Staff/Senior AI Engineer, AI for Code

Peloton

ABOUT THE ROLE  Peloton is looking to transform our enterprise tech strategy with AI adoption. We are looking for a Staff Enterprise AI Engineer to serve as the "Founding Engineer" of our Enterprise AI Platform.This is not a traditional Data Science role. You will not spend your days tweaking hyperparameters. Instead, you will architect and build the Operating System that enables our Product, People, and Operations teams to deploy AI Agents safely and at scale. You will act as a "Player/Coach," laying the technical foundation (Infrastructure, Security, Orchestration) while guiding a team of engineers to execute the vision. You will build the "Golden Path" that helps everyone at Peloton to leverage AI securely for the competitive advantage of Peloton. YOUR DAILY IMPACT AT PELOTON * Architect the "Intelligence & Integration" Layers * Design and build a scalable Agentic Orchestration Platform (using LangChain, LangGraph, or custom frameworks) that allows internal developers to spin up autonomous agents. * Implement the "Integration Layer" ensuring all AI agents connect to internal APIs (Workday, Snowflake, SAP) via secure, standardized protocols (Model Context Protocol - MCP). * Solve the "State Problem" for AI, architecting memory stores (Vector DBs like Pinecone/Weaviate) that persist context across user sessions. * Enforce "Security by Design" * Partner with Security leadership to implement Identity Propagation. Ensure agents execute tasks using the user’s specific OAuth scopes, preventing privilege escalation. * Build "Data Clean Rooms" and PII masking pipelines to ensure sensitive member or employee data is never leaked to model providers. * Deploy EvalOps pipelines to automatically test models for hallucination and regression before they hit production * Define the Engineering Standards * Define the "Guide vs. Control" standards for the organization. Create the templates and libraries that allow analysts to "Vibe Code" (low-code/assisted coding) safely within our guardrails. * Perform rigorous code reviews for partner teams and vendors, ensuring high performance, low latency (<200ms), and cost efficiency * Capital-Efficient Scale * Optimization of inference costs by implementing Semantic Caching and routing logic (e.g., routing simple queries to smaller/cheaper models). * Leverage Kubernetes (EKS) to manage ephemeral compute resources for AI workloads. * A Systems Builder: You view AI as a distributed systems problem. You care about latency, rate limiting, and eventual consistency just as much as you care about prompt engineering. * A Pragmatist: You don't build "Science Projects." You build tools that solve specific business frictions (e.g., automating Content PR approvals or speeding up Supply Chain queries). * A Force Multiplier: You enjoy mentoring senior engineers and demystifying AI for non-technical stakeholders (from HR to Product). YOU BRING TO PELOTON * Experience: 10+ years of software engineering experience, with 3+ years specifically focused on MLOps, LLM Orchestration, or Large Scale Distributed Systems. * The Stack: Deep fluency in Python (production grade) and Go (preferred for platform services). * AI Engineering: Proven experience deploying RAG (Retrieval Augmented Generation) and Agentic Workflows in production. Experience with frameworks like LangChain, Semantic Kernel, or similar. * Platform Engineering: Strong background in Kubernetes (EKS), Docker, and Infrastructure-as-Code (Terraform). * Security: Solid understanding of OAuth 2.0 (OBO flow), RBAC, and zero-trust networking principles. * Communication: Ability to explain complex technical trade-offs (e.g., "Latency vs. Accuracy") to executive stakeholders. BONUS  * Experience implementing Model Context Protocol (MCP) or similar standardized tool interfaces. * Background in FinOps (managing GPU/Cloud spend). * Experience navigating highly regulated environments (HIPAA, SOX, etc.). #LI-DD1 #LI-Hybrid   The base salary range represents the low and high end of the anticipated salary range for this position based at our New York City headquarters. The actual base salary offered for this position will depend on numerous factors including, without limitation, experience and business objectives and if the location for the job changes. Our base salary is just one component of Peloton’s competitive total rewards strategy that also includes annual equity awards and an Employee Stock Purchase Plan as well as other region-specific health and welfare benefits. As an organization, one of our top priorities is to maintain the health and wellbeing for our employees and their family. To achieve this goal, we offer robust and comprehensive benefits including: * Medical, dental and vision insurance  * Generous paid time off policy * Short-term and long-term disability * Access to mental health services * 401k, tuition reimbursement and student loan paydown plans * Employee Stock Purchase Plan * Fertility and adoption support and up to 18 weeks of paid parental leave  * Child care and family care discounts * Free access to Peloton Digital App and apparel and product discounts * Commuter benefits and Citi Bike Discount * Pet insurance and so much more! Base Salary Range $193,550—$237,750 USD   ABOUT PELOTON: Peloton (NASDAQ: PTON) provides Members with expert instruction, and world class content to create impactful and entertaining workout experiences for anyone, anywhere and at any stage in their fitness journey. At home, outdoors, traveling, or at the gym, Peloton brings together innovative hardware, distinctive software, and exclusive content. Founded in 2012 and headquartered in New York City, Peloton has millions of Members across the US, UK, Canada, Germany, Australia, and Austria. For more information, visit www.onepeloton.com. Peloton is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. Equal employment opportunity has been, and will continue to be, a fundamental principle at Peloton, where all team members, applicants, and other covered persons are considered on the basis of their personal capabilities and qualifications without discrimination because of race, color, religion, sex, age, national origin, disability, pregnancy, genetic information, military or veteran status, sexual orientation, gender identity or expression, marital and civil partnership/union status, alienage or citizenship status, creed, genetic predisposition or carrier status, unemployment status, familial status, domestic violence, sexual violence or stalking victim status, caregiver status, or any other protected characteristic as established by applicable law. This policy of equal employment opportunity applies to all practices and procedures relating to recruitment and hiring, compensation, benefits, termination, and all other terms and conditions of employment.  If you would like to request any accommodations from application through to interview, please email: applicantaccommodations@onepeloton.com. At Peloton, we embrace technology, including AI, to enhance productivity and accelerate innovation in the work we do for our members. However, in our hiring process, our priority remains in getting to know you and your unique qualifications. To ensure a fair and equitable process, we do not permit the use of AI tools during any stage of the application and interview process. In considering you as an applicant, we want to understand your skills, experiences, and motivations without mediation through an AI system. We also want to directly assess your communication skills without the use of an AI tool.  Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance and the San Francisco Fair Chance Ordinance, as applicable to applicants applying for positions in these jurisdictions. Please be aware that fictitious job openings, consulting engagements, solicitations, or employment offers may be circulated on the Internet in an attempt to obtain privileged information, or to induce you to pay a fee for services related to recruitment or training. Peloton does NOT charge any application, processing, or training fee at any stage of the recruitment or hiring process. All genuine job openings will be posted here on our careers page and all communications from the Peloton recruiting team and/or hiring managers will be from an @onepeloton.com email address.  If you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Peloton, please email applicantaccommodations@onepeloton.com before taking any further action in relation to the correspondence. Peloton does not accept unsolicited agency resumes. Agencies should not forward resumes to our jobs alias, Peloton employees or any other organization location. Peloton is not responsible for any agency fees related to unsolicited resumes.

Joko

At Joko, we help consumers shop smarter. Our mission is to revolutionize shopping, empowering people to find what they need, make informed decisions, and save money. Founded in Paris, Joko is a tech company and certified B Corp with over 105 talents across Paris, Barcelona, and New York (and beyond). More than 6 million users already save money every day at 10,000+ merchants with Joko. From cashback and automatic coupons to price alerts and carbon tracking, we keep expanding our products to make shopping smarter. We’re now building an AI-powered shopping assistant to help users find the best products by price, quality, and environmental impact. Having reached profitability in our core market, we’re now scaling globally, with a strong focus on the US. It’s still day 1, come build the future of shopping with us! This position is remote-friendly (France and Spain). 📱 OUR ENGINEERING TEAM Our Engineering team excels at solving cutting-edge technical challenges with elegant solutions. With a strong focus on product innovation and design, they are shaping the future of the online shopping experience. Their ambition is to have a positive impact on the everyday lives of hundreds of millions of users around the world. Software Engineers in the Engineering team work hand-in-hand with the Product team, from exploration, design, and roadmap prioritization to implementation, and deployment in production. At Joko, we have firsthand experience that teams with engineers who possess a diverse range of skills, and where engineering and product collaborate closely, are able to deliver a truly delightful and innovative user experience. The Engineering team is currently growing fast to continuously innovate on all parts of our product and tech stack and to empower the revolution of the way people shop online. 🎯 WHAT YOU WILL DO As an AI Software Engineer, you will own the development and continuous improvement of Joko AI — our AI shopping agent that seamlessly guides users to the ideal product whatever their intent — helping them save significant time by taking into account all relevant considerations (price, quality, reviews, environmental impact), across every product sold by any e-commerce merchant in the world. Working closely with Alex, our CTO, and alongside a small team of world-class engineers, sitting at the intersection of applied research and production. * Agent architecture: You will own the architecture of our agentic system — ensuring it constantly evolves, incorporates the latest advancements in the field, challenges existing assumptions, tests bold ideas, and pushes the boundaries of what our AI assistant can do. * Evaluation & monitoring: You will design and run robust evaluation frameworks to measure Joko AI's performance, catch regressions, and build confidence before shipping to production. * Capabilities & integrations: You will constantly expand the set of tools and capabilities that Joko AI can leverage — web search, vector search, ever-smarter catalog lookups — making the agent more resourceful, faster, and more reliable at scale. * Catalog & data at scale: Great recommendations start with great data. Joko AI is powered by a product catalog of hundreds of millions of entries, continuously updated. You will tackle the massive challenges of ingesting, standardizing, and enriching this data at scale, where AI itself plays a key role. * Personalization: Joko has access to uniquely rich data — bank transactions and browsing behavior through the browser extensions — giving us unparalleled insight into user preferences and shopping patterns. You will leverage these signals to deeply understand user intent and build a truly personalized experience — making Joko AI feel like it genuinely knows what you're looking for. * Experimentation & prototyping: You will constantly push Joko AI forward by identifying new challenges and building new features for the agent. You will prototype fast, put early versions in users' hands, and iterate based on real feedback * Staying ahead: You will stay on top of the latest models, agentic frameworks, and research papers, and translate what's emerging into concrete improvements for Joko AI. * Fine-tuning & optimization: You will fine-tune models to improve quality, reduce latency, and cut costs — always with a production-grade mindset. * Runtime & scalability: You will iterate on the backbone and infrastructure Joko AI runs on, ensuring it handles hundreds of thousands of daily users with zero downtime and minimal latency. * Product collaboration: We are inventing an entirely new shopping experience with Joko AI — and much of what the ideal UX looks like is still to be defined. You will work hand-in-hand with the Product team, exploring bold design directions, imagining what the future of AI-assisted shopping can be, and turning that vision into reality from early concept to full rollout. 👀 WHO WE'RE LOOKING FOR * Experience: You have 5+ years of software engineering experience, including time building and shipping production systems. You've operated at a senior or staff level and you're used to owning ambitious projects from design to production. * Track record: You've ideally built production AI systems that real users rely on, and you care deeply about code quality, separation of concerns, and testing. * Technical skills: You are deeply familiar with agentic frameworks (LangChain, LangGraph, or equivalents), LLM observability tools (LangFuse or equivalents), LLM APIs, and evaluation tooling for AI systems. An AI/ML background or degree is a strong plus, but not a blocker. * Builder's mindset: You love building from scratch. You are not precious about your ideas — you ship, test, learn, and iterate fast. * Full-stack spirit: You are comfortable going from AI logic to infrastructure to frontend prototyping when needed. You don't stop at your lane. * Fast learner: The AI landscape moves fast. You thrive in it. You follow the research, experiment with new models and tools, and you are always slightly ahead of the curve. * Problem solver: You approach hard technical problems methodically. Latency, cost, hallucinations, long-term memory — you know these challenges and you enjoy tackling them. * Team player: You work closely with Product, iterate with users, and communicate clearly about what's working and what isn't. * Drive & ownership: You take full ownership of your scope. You don't wait to be asked — you spot issues, propose solutions, and ship. * Language: You are fluent in English (written and spoken). * Mindset: You have an entrepreneurial mindset, you like challenges, you welcome feedback and you love constantly learning and getting better. 💎 OUR PERKS (Some of the benefits listed below are available to full-time positions only) At Joko, we believe that flexibility and trust are essential. Our work environment reflects this through: * Flexible remote : If you live in Paris, you can choose to work from our office or from home with no constraints. If you live elsewhere, we can provide access to a coworking space and a coworking budget. * Work from anywhere : Want to spend a month in Italy while working? You can work from most countries in the world for up to 3 months per year. On top of that, we offer plenty of perks: * 💸 Top-market compensation * 📈 Equity for everyone with the chance to own a piece of what you build * 🤖 Half-day each week dedicated to leveling up with AI by exploring new tools, iterating hard, and sharpening your skills * 🌴 Yearly offsite in amazing locations and budget for team-building events & monthly in-person gatherings * 💪 Contribution to your ClassPass subscription * 🍼 8-week leave paid 100% for the second parent * …and much more, check the full list here! 🤝 OUR HIRING PROCESS 1. Intro call: Quick screening with the Hiring Manager or the Talent team. 2. Step 1 – Team interview (45 min): Conversation with two Joko team members (could include the Hiring Manager, people from the team you’d join, or colleagues from other teams). 3. Step 2 – Role-specific assessments * For non-engineering roles: A take-home case study followed by a 45-min interview. We assess both your output and how you think in real time. The exercise will be relevant to your role (e.g. analysis, strategy, or process design). * For engineering roles: A 90-min live technical interview on CoderPad covering code understanding, review, system design, and product thinking (with AI serving as a collaboration tool). 4. Step 3 – Leadership interview (45 min): Conversation with a SteerCo member and a Founder. 5. References: Up to 3 calls with former colleagues or managers. ☕ You may also be invited for coffee with team members to get a feel for our culture.

Snowflake

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. ABOUT THE ROLE We are an AI-first analytics team. We don't use AI to augment traditional BI workflows — we've replaced them. The Finance Analytics team builds the intelligence layer that Strategic Finance runs on: AI agents that encode repeatable finance processes, Streamlit apps that surface real-time insight, semantic models that let any analyst query complex data in plain English, and workflow automations that collapse hours of manual work into a single prompt. Our primary development environment is CoCo (Cortex Code), Snowflake's AI coding assistant, and SnowWork, the AI IDE we ship work in. Every deliverable on this team is built AI-first: you design the workflow, you write the prompt, you validate the output. If you are still building dashboards by hand, refreshing Excel files manually, or treating AI as a spell-checker for your code — this role will ask you to operate differently. This is a high-breadth seat. One week you're building a new AI agent for quarterly revenue analysis; the next you're designing a sensitivity analysis tool for an earnings war room. You are equally comfortable in an AI-IDE, a Python file, and a stakeholder summary for a senior finance leader. WHAT YOU'LL WORK ON AI AGENT AND WORKFLOW DEVELOPMENT (PRIMARY FOCUS) * Design and build skills and agentic experiences that encode repeatable finance workflows — revenue analysis, cost monitoring, earnings prep, headcount tracking — into reusable, invokable tools using CoCo and CoWork * Write and iterate on prompt & skill structures (YAML + Markdown skill files) based on output quality and stakeholder feedback * Build skills that allows non-technical finance analysts to produce analyst-quality output in a single prompt * Evaluate model outputs rigorously — you are the quality gate before anything reaches a finance stakeholder FINANCE ANALYTICS * Build and maintain quarterly and weekly revenue summary pipelines * Support sensitivity analysis models for quarterly business reviews & revenue forecast scenarios * Produce ad-hoc analysis for Strategic Finance SEMANTIC LAYER & APPLICATION DEVELOPMENT * Own semantic layers end-to-end — model design, versioning strategy, verified query coverage, and accuracy iteration based on eval metrics; not just build models, but maintain the contract between the model and its consumers across each quarterly iteration * Develop and deploy production finance dashboards as Streamlit apps (locally and deployed to Snowflake) * Build customer-facing demo applications for Sales and Field teams * Apply reusable component patterns and shared utility libraries for consistent, polished UI EARNINGS AND REPORTING AUTOMATION * Participate in quarterly earnings cycle prep — scenario tooling, export automation, IR data requests * Build and maintain source-of-truth reporting exports (multi-tab Excel, formatted to spec) * Support ad-hoc disclosure and investor relations data needs during quarter-end HARD SKILLS REQUIRED MUST-HAVE AI-assisted development — You have used an LLM coding assistant (CoCo, Cursor, GitHub Copilot, Claude, or equivalent) as your primary development tool. You know how to write a prompt that produces production-ready output, how to steer a model that's heading in the wrong direction, and how to encode domain logic into a reusable, parameterized skill. You have a measurable, trackable record of daily AI usage. Prompt engineering and skill authoring — You can write a structured prompt (YAML + Markdown or equivalent) that routes correctly 95% of the time, handles edge cases gracefully, and encodes enough domain knowledge that the model behaves like a subject matter expert. You think in terms of context, instructions, examples, and output format — not just "the thing I typed before the code came out." Python — Modern, type-hinted, readable. You write Python-based applications, data pipelines, and reporting automation. You understand caching, session state, and how to structure a multi-page app cleanly. At the senior level: you've contributed to a shared library or package that others depend on, and you've designed agent orchestration systems — including parallel agent patterns with synthesis layers. SQL — CTEs, window functions, incremental pipeline patterns. You don't look up the syntax for a row-numbered deduplication. Data modeling fundamentals — You understand bronze, silver, and gold data models conceptually and contribute to the gold layers and how they translate to semantic layer. You know not just how to build a model, but how to version it, evaluate SQL generation accuracy, maintain a verified query library, and iterate based on real analyst feedback. A non-technical user should be able to query your model in plain English and get a correct answer. STRONG PLUS * Snowflake Cortex — Cortex Analyst, Cortex Agents, AI_SUMMARIZE, AI_EXTRACT, Dynamic Tables, semantic views * SnowWork / CoCo — Prior experience deploying agents, authoring skill files, or working within the Snowflake Intelligence ecosystem * Finance literacy — You can read a revenue waterfall, distinguish ARR from NRR, and explain what drives a QoQ change in product revenue * Reporting automation — openpyxl, multi-tab Excel exports formatted to spec, named ranges * dbt — Model authoring, ref() patterns, YAML tests in a cloud warehouse context * Semantic search / embeddings — Vector similarity, embedding-based retrieval, and how they power natural language analytics SOFT SKILLS REQUIRED TRANSLATES BETWEEN AI, DATA, AND FINANCE Your stakeholders are financial analysts and senior directors who think in Excel models and board decks. You write prompts and code, but your output needs to make sense to someone who has never opened a terminal. You are the translation layer between what the model can do and what finance actually needs. You communicate complex ideas simply, ensuring stakeholders understand, trust, and can act on what you build. You are the translation layer between what the model can do and what finance actually needs. You set the standard for how agents are built on this team. Junior analysts look to your skills and code as the reference implementation. You push back on shortcuts that create maintenance debt. You don't wait to be asked to improve shared infrastructure. THINKS IN WORKFLOWS, NOT TASKS You don't just answer a question — you build a tool that answers it forever. When asked to do something twice, you automate it. Your instinct is to encode work into a reusable agent, not to redo it manually each week. At the senior level, this extends to the team: when the team does something repeatedly, you build the shared infrastructure that makes everyone faster. WORKS FAST WITH HIGH ACCURACY The role runs on a weekly cadence tied to finance deliverables. You scope, build, and ship a working artifact in 1–2 days. Accuracy matters more than speed — but accuracy is not a reason to be perpetually slow. COMFORTABLE WITH AMBIGUITY The brief is often: "Can you build something like the earnings tool, but for sensitivity analysis?" You scope it, build a working prototype, and come back for feedback — not a list of clarifying questions. MINIMUM REQUIREMENTS * 3-5+ years of experience in analytics, data engineering, or a technical finance adjacent role * Has used an AI coding assistant as a primary development tool — daily usage, not occasional * Proficient in SQL — you can write a window function without looking it up * Has shipped multiple Python applications that end-users actually interacted with; at least one is actively maintained in production * Comfortable working in Git (PRs, branches, code review) * Familiar with fiscal year concepts and core revenue metrics (ARR, bookings, NRR) WHAT SUCCESS LOOKS LIKE AT 90 DAYS * You've taken ownership of the quarterly and weekly revenue analysis workflows — they run correctly on schedule without hand-holding * You've shipped at least one Streamlit app to production or a demo application to the Finance Workloads team * You've participated in at least one quarterly earnings cycle * You've contributed a module, skill, or shared component to the team's shared infrastructure — something other analysts use without you having to explain it WHY THIS ROLE IS UNUSUAL AT THIS LEVEL This seat asks you to do all of that and build the AI infrastructure that makes the entire Finance Analytics team faster. You are simultaneously a practitioner and a workflow engineer. If you are fluent with AI development tools, you can punch significantly above your level. At the senior level, you are not just building the infrastructure — you are deciding what it should be. That means making architectural calls that hold across quarters, not just shipping the next feature. Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com