Senior Forward Deployed Engineer -Spark

Senior Forward Deployed Engineer, Applied AI

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. Snowflake is about empowering enterprises to achieve their full potential – and people too. With a culture that's all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology – and careers – to the next level. Where Data Does More. Join the Snowflake team. At Snowflake, we are building a high-impact team to help the world's most innovative companies unlock the power of AI. As a Senior Forward Deployed Engineer, Applied AI on our Cortex AI team, you will be a hands-on technical leader and trusted partner to our most strategic customers. You will own the end-to-end delivery of enterprise AI programs, leading a team of 2–4 engineers while staying deeply technical yourself. You will set the technical direction for your customer engagements, mentor your team, and serve as the senior technical voice at the intersection of product, engineering, and customer success. IN THIS ROLE AT SNOWFLAKE, YOU WILL: Lead Customer Programs: Own the full lifecycle of complex, multi-engineer AI engagements – from scoping and architecture through deployment, monitoring, and handoff. Be accountable for delivery quality and customer outcomes for the projects you lead. Own AI Quality: Define what "good" means for each engagement. Translate ambiguous customer goals into measurable quality metrics, evaluation frameworks, and golden datasets – then run systematic eval loops to hill-climb on agent quality, catch regressions before customers do, and continuously raise the bar on accuracy, faithfulness, and safety. Set the standard for how the team measures and improves AI systems in production. Grow and Mentor Engineers: Provide day-to-day technical leadership and mentorship to a team of 2–6 Applied AI Engineers. Review designs and code, unblock teammates, and actively develop their skills and careers. Deliver with Velocity: Remain a hands-on contributor – designing, iterating, and shipping high-quality ML pipelines and agentic AI solutions alongside your team. Translate ambiguous business objectives into robust, scalable, and performant solutions. Productionize AI at Scale: Own the full implementation lifecycle for AI solutions, from prototype through deployment, monitoring, and optimization in secure, large-scale production environments. Build the safety guardrails, observability, and human-review workflows that keep AI applications reliable and trustworthy – and close the loop from production traces and user feedback back into your evals so quality compounds over time. Be a Strategic Technical Advisor: Serve as a senior technical advisor to customer data science and engineering leadership. Set the standard for how Snowflake AI is deployed and articulate complex technical concepts to both technical and executive stakeholders. Collaborate to Innovate: Work cross-functionally with Snowflake's Product and Engineering teams, bringing real-world patterns and feedback from the field to directly shape the future of Snowflake's AI platform. Drive Compounding Outcomes: Identify recurring deployment patterns and turn them into reusable assets – reference architectures, evaluation harnesses, and product feedback that scale Snowflake's impact across customers. Have the opportunity to travel: Spend at least 25% of your time onsite, working closely with Snowflake's most strategic customers. WE'RE LOOKING FOR CANDIDATES WHO HAVE: MINIMUM QUALIFICATIONS * Demonstrated experience leading technical projects or teams, including setting technical direction, reviewing others' work, and driving delivery to completion. * Proven experience building and productionizing applications using LLMs, especially with technologies like RAG and agentic workflows. * Hands-on experience defining quality metrics and evaluation frameworks for LLM or agent systems, and using evals to systematically improve quality over time. * Excellent problem-solving and communication skills, with an ability to articulate complex technical concepts to both technical and executive stakeholders. * Comfort with ambiguity and the ability to independently structure and execute on complex, open-ended problems. * 5+ years of professional software engineering experience. * Experience in a customer-facing technical role. * Willingness to travel. PREFERRED QUALIFICATIONS * Experience building eval sets from production traces and synthetic data, and running structured experimentation (A/B tests, ablations, offline evals) to compare prompts, models, or agent architectures. * Familiarity with eval and observability tooling (e.g., Braintrust, LangSmith, Arize, Weave, Promptfoo) or experience building custom eval harnesses. * Experience with failure-mode analysis on agent or RAG systems – categorizing errors (hallucination, retrieval miss, planning failure, tool misuse) and driving each down with targeted evals. * Hands-on experience with the MLOps lifecycle, including model deployment, monitoring, and evaluation in a cloud environment (AWS, Azure, or GCP). * Familiarity with core data science libraries and tools (e.g., pandas, numpy, Snowpark). * Startup experience or experience in a high-growth, fast-paced environment. Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee’s duty to keep customer information secure and confidential. 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

Senior Product Manager - Applied AI

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. The Snowflake Cortex team is on a mission to bring the transformative power of generative AI and machine learning to enterprise customers, seamlessly and securely within the Snowflake Data Cloud. We are seeking an entrepreneurial and customer-obsessed Product Manager to lead the product vision and execution for our AI Solutions and Services. In this role, you will own the end-to-end product lifecycle for some of our most exciting AI services. You will be responsible for understanding customer needs, defining the product roadmap, and working with a world-class engineering team to deliver innovative solutions that make it easy for any user to leverage AI. You will sit at the critical intersection of customers, our forward-deployed engineering team, core engineering, and GTM strategy, driving the future of AI within the Data Cloud. If you are obsessed with building products that are both powerful and simple, and thrive on turning ambiguity into impact, this is the role for you. AS A SENIOR APPLIED AI PRODUCT MANAGER AT SNOWFLAKE, YOU WILL: * Own the Product Vision & Roadmap: Define and articulate a clear, compelling strategy for large-scale AI solutions. You will architect and own the end-to-end product lifecycle, from deep discovery and detailed requirements to hands-on development, launch, and the analysis of metrics to ensure a successful impact. * Lead from the Front: Serve as the unequivocal cross-functional leader for a dedicated pod of world-class engineers, data scientists, and solution architects. You will drive execution, partner with design, marketing, and sales to bring products to market, and act as the evangelist for your product vision. * Be the Voice of the Customer: Act as the critical bridge between customer objectives and our technical capabilities. You will engage deeply with users and executives to gather insights, validate hypotheses, and ensure the solutions you build solve their most pressing, high-value problems. * Commercialize Innovation: Masterfully distill insights from bespoke customer solutions into a strategic vision for scalable, repeatable products. You will own the roadmap for turning successful 1-of-1 deployments into 1-to-many platform features. * Shape Business Strategy: Work shoulder-to-shoulder with leadership at both Snowflake and our customer organizations to define product strategy and execute on high-stakes business goals. OUR IDEAL SENIOR PRODUCT MANAGER WILL HAVE: * A Bachelor's degree in Computer Science, Engineering, or a related technical field; MBA or advanced degree is a plus. * 7+ years of experience in product management, with a proven track record of shipping successful enterprise software or cloud services. * Deep technical fluency to confidently lead architectural discussions with senior engineers and have hands-on experience with data science workflows and modern AI paradigms (e.g., LLMs, vector databases, agentic workflows). * Demonstrated ability to develop a product strategy and translate it into a concrete, actionable roadmap. * Strong customer empathy and experience working directly with enterprise customers to understand their needs and challenges. * Exceptional executive presence and communication skills. You can command a room of C-level stakeholders and inspire a team around a shared vision. * A "get it done" attitude with a passion for building exceptional products. BONUS POINTS (NICE TO HAVES): * Experience building and launching products for developers or data scientists. * Familiarity with the Snowflake platform and Data Cloud ecosystem. * Management consulting experience. * Experience operating in a high-growth, high-ambiguity environment where you were responsible for creating clarity and driving focus. * Experience in a role that directly supported a professional services or forward-deployed engineering team. Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential. 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

Corporate Counsel 2 - Product

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. Snowflake's Product Legal team is hiring a Corporate Counsel II to support Snowflake's AI Forward Deployed Engineering, AI Governance, Data Clean Rooms, and Native Apps product surfaces. We're looking for a thoughtful, business-minded lawyer who is energized by open-ended problems. You'll report to a Senior Corporate Counsel within Product Legal. RESPONSIBILITIES * Day-to-day product counseling for AI Governance, Data Clean Rooms, and Native Apps. Collaborate with PMs and engineers as features get scoped and built, diving deep on feature functionality, identifying what risks they introduce, and designing meaningful risk mitigations and compliance strategies. Advise on issues relating to IP, privacy, regulatory, contract architecture, and product policy, often at the same time. * Manage AI Forward Deployed Engineering engagements. Support commercial negotiations and drive cross-functional alignment with tax, accounting, finance, product, and engineering stakeholders. Comfort with novel commercial agreements matters here. * Draft and maintain customer-facing legal terms tied to new product offerings and launches. * Discover new best practices for product counseling in the AI era by reimagining how legal work can be done. REQUIREMENTS * Equivalent of 3+ years substantive post-bar legal practice, with substantive practice in one or more of the following: privacy / cybersecurity regulatory, tech transactions, AI/ML regulatory, IP (transactional or litigation), commercial litigation with technology clients, or hybrid commercial-regulatory practice. Your career arc should signal substantive curiosity and adaptability across areas — we care more about how you think and learn than about which practice group you sit in today. * Demonstrated comfort with technical product material — you should be able to read an architecture document and have a focused conversation with Engineering. * Strong judgment under ambiguity. * Clear written communication, especially translating legal positions into plain-English for sophisticated non-lawyer audiences. * Experimental mindset toward AI tooling: curiosity about emerging capabilities, willingness to test, and developed views on what works and what doesn't. AI tooling is part of how the team works day to day; that should sound like a feature of the role to you, not a hurdle. * Integrity, empathy, strategic thinking, and service orientation. * Active California bar OR active bar in another US jurisdiction with eligibility to register as in-house counsel in California. PREFERRED EXPERIENCE (one or more) * Custom enterprise deal experience, particularly technology transactions. * Active practice using AI tools (Cortex, Claude, ChatGPT, GitHub Copilot, or comparable) for legal work product. * Exposure to AI/ML product law: model licensing, data rights, AI Act and state AI laws, customer AI risk allocation. * Exposure to clean-room / multi-party data collaboration, marketplace, app distribution, or AI governance. * Substantive prior career before law school (e.g., teaching, military, government, healthcare, prior tech IC role, policy/advocacy, journalism). * Technical or quantitative academic background prior to law school. INTERVIEW PROCESS The complete interview process will include both remote and in-person interviews, as well as a structured in-office working session and reference checks. The working session will involve redlining a partnership integration agreement excerpt using AI tooling, defending the redline in a stakeholder simulation, walking through how the structure adapts when the partnership layers into a custom AI forward-deployed engineering engagement, and a brief feedback and reflection session. Working-session materials will be shared 48 hours in advance. Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential. 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