Objective 

We are looking for a Staff AI Engineer to join our AI Products Chapter and help us build the next generation of AI-driven experiences within Spin, part of a multi-business ecosystem. We are not looking for someone to build prototypes or proofs of concept. We are looking for a technical leader with a strong software engineering foundation who has shipped AI agents, copilots, or agentic systems to production with real users, real traffic, and real operational accountability. As a Staff-level engineer, you will work alongside Product Managers, Designers, Data Scientists, Researchers, and squads from different tribes to define how agentic systems are architected, deployed, evaluated, and operated at scale, setting the engineering standard for AI products across the entire organization.

What you’ll do 

• Design and build the engineering architecture behind AI agents and copilots: tool use, orchestration, retrieval, memory, and multi-step reasoning. 

• Take agentic systems from prototype to production: deployment, observability, latency, cost, error handling, and graceful degradation when the model fails. 

• Build and maintain evaluation (evals) pipelines, guardrails, and monitoring to catch regressions and quality drift before they reach users. 

• Own the reliability of agentic systems in production: on-call readiness, incident response, and root-cause fixes — not just handoff to another team. 

• Collaborate with Product Managers, Designers, Data Scientists, and business teams from early discovery through launch and iteration. 

• Define and evangelize engineering standards, patterns, and best practices for agentic and GenAI-based systems across squads and tribes. 

• Drive engineering initiatives end-to-end with autonomy: scope the problem, align stakeholders, sequence the work, and see it through to production — without depending on a dedicated Technical Program Manager. 

• Make build-vs-buy and architecture trade-off calls (framework, model provider, retrieval strategy, orchestration pattern) based on the problem, not on tool familiarity. 

• Mentor engineers across the chapter on agent engineering practices and raise the technical bar org-wide. 

What we’re looking for 

• Seniority: Extensive software engineering experience, with a proven track record of leading complex, high-impact engineering initiatives (IC5/Staff level equivalent). 
• Evidence of production, not proofs of concept: you have shipped and operated an AI agent, copilot, or agentic system serving real users, and can speak concretely about what broke, how you found out, and how you fixed it. 
• A strong software engineering foundation — you write, review, and own production code yourself. What matters is that you build and operate systems in production; your professional background (software engineer, ML engineer, ex-Data Scientist, etc.) matters less than that evidence. 
• Systems thinking: you can reason about an agent as a distributed system with failure modes, not just a model call. 
• Judgment on trade-offs particular to agentic systems: latency vs. quality, autonomy vs. control, cost vs. accuracy. 
• Ability to drive cross-functional initiatives with autonomy, aligning Product, Design, and business stakeholders without needing a dedicated project manager. 
• Experience working in agile, collaborative, multidisciplinary environments. 
• Constant curiosity about new tools, architectures, and ways of building with AI. 

We are very excited if you also... 

• Have hands-on experience with agent frameworks/orchestrators (e.g., LangGraph, LangChain, or equivalent), LLM provider APIs (Claude, OpenAI, Gemini), vector databases, and eval frameworks. 

• Have designed or contributed to evaluation and guardrail systems for LLM-based products. 

• Have worked with financial products, operations, support, growth, loyalty, or digital ecosystems. 

• Have led a technical initiative end-to-end without a dedicated PM/TechPM — scoping, sequencing, and shipping it yourself. 

• Are interested in agent design, human-in-the-loop systems, AI trust, explainability, and responsible AI. 

• Enjoy working with PMs, Designers, Data Scientists, and business teams from early discovery stages. 

• Are excited about building new things, iterating fast, and learning from problems that don’t have an obvious answer yet.

What will you find? 

• A company building AI-First capabilities at scale. 

• An AI Products Chapter focused on creating agents, copilots, and intelligent experiences for multiple tribes and squads. 

• Real, high-impact challenges impacting clients, businesses, operations, and the ecosystem. 

• Space to experiment, propose, and build new interaction patterns. 

• Multidisciplinary teams with a focus on product, data, technology, and user experience. 

• The opportunity to design experiences that will become the new digital interaction standard within the company. 

If you are excited about engineering the future of interaction between humans, AI, and digital products from a Staff/IC5 leadership perspective, we want to meet you 🚀