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Principal Engineer
Remote USA
10+ years software engineering with recent hands-on coding
Experience operating at Principal/Lead/ Distinguished Engineer position (or Head of Engineering or Engineering Lead still shipping code)
Production GenAI ownership (not prototypes): e.g., RAG, eval frameworks, inference services, safety/guardrails, tracing/observability.
Python expert; practical TypeScript/React/Node to contribute and guide full-stack work.
Demonstrated facilitative leadership: improved multi-team architecture/decisions; partnered with senior business leaders on product direction.
Strong cloud/platform chops (AWS/GCP/Azure), containers/K8s, CI/CD, telemetry, scalable data pipelines.
Nice to have:
Hands-on with RAG evals and infra: Vector databases (Pinecone, Weaviate, Milvus, Qdrant), evaluation frameworks—especially ragas—OpenTelemetry, and model gateways.
Performance & cost optimization of inference (batching, caching, KV, quantization).
Blockchain/tamper-evidence concepts—useful but not required.
Enable GenAI production-readiness (platform, not model R&D): Partner with product squads to take GenAI features from tooling setup through release and iteration—owning the standards, pipelines, and SLOs that make them reliable
Oversee the product’s technical solution end-to-end: translate customer requirements into clear architecture and shipped features, lead design reviews and trade-offs, and drive iterative delivery of our GenAI product.
Review & recommend AI best practices: Evaluate GenAI designs and implementations; explain how/why they work and recommend changes to improve latency, quality, cost, and safety.
Drive tooling & pipeline decisions: Run hands-on evaluations/POCs and make final calls on data pipelines, eval frameworks, workflow/orchestration tools, guardrails/safety, model/service integrations, and release mechanisms.
Define how AI features ship to customers: Deliver and maintain a practical playbook for AI releases—readiness criteria, eval gates, safety guardrails, rollout/rollback, and measurement—so customers get predictable quality.
Demonstrate business impact: Ensure solutions are production-used and mission-critical; define & track KPIs/OKRs (adoption, accuracy, p95/p99, cost per request, safety incidents).
Partner with leadership on vision: Shape the technical vision for engineer-focused AI tooling; translate ambiguous user problems into shippable, staged work with clear success criteria.
Influence product direction: Provide trade-off narratives grounded in customer impact, security, and long-term maintainability; propose sequencing and de-risking plans.
Design, build, and own core components: Eval pipelines, tracing/observability, dataset/prompt/version workflows, guardrails/safety, and inference orchestration—own these as first-class platform capabilities.
Lead high-impact contributions across the stack: Act as a force multiplier—set patterns, pair, review, and land critical changes in Python services, Node/TypeScript APIs, and React UI to unblock teams and raise the bar. Not expected to own full end-to-end projects solo.
Raise the bar on architecture and engineering practice: Write clear architectural documentation, lead design reviews, set lightweight engineering principles, and build mechanisms that help teams make good decisions without central bottlenecks.
Develop Key Metrics: Establish and operate metrics for quality, latency, cost, and safety; drive continuous improvement loops tied to SLOs and error budgets.
Mentor, give actionable feedback, and grow careers: Coach senior and junior engineers, provide regular, constructive feedback, co-create growth plans, define clear levelling signals, support hiring loops, and scale bar-raising practices across teams.
Operate with excellence: Set SLAs/SLOs, own on-call/incident posture for GenAI services, and ensure security, compliance, and cost efficiency at scale.
Advise senior leaders through clear technical documents: Write persuasive technical proposals and briefs that align multi-team initiatives and inform investment choices and risk/mitigation for GenAI programs.
Fully remote, work from home environment
Flexible working hours
Paid Time-Off
Periodic in-person offsites globally (travel permitting)
Long-term incentive programs
Continued education support
Advancement opportunity
hackajob is partnering with Prove AI to fill this position. Create a profile to be automatically considered for this role—and others that match your experience.