Tech Lead Manager

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 The Cortex Apps team is building the future of AI for enterprise data. See our flagship product in action: Talk To Your Data: Snowflake Intelligence Demo. Your work will directly impact how businesses understand and leverage their data. You'll own the full AI engineering lifecycle: design, prompt/tool engineering, evals, deployment, measurement, and optimization. You'll work with a small, high-powered modeling and infrastructure team. WHAT YOU WILL DO IN THIS ROLE: * Own features end-to-end for Snowflake Cortex products. Build agentic workflows, NL-to-SQL on semantic layers, search. * Build enterprise-grade context engineering: function calling, tool schemas, guardrails, semantic model-aware prompting for SQL, and verification/repair * Design evals and hillclimb : create golden sets, create rubrics and metrics, analyze errors, run experiments to hill climb on the metrics. * Partner with product and infra: translate customer problems into products and experiments. Collaborate with infrastructure teams to productionize improvements. * Lead a team of engineers towards building great products REQUIREMENTS: * Bachelor’s degree in Computer Science, Engineering, Statistics or a related field. Master’s or higher degree preferred but not a requirement. * 8+ years of experience shipping AI features in production. * Proficiency in programming languages such as Python, Go * Strong communication skills and ability to collaborate effectively in a team environment. * (Optional) Experience working with text2sql, data modeling, data analysis, retrieval systems, and semantic layers is a plus. ABOUT SNOWFLAKE Snowflake is the AI Data Cloud trusted by the world's most innovative companies. We're shipping production-ready AI applications at scale and want you to join us in building the future of how businesses interact with their data through our Cortex products: Snowflake intelligence, cortex agents, cortex analyst, cortex search. 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

ABOUT ANTHROPIC Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. ABOUT THE ROLE Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We're looking for an experienced tech lead to join our Evals Infrastructure team, building the systems that let us measure what our models can actually do. Evaluation is how we know whether a model is safe to ship — you'd own the infrastructure that makes those measurements fast, reliable, and trustworthy at scale. In this role you'll work at the intersection of inference, research and infrastructure engineering: managing the large scale distributed systems that orchestrate evals for our frontier models, building and scaling the harnesses researchers use to design and run evals, making results reproducible and interpretable, and ensuring eval signal is available where decisions get made. Your work directly shapes what we build and what we don't. Responsibilities * Lead the team building the distributed systems that schedule, orchestrate, and execute evals for our frontier model training * Own eval throughput and cost: compute allocation across suites, queueing against constrained accelerator pools, caching and reuse of eval work * Build and scale the harnesses researchers use to define, run, and iterate on evals * Make eval results trustworthy — determinism, reproducibility, and honest uncertainty quantification on reported metrics * Ensure eval signal reaches the dashboards and reviews where launch decisions actually get made * Contribute directly as an engineer while managing and growing the team, prioritizing its work, and coaching your reports You may be a good fit if you * Have led technical projects end-to-end on large-scale distributed systems, and have 1+ years managing engineers (or tech-lead-with-reports experience) * Are strong in Python and Rust * Have built high-throughput, fault-tolerant systems on cloud or on-prem accelerator fleets * Care about measurement quality, not just pipeline uptime — you'd notice if a metric moved for the wrong reason * Communicate well with researchers and can translate research needs into infrastructure * Are deeply interested in the transformative effects of advanced AI and committed to safe development Strong candidates may have * Worked on LLM inference or training infrastructure * Experience with eval or benchmarking systems, especially agentic evals requiring sandboxed execution * Working statistical literacy — variance, confidence intervals, sample-size sufficiency for noisy metrics * Experience with observability and regression detection over time-series metrics Sample Projects * Rebuilding the eval orchestration layer to cut wall-clock time on the pre-train eval suite * Designing compute allocation and scheduling so eval suites fit inside a fixed fraction of a production run's chip-hours * Adding rigorous uncertainty estimates to top-line dashboard metrics so checkpoint-to-checkpoint comparisons are actually decision-grade * Building sandboxed execution infrastructure for agentic evals The annual compensation range for this role is listed below.  For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000—$850,000 USD LOGISTICS Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers [http://anthropic.com/careers] directly for confirmed position openings. HOW WE'RE DIFFERENT We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. COME WORK WITH US! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy [https://www.anthropic.com/candidate-ai-guidance] for using AI in our application process.