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Staff AI Engineer

Stafffull-timeRemote (Global)$230k–$320k + equity
As a Staff AI Engineer at Overnox, you are the most senior individual contributor on our AI engineering practice — the person clients' CTOs want in the room when they're betting a product line on generative AI. You'll architect and ship production-grade LLM systems end to end: multi-agent workflows, retrieval-augmented generation over messy enterprise data, tool-use and MCP integrations, and the evaluation harnesses that keep them honest. This is not a research role and it is not a prototype-and-hand-off role; you own systems from whiteboard through to the 3am page, across a portfolio of concurrent client engagements. You'll set the technical direction for how we build AI at Overnox — reference architectures, model-selection frameworks, prompt and context engineering standards, guardrails, and cost/latency budgets — and you'll raise the bar for every engineer around you through design reviews, pairing, and mentorship. Because our clients range from Series-A startups to regulated enterprises, you'll routinely make pragmatic tradeoffs between frontier capability and the security, compliance, and reliability constraints those environments demand. This role matters because AI systems fail in ways traditional software does not — silently, expensively, and unpredictably. Overnox wins repeat business by shipping AI that is measurable, secure, and durable in production, and you are the engineer most responsible for making that true.

What you'll do

  • Architect and ship production LLM applications end to end: agentic workflows, multi-agent orchestration, RAG pipelines, tool/function calling, and MCP-based integrations against real enterprise data and systems
  • Design and own evaluation systems — offline eval suites, LLM-as-judge pipelines, golden datasets, and online A/B and regression testing — so model and prompt changes ship on evidence, not vibes
  • Establish reference architectures, context-engineering standards, guardrail patterns (prompt-injection defense, output validation, PII handling), and cost/latency budgets adopted across all client work
  • Own the full model lifecycle in production: retrieval quality, chunking and embedding strategy, fine-tuning/distillation where warranted, caching, streaming, and fallback/routing across providers (OpenAI, Anthropic, open-weight models)
  • Lead technical discovery and architecture reviews directly with client CTOs and engineering leaders, translating ambiguous business goals into concrete, shippable AI systems
  • Instrument systems for observability (traces, token/cost metrics, quality dashboards) and drive incident response and postmortems for AI-specific failure modes (hallucination, drift, latency regressions)
  • Mentor senior and mid-level engineers, run design reviews, and codify hard-won patterns into internal frameworks and playbooks that scale our practice

What we're looking for

  • 8+ years building production software, with 3+ years shipping LLM/GenAI systems that real users depend on (not demos or notebooks)
  • Deep, hands-on expertise with the modern LLM stack: at least one major provider API (OpenAI/Anthropic), an orchestration framework (LangChain/LlamaIndex or equivalent, or hand-rolled), vector stores (pgvector, Pinecone, Weaviate), and MCP or comparable tool-integration patterns
  • Proven experience designing RAG and agentic systems, including retrieval evaluation, chunking/embedding strategy, and handling long-context and multi-step reasoning reliably
  • Rigorous approach to evaluation: you've built eval harnesses, defined quality metrics, and can quantify whether a change made a system better or worse
  • Expert-level Python (and/or TypeScript) and strong systems fundamentals — APIs, data pipelines, concurrency, latency and cost optimization at scale
  • Experience deploying and operating AI workloads on AWS, GCP, or Azure, including containerized services and CI/CD
  • Demonstrated technical leadership: setting standards, mentoring engineers, and driving architecture across teams or client engagements
  • Excellent written and verbal communication — you can earn the trust of a skeptical enterprise CTO in a single design session

Nice to have

  • Experience with model fine-tuning, LoRA/PEFT, distillation, or self-hosting open-weight models (Llama, Mistral, Qwen) with vLLM/TGI
  • Hands-on work with AI security and safety: prompt-injection red-teaming, jailbreak defense, or LLM security reviews
  • Familiarity with GPU infrastructure, inference optimization, and serving cost economics at scale
  • Prior consulting, agency, or client-facing delivery experience across multiple concurrent projects
  • Open-source contributions, published writing, or conference talks in the AI engineering space

About Overnox

Overnox is an AI engineering and infrastructure consultancy. We help startups and enterprises securely adopt AI, automate operations, and scale cloud infrastructure with enterprise-grade engineering — building, securing, and operating production AI systems as one accountable senior team. Security-first, product-minded, no outsourcing.

What we offer

  • Fully remote — work from anywhere, with a few hours of overlap for collaboration
  • Competitive base plus meaningful equity in the company you're helping build
  • Senior-only team — real peers, no juniors to babysit, no offshore handoffs
  • Top-tier hardware and a generous learning, certification, and conference budget
  • Direct ownership of outcomes and a genuine say in how we build and operate
  • Region-appropriate health, time-off, and wellbeing support

Compensation

The listed range ($230k–$320k + equity) is a good-faith estimate. Final compensation is based on your experience, level, and location, and includes meaningful equity. We benchmark pay against the market and review it regularly.

Equal opportunity & accommodations

Overnox is an equal opportunity employer. We celebrate diversity and are committed to an inclusive environment for everyone. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable law.

If you need a reasonable accommodation at any point in the application or interview process, email hello@overnox.com and we'll work with you.

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