.