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Location: Hong Kong, Hong Kong SAR; Singapore, Singapore Staff/Senior Java Engineer, OKX Wallet (Web3) Who We Are OKX Wallet is OKX's self-custody wallet, built for users worldwide to securely and conveniently store, manage, and use their on-chain assets. The wallet backend operates in a multi-chain, multi-asset, high-concurrency environment shaped by on-chain state uncertainty and strict fund-security requirements — combining the complex-systems challenges of traditional internet backends with the transaction, signing, and on-chain interaction problems unique to blockchain. We're looking for a Senior Java Engineer with roughly 5–10 years of backend experience: someone with strong engineering fundamentals who can independently own core modules, exercise sound judgment on complex problems, and proactively coordinate across upstream and downstream teams to drive work to completion. What You'll Do Own core wallet backend modules. Build and continuously improve address management, asset synchronization, transaction construction, broadcasting, on-chain confirmation, gas estimation, nonce management, and transaction-state tracking. Understand each module's role in the full wallet flow, and keep stability, performance, and maintainability front of mind. For complex requirements, break the problem down before choosing an implementation rather than stacking code or reusing old designs. Build transaction and on-chain interaction scenarios. Work on transfers, token approvals, contract interactions, cross-chain, swaps, DApp connections, and signature-request handling. Understand a transaction's full lifecycle — from initiation through construction, signing, broadcasting, on-chain confirmation, and final state update — and diagnose issues like stuck transactions, duplicate submissions, state inconsistencies, and on-chain success that isn't reflected in the business system, using logs, on-chain data, and call traces. Support multi-chain and new-chain integration. We already support EVM, Tron, and Solana, and continuously onboard new public chains, Layer 2 networks, and asset standards. Contribute to technical research, integration design, and feature development, accounting for differences in address models, account systems, transaction structures, signing methods, fees, and confirmation mechanisms — as well as node stability, asset sync, exception compensation, monitoring, and security boundaries. Ensure stable operation. Contribute to day-to-day stability work — monitoring, alerting, rate limiting, graceful degradation, retries, compensation, data reconciliation, and troubleshooting. When incidents occur, help investigate, narrow scope, and fix root causes; for recurring issues, drive systemic fixes such as added monitoring, stronger fallbacks, or design improvements. Drive your projects to delivery. Take ownership of the modules and projects you're responsible for. On work spanning product, QA, frontend, infrastructure, or other backend teams, proactively sync information, surface dependencies and risks, and drive issues to resolution. When requirements are unclear or opinions diverge, lay out the context, offer your own judgment, and help build consensus. Continuously raise engineering quality. Participate in design discussions, code reviews, and system optimization. Spot unreasonable designs, duplicated logic, and latent risks, and propose actionable improvements. Document technical decisions, post-incident learnings, and best practices, and help less-experienced teammates. Apply AI in daily development. Use AI coding tools (Claude Code, Cursor, Codex, etc.) to assist with code comprehension, scaffolding, unit tests, code review, troubleshooting, refactoring, and documentation — validating AI output for correctness, project conventions, performance, and security rather than using it unchecked. What We're Looking For Solid Java backend fundamentals. ~5–10 years of Java backend experience with a strong grasp of collections, concurrency, thread pools, the JVM, network communication, and common performance issues. Proficient with Spring Boot, Spring Cloud, MyBatis, or comparable stacks, able to independently design and build medium-to-large backend modules and reason about the mechanics behind the frameworks you use. Strong system design ability. Experience with complex or high-concurrency systems; comfortable with idempotency, retries, compensation, caching, message queues, distributed locks, data consistency, rate limiting, and service degradation. Able to own module- or service-level design and clearly explain the core flow, failure scenarios, and key trade-offs. Cognitive ability and judgment. Able to understand context and goals on ambiguous problems, separate symptom from root cause, and choose a fitting solution based on business value, user experience, stability, cost, and security — rather than reflexively adding complexity. Drive and ownership. Able to independently own a module or project end to end, from design through development, testing, and launch. Proactively communicates and resolves dependencies, risks, and blockers, and follows through on launch outcomes rather than stopping at code merge. Blockchain or wallet experience. Experience with wallets, blockchain, trading platforms, on-chain data services, or related systems. Understands addresses, public/private keys, mnemonics, transaction signing, broadcasting, on-chain confirmation, gas, and nonce; familiar with the transaction mechanics of at least one of EVM, Tron, or Solana, and with token standards such as ERC-20 and TRC-20. (Strong backend fundamentals and fast learning can offset gaps in blockchain coverage.) High security awareness. Sensitive to private-key, signing, permission, and user-asset security; familiar with replay protection, API authentication, tamper resistance, sensitive-data protection, and least-privilege principles. Actively considers malformed input, duplicate requests, privilege bypass, and data-leak risks when building transaction features. Independent production troubleshooting. Able to diagnose live issues via log analysis, metrics monitoring, distributed tracing, and thread/memory analysis; can form hypotheses and narrow scope even with incomplete information. Hands-on experience with performance degradation, timeouts, message backlogs, data inconsistencies, memory issues, or unstable third-party services. Engineering in the AI era. Willing to use AI coding tools to improve daily efficiency and able to judge whether AI output meets real business requirements before shipping it. Has a basic understanding of prompts, context management, RAG, AI agents, and MCP, or a genuine willingness to keep learning — treating AI as an engineering tool, not requiring an algorithm/model-training background. Nice to Have Integration work on new public chains, new asset standards, or cross-chain protocols Familiarity with WalletConnect, DApp Browser, or signature-request handling Knowledge of MPC, multisig, hardware wallets, or TEE-based key-security schemes Experience with Swap, staking, cross-chain bridges, or DeFi aggregation Address risk detection, allow/deny lists, anti-fraud, or wallet risk-control experience High-concurrency transaction systems, blockchain node services, on-chain data indexing, or transaction-state-tracking systems Familiarity with RPC calls, block scanning, chain reorgs, transaction compensation, and reconciliation mechanisms JVM performance tuning, stability governance, or complex production-incident experience Cross-team collaboration with a track record of driving projects to delivery Real projects built with AI — e.g. AI code review, development agents, MCP servers, intelligent troubleshooting, or knowledge bases Follows developments in AI coding assistants and LLM applications and shares practical takeaways with the team Perks & Benefits Competitive total compensation Comprehensive insurance coverage for you and your dependents More benefits to be discussed after you join Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Location: San Francisco; New York City Perplexity is looking for a Design Engineer to help turn perplexity.com http://perplexity.com into a real growth engine, not a pile of one-off pages. You'll sit shoulder to shoulder with brand designers, PMMs, growth, and content teams, shipping product launch pages, campaign landing pages, and the components and tooling that let those teams move fast without lowering the bar. This is a hands-on role for someone with real taste, sharp attention to detail, and the speed to turn a Figma file, a Slack thread, or a rough sketch into a polished, shipped page quickly. Tech stack: React, TypeScript, Tailwind CSS, Sanity WHAT YOU'LL DO - Ship product launch pages and evergreen marketing pages for products like Comet, Computer, Deep Research, Search, and Hub. Own the work from Figma handoff to production. - Partner with brand designers to build interactive experiences that make the site feel alive and drive engagement. - Maintain and extend our brand design system and component library, keeping Figma and production in sync so brand and creative can scaffold pages with guardrails. - Work closely with the paid ads and growth teams to run A/B tests on landing pages, popups, and upsell modules. Read the results, then iterate. - Migrate the leftover Framer collections to Sanity, model schemas that non-engineers can actually use, and help ship new content types like changelog, customer stories, and academy pages. - Design and unblock yourself when design resources are constrained. You can take a rough direction and turn it into something worth shipping. - Improve the tools around the work: CMS workflows, i18n, SEO, experimentation, and internal tooling for marketing self-serve. If a manual process is slowing the team down, you should want to fix it. WHAT YOU NEED - 3+ years of experience as a front-end or design engineer, ideally on a marketing or growth site. - A portfolio site that shows your previous work on marketing sites and design work. - Strong skills in React, CSS, and modern frameworks. - Deep understanding of responsive design and design-to-code workflows. You know what the platform can do and you stay current on what's new. - Experience maintaining a reusable component library and sweating the design details in code. - A real eye for design. You can tell the difference between "almost right" and "actually right," and your work reflects it. - Attention to detail that shows up unprompted. The 2px misalignment, the wrong easing curve, the widow at the end of the paragraph. - Stellar communication skills and a track record of working effectively in cross-functional teams. You can defend a decision, push back constructively, and explain trade-offs to non-technical stakeholders. - Desire to work in a fast-paced environment, continuously grow, and master your craft. NICE TO HAVE - Experience running A/B tests and reading experiments results in a growth context. - Knowledge of SEO principles, structured data, and localization workflows. - Experience with web animations (GSAP, Motion, Web Animations API), 3D libraries, or interactive storytelling. - Experience working with a headless CMS (Sanity, Contentful). - Experience building internal tools or AI-assisted workflows that made a marketing or design team faster.

Location: Americas Remote About Customer.io Over 9,000 companies — from scrappy startups to global brands — use our platform to send billions of emails, push notifications, in-app messages, and SMS every day. Customer.io powers automated communication that people actually want to receive. We help teams send smarter, more relevant messages using real-time behavioral data. About the role Hi, my name is Nick Guardino, Senior Director of Marketing Ops at Customer.io , and I'm looking for a GTM AI Engineer to help take our AI agents from scrappy prototypes to production-grade systems our GTM teams can depend on. Over the last 3.5 months, our GTM AI team has built 11 agents now running in production, serving 120 active users and roughly 25,000 tool calls a day — all through custom CLIs that work, but weren't built to scale. We believe businesses can run leaner and go further when they deploy AI agents well, and we're figuring out that motion in real time. This role owns the scale and reliability layer so the rest of the team can keep building. What we value Craft over quick wins — energized by making things robust, not just making them work. A point of view — we want someone who asks "why did you build it that way?" and has a specific answer for what to do instead. Comfortable being wrong — you try things fast, and you course-correct just as fast. AI-native by default — you'd rather direct Claude to write and QA code than write it by hand. What you'll do Alpha-to-production ownership — take newly built agents from working v1 to production-ready: write evals, harden prompts and tool definitions, and refactor prototype scaffolding into clean, production-quality code. Observability & stability — instrument tracing, logging, and monitoring across the agent fleet so we catch regressions before our 120+ GTM users do. Deployment & infrastructure — stand up and maintain the pipelines that get agents into users' hands without surprises, owning environment parity and release hygiene on our GCP stack. Database administration — own how agents read from and write to our databases, safely and at scale. Fleet maintenance — monitor agent behavior in production, triage issues, and ship the steady stream of improvements that make an agent indispensable rather than just useful. Partner closely with the GTM AI team — free up our agent builders to stay in their zero-to-one wheelhouse while you own scale and reliability. Bring an outside point of view — tell us what we built wrong, and back it up with a plan to fix it. What we're looking for 4+ years in software engineering, platform/infrastructure engineering, or a similarly technical role, ideally at a B2B SaaS company. Comfort working in the terminal daily, with a real GitHub PR-and-deploy workflow. Cloud hosting experience — Kubernetes, VMs, or equivalent; Google Cloud experience strongly preferred. Experience with how agents interact with and edit databases, including some hands-on database administration. Familiarity with LLM-based application development: prompt engineering, tool/function calling, evals, and modern agent frameworks. Ability to prompt AI tools correctly, review their output critically, and direct them to QA their own work — this is an AI-native role, not a hand-coding one. Scrappy enough to iterate fast, disciplined enough to think about consistency once something needs to scale. A point of view, and the willingness to ask "why did you build it that way?" Compensation & Benefits We believe in transparency. Starting salary for this role is $140,000–$170,000 USD (or equivalent in local currency) depending on experience and subject to market rate adjustment. In addition to base salary, this role includes an equity grant in the form of stock options, so you share in the success you help build. We know our people are what make us great, and we’re committed to taking great care of them. Our inclusive benefits package supports your well-being and growth, including 100% coverage of medical, dental, vision, mental health, and supplemental insurance premiums for you and your family . We also offer 16 weeks paid parental leave, unlimited PTO , stipends for remote work and wellness, a professional development budget, and more. See full benefits here → Our Process No gotchas, no trick questions - just a clear, human process designed to help both of us make an informed decision. 30-minute Zoom call with Recruiter 45-minute Zoom call with Hiring Manager 45-minute Zoom call with a member of the GTM AI team 60-minute Live technical session with the team All final candidates will be asked to complete a background check and employment verifications as part of our pre-employment process. Customer.io recognizes the stifling impact of systemic injustice on diverse communities. We commit to using our influence to increase inclusion and equity within the tech industry. We strive to build an inclusive team culture, implement bias-free hiring practices, and develop community partnerships to expand our global impact. Zoom is the only video conference platform that we use, virtual interviews will be conducted using the video capability (i.e., not via the chat), and offers will be extended in writing on official Customer.io letterhead. Please be vigilant in all of your job search activity, and if you have any questions please contact jobs@customer.io . Join us! Check out our careers page for more information about why you should come work with us! We believe in empathy, transparency, responsibility, and, yes, a little awkwardness. If you’re excited by what you read — apply now.

Location: New York, NY (HQ) Workplace: Hybrid ABOUT RAMP Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. ABOUT THE ROLE As a Design Engineer at Ramp, you sit at the intersection of design and front-end engineering. You bring ambitious ideas to life in real interfaces, prototype directly in code, validate with customers, and ship production experiences with a high bar for craft, performance, and reliability. Design at Ramp is AI first and builder led. Work starts in an LLM to clarify intent and constraints, moves into tools like Claude and Cursor to explore and build, is tested with real customers, and then comes into Figma for systems and polish. AI and self-serve research are default parts of the workflow, not side experiments. We are looking for multiple design engineers who think like a designer, code like a front-end engineer, and treat AI as a real collaborator. WHAT YOU’LL DO - Design and build high-craft product experiences: Own key surfaces end to end, from concept through production. Use layout, interaction, and motion to make complex behavior feel simple and safe. - Work AI first with Cursor and Claude Code: Use LLMs, Cursor, and Claude Code as your starting point. Draft intent, explore implementations, scaffold components, and refactor with AI in the loop. Apply your own judgment to refine quality. - Prototype in code and validate with customers: Build interactive prototypes in React and TypeScript and test them with real users using self-serve research tools. Use what you learn to refine flows before full systemization. - Bridge design systems, product, and brand: Translate Ramp’s design principles into reusable components and patterns. Extend the design system so expressive, brand-aligned moments are easy to build and scale. - Reveal what our agents are doing without noise: Design patterns that show what AI and automation are doing on behalf of customers. Use hierarchy, copy, and motion to earn trust while keeping the default experience simple. - Champion performance and accessibility: Ship work that is fast, accessible, and robust. Pay attention to semantics, focus states, reduced motion, and Core Web Vitals. Partner with engineers to debug and optimize over time. - Share AI-native workflows: Document prompts, patterns, and workflows you use in Cursor and Claude Code. Share them with designers and engineers to raise the bar across the team. WHAT YOU NEED - Strong experience across both design and front-end engineering, with ownership from idea to shipped interface - Fluency in React, TypeScript or JavaScript, semantic HTML, and modern CSS - Active use of tools like Cursor and Claude Code, with clear opinions on how to get high-quality output - A portfolio that shows high visual and interaction craft in live experiences or working prototypes - A systems mindset and interest in building reusable components and patterns - Care for performance, accessibility, and reliability as part of craft - Clear written and verbal communication, and comfort pairing with designers, engineers, and marketers - Based in or open to relocate to NYC NICE TO HAVES - Experience contributing to a design system or front-end component library - Familiarity with experimentation or analytics tools - Experience with headless CMS, design tokens, or theming systems - Background in fintech, B2B SaaS, or other trust-heavy domains - Interest in mentoring others on AI-native workflows BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL) - Flexible PTO - Centralized home-office equipment ordering - Health and wellness stipend - Budget for intra-office travel - Weekly coffee stipend UNITED STATES - 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents - One Medical annual membership - 401(k), including employer match on contributions made while employed by Ramp - Fertility HRA (up to $10,000 per year) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay - Pet insurance - In-office perks: lunch, snacks, drinks, and more - Relocation expense coverage to NYC or SF (if needed) CANADA - Group medical, dental, and vision coverage through Sun Life - Life, AD&D, and disability coverage - Fertility drug coverage (up to $4,000 lifetime) - Group Retirement Plan with employer match (RRSP + DPSP) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay - Employee Assistance Program and virtual care through Lumino Health UNITED KINGDOM - Private medical insurance through Freedom Elite - Virtual GP and at-home care via eMed x Livi - Workplace pension through Penfold, with salary sacrifice option - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.   OTHER NOTICES Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.   Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.   Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice

Location: United States What The Role Is As a Staff Engineer at Babylist, you own some of our hardest domains and decide where they go. Millions of families depend on what we build. Agents write most of the code now. So the hard part is yours: what to build, how it should work and whether what shipped was right. You're still in the code for the genuinely hard problems. Agents handle the volume. You spend your time on the parts that need a person. We're building well beyond the registry now: the financial side of raising a kid, maternal health made simpler and more human, the education new parents are looking for and the community around them. The hard problems run across all of it, plus the platform underneath and the AI we already ship to families. You'll own a big piece of the product, but you won't be boxed into it. The roadmap is open. You have a say in which bets we make, and you pick what you take on next. What You'll Own A Staff Engineer here sets direction. You own a domain: a product surface, a platform area or a capability that cuts across several teams. You set where it's going over the next year or two, sequence the bets that get there and make the technical and product calls along the way. You're still in the code. We don't have architects who've stopped building. If you stepped away, multiple teams would feel it. Your influence shows up in the systems and the work other teams choose to build on. You don't need direct reports to have that reach. It comes from what you build. In practice, you: Take a fuzzy business problem from the first sketch through to production, and stay on the hook for whether it actually helped customers. Build the platform or tooling other teams adopt by choice, and own it as it scales. Make the architecture calls that span teams and the ones that are expensive to reverse. Set the standard for how your domain builds with AI. Decide what good looks like, build the patterns and evals that get agents there and catch the output that's confidently wrong before it ships. Partner with product, design and data as a peer, shaping what's worth building from the start. Coach Senior engineers through the hard calls, the ambiguous ones as much as the technical ones. A few problems people at this level are working on right now: Resolving one customer across registry, shop and health, plus the friends and family buying for them, so personalization works everywhere without each team rebuilding it. Designing the knowledge system our coding agents reliably load, and working out how much context actually helps before it starts to hurt. Building Early Investor, our new family finance product, from scratch, on a deadline that can't move. Who You Are You've shipped production systems for enough years to have earned strong opinions, and you hold them loosely. You can pick up an ambiguous problem and start moving before anyone hands you the full picture. You've already changed how a team builds with AI, and the new way stuck. Most Staff engineers lean one of two ways, and both do well here. Some point their depth at the systems everyone runs on: the platforms, the reliability and security bar, the harnesses that make AI produce good code. Others point it at the customer: framing the problem with PMs as peers, owning a journey end to end, deciding what to build and learning whether it worked. You don't have to be both. You do have to be excellent at one and fluent in the other. A few things that tend to be true of people who thrive here: You measure yourself by impact: a customer outcome, or a system a dozen teams come to depend on. You're curious: you spot problems before they're filed and push your own ideas until they ship. Compensation We post real numbers. For a US-based Staff Engineer, the starting base salary range is $233,500 to $290,700, plus a target annual bonus of 20 percent of base. That's total target cash of roughly $280,200 to $348,840. On top of that you get meaningful equity and a 401(k) match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope. How We Build AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome. The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers. The Stack Core app: Rails, Packwerk, React, TypeScript, Sidekiq Mobile: iOS (Swift), Android (Kotlin) Data, search & events: MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma Machine learning: deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow AI & dev tooling: Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim Infra & ops: AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly Key integrations: Shopify (payments), Iterable (CRM) Why Babylist An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done. Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide. How We Work Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis. How We Hire Three rounds, usually two to three weeks start to finish. Recruiter conversation (30 minutes). Trade context: what you want next, what we're building and straight answers on comp, team and remote. Technical screen (1 hour). One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles. Final round (4 hours). Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours. If your timeline is tight, tell us and we'll move faster. Benefits Company-paid medical and fully covered dental and vision A 401(k) match Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program Winter Wonder Week, a paid company-wide week off at the end of the year A remote-work stipend Mental-health and wellness support A Few Things To Know We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws. We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking. If you have a family member or close relationship with a Babylist employee, let your recruiter know. Official outreach only ever comes from an @babylist.com address

Location: United States Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ Docker seeks a Principal Software Engineer to define the technical vision and architecture for our internal Developer Tools team. This is a rare opportunity to establish how software is designed, built, shipped, and operated at Docker. With the addition of AI we are modernizing our SDLC and building the mechanisms that make the right way the easy way for every engineer. You'll own the technical strategy across four interconnected pillars: Platform Engineering & Self-Service: Design and build the internal developer platform that empowers teams across Docker to unblock themselves, rapidly scaffolding, prototyping, deploying, and operating their own services and tools. CI/CD & Build Systems: Define Docker's technical approach to continuous integration, delivery, and build infrastructure. Establish architectural standards for pipeline tooling, GitOps deployment patterns, build substrate, and release engineering. As Principal Software Engineer, you'll partner with engineering leadership across Docker, principal engineers, Security, Infrastructure, and the service teams to author the SDLC tenets that underpin all of this work, and build the mechanisms those tenets run through. Reporting to the Sr Manager of Developer Tools, you'll collaborate closely with engineering leadership across Docker, product engineering teams, platform teams, and ultimately customers as internal tools evolve into product offerings. WHAT WOULD MAKE SOMEONE SUCCESSFUL IN THIS ROLE You're a technical leader who excels at the intersection of developer experience, platform engineering, and systems design. You think in platforms and golden paths, building once and enabling dozens of teams to move faster. You have strong opinions on what makes developer tools great: invisible by default, indispensable once adopted, and measurable in the workflows engineers already use. You have deep experience across the breadth of the developer tooling stack, CI/CD, build systems, observability infrastructure, and developer platforms, and working knowledge of LLM integration and AI agent development. You understand the nuances of internal platforms: designing for adoption, not mandate; plugging into existing workflows before standing up new ones; and earning trust through data before expanding scope. You have exceptional judgment on when to build custom solutions versus integrate existing tools, and you're comfortable navigating a rapidly evolving landscape across both AI and developer infrastructure. You balance technical excellence with pragmatism, shipping iteratively while maintaining high quality bars. Most importantly, you lead through influence and mentorship, elevating the entire engineering organization's technical capabilities. RESPONSIBILITIES Technical Leadership & Architecture - Define the long-term technical vision and architecture for Docker's developer tooling platform spanning platform engineering, CI/CD, and AI-powered tools - Lead authoring of SDLC tenets in partnership with other principal engineers, Security, and Infrastructure and build the mechanisms those tenets bind to (design gates, code review gates, pipeline standards, visibility) - Establish architectural patterns, technical standards, and best practices across the developer tooling stack - Design highly available, scalable infrastructure for hosting developer tools, agents, and platform services - Drive technical decisions on tooling choices, provider strategies, build/deploy substrate, and agent orchestration frameworks - Partner with Senior Manager and product leadership to align technical architecture with business objectives and productization opportunities Systems Design & Implementation - Architect and build Docker's internal developer platform, the self-service substrate enabling teams to scaffold, deploy, and operate services with minimal friction - Design and implement CI/CD and build infrastructure that supports Docker's SDLC tenets and GitOps deployment patterns - Establish reliability, security, and performance standards across developer tooling including SLOs, monitoring, incident response, and cost management - Design integration points between developer tools and existing infrastructure (CI/CD pipelines, observability platforms, deployment systems) Strategic Impact & Innovation - Evaluate emerging technologies across developer tooling, platform engineering, AI/LLM, and agent frameworks to inform Docker's technical strategy - Define and enforce the golden path, the concrete, left-to-right walkthrough of how Docker builds software, and identify where tooling closes gaps vs. where human process does - Drive technical standards for measuring developer tool effectiveness: adoption metrics, productivity gains, pipeline performance, and developer satisfaction - Lead cross-functional technical discussions influencing company-wide developer tooling architecture - Define technical approach for productizing successful internal developer tools into customer-facing offerings Leadership & Mentorship - Mentor senior and staff engineers on platform engineering, CI/CD patterns, design, and AI/LLM integration - Lead design reviews and technical decision-making across all developer tooling work - Foster culture of technical excellence, experimentation, and rapid prototyping within the Developer Tools team - Serve as primary technical contact and thought leader for developer tooling across Docker's engineering organization - Collaborate with platform teams (Infrastructure, Security, Agentic Platform, Supply Chain Security) to establish shared technical standards and integration patterns - This role may require participation in an on-call rotation to provide support outside of standard business hours, including evenings, weekends, and holidays, as needed. QUALIFICATIONS REQUIRED: - 10+ years software engineering experience with 3+ years in Staff or Principal Engineer roles - Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience. - Proven track record architecting and operating developer-facing platforms, internal tools, or developer productivity systems at scale - Deep expertise in CI/CD systems, build infrastructure, and GitOps deployment patterns - Production experience with cloud-native infrastructure including Kubernetes, observability systems (Prometheus, Grafana, Loki), and deployment tooling - Experience designing self-service platforms, developer portals, or golden path tooling that enable other teams to move faster - Working knowledge of AI/ML technologies and hands-on experience with LLM APIs or AI agent development - Proficiency in Go (preferred), Rust, Java, or Python with strong software engineering fundamentals - Exceptional product and platform mindset considering developer experience, business outcomes, and technical/security trade-offs - Strong communication skills with ability to influence technical and non-technical stakeholders - Track record of technical mentorship and elevating engineering teams' capabilities - Ownership mentality with bias for action and iterative delivery in ambiguous, fast-moving environments - Comfortable with autonomous work in distributed, remote-first teams across multiple time zones PREFERRED: - Experience with MCP (Model Context Protocol) or similar AI agent integration standards - Background in DevOps, SRE, or platform engineering domains - Contributions to open source developer tooling, platform engineering, or observability projects - Experience productizing internal platforms into commercial offerings - Deep knowledge of security, compliance, and operational best practices for production systems - Experience with infrastructure-as-code frameworks (Terraform, Pulumi) and multi-cloud platforms (AWS, GCP, Azure) - Track record driving org-wide adoption of developer tooling and engineering standards WHAT TO EXPECT FIRST 30 DAYS - Understand Docker's current developer tooling landscape: AI tools, CI/CD state, platform engineering gaps, and the foundational SDLC gap - Meet with engineering leadership, principal engineers, and key technical stakeholders across product engineering, Security, Infrastructure, and Agentic Platform - Conduct deep technical assessment of current developer tooling infrastructure to identify opportunities and constraints across all four pillars - Review existing tools in production and understand what's working, what isn't, and the technical lessons learned - Partner with Senior Manager to define initial technical priorities and 90-day technical roadmap across pillars FIRST 90 DAYS - Define and document technical architecture for the Developer Tools platform across: system design, technology choices, integration patterns, and operational model - Ship first production deliverable, either an extension of existing tooling or a net-new tool with architectural patterns and standards that scale to future work - Establish technical foundations for the self-service platform: deployment pipeline, security controls, and cost management - Lead or contribute to the SDLC tenets working session with principal engineers, Security, and Infrastructure - Define success metrics and instrumentation strategy for measuring developer tool adoption, effectiveness, and productivity impact - Create architectural decision records and best practices guides for teams building on the platform FIRST YEAR OUTLOOK - Establish mature technical architecture for the Developer Tools platform with multiple production tools demonstrating value - Build production-ready self-service platform enabling multiple teams to build, deploy, and operate their own tools with minimal friction - Define and implement technical standards for measuring developer productivity improvement: design quality, commit frequency, PR velocity, deployment reliability, and incident response times - Lead technical strategy for productizing successful internal tools into customer-facing offerings - Position Developer Tools as Docker's technical center of excellence for developer productivity, with regular technical talks, demos, and knowledge sharing - Define multi-year technical roadmap including advanced platform capabilities, expanded AI tooling, and emerging technology adoption Docker considers visa sponsorship on a case-by-case basis based on business needs. Compensation & Equity United States: $198K – $319K + equity ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: San Francisco, CA 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. We're seeking an exceptional Research Scientist to join our Life Sciences team at Anthropic. Our team is building a world-class research group focused on making Claude a superhuman life sciences research assistant. This role sits at the intersection of machine learning, software engineering, and biology — you'll directly improve model capabilities on scientific tasks through post-training, evaluation design, and RL environment development. As a core member of our Life Sciences team, you'll work in a high-impact team that translates deep biological domain knowledge into model training objectives, benchmarks, and agentic workflows. You'll help establish Anthropic as a leader in AI-accelerated biology while shaping how frontier models reason about and execute computational biology tasks. This role offers a unique opportunity to shape how frontier AI models learn to do biology. You'll work alongside some of the world's best AI researchers while tackling problems that matter for human health and scientific understanding. If you're excited about turning your computational biology expertise into model capabilities, we want to hear from you. Key Responsibilities Build and ship agentic tools and integrations that let Claude execute real life science workflows — bioinformatics pipelines, database queries, analysis notebooks, literature review Design and build evaluation benchmarks that measure model capabilities on biology tasks — figure interpretation, bioinformatics, protocol reasoning, literature synthesis Work closely with product and design teams to scope, prototype, and ship features for life sciences users Partner with external biotech, pharma, and academic users to understand their workflows and turn feedback into product improvements Build and maintain the engineering infrastructure behind our biology product surface — tool scaffolding, data pipelines, eval harnesses Translate biological domain knowledge into product requirements and evaluation criteria that guide model improvement Minimum Qualifications Experience applying ML and software engineering to biological problems — computational biology, bioinformatics, protein ML, genomics, or similar Experience working in drug discovery or development at a biotech or pharma company, or conducted fundamental research in an academic setting — with an understanding of what real scientific workflows look like and where they break down Strong software engineering skills: comfortable building production-quality Python, working in large codebases, and owning infrastructure end-to-end Hands-on experience training or fine-tuning ML models (LLMs, protein language models, or other deep learning architectures) A track record of shipping computational tools or pipelines that biologists actually use Comfortable navigating ambiguity and defining problems in a rapidly evolving research environment Able to work independently while collaborating tightly with research, product, and domain-expert teams Results-oriented with a bias toward rapid iteration and measurable impact Passionate about using AI to accelerate scientific discovery while maintaining high ethical standards Preferred Qualifications 5+ years of experience applying ML and software engineering to biological problems — computational biology, bioinformatics, protein ML, genomics, or similar Ph.D. in computational biology, bioinformatics, bioengineering, CS, or a related quantitative field — or equivalent industry experience Experience with LLM post-training: RLHF, RL from verifiable rewards, SFT data curation, or eval-driven development Direct experience with therapeutic discovery pipelines — target identification, lead optimization, ADMET modeling, or clinical data analysis Familiarity with bioinformatics tooling and pipelines (sequence analysis, structure prediction, single-cell, variant calling, etc.) Experience building agentic systems or tool-use environments Published research in ML for biology, or open-source contributions to computational biology tools Fluency with biological databases (UniProt, PDB, Ensembl, NCBI) and the ability to reason about their schemas and failure modes 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: $300,000 — $320,000 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 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 for using AI in our application process.

Location: Montreal; Canada; Serbia Workplace: remote ABOUT YOU We are looking for a Principal Engineer to take architectural ownership of the agent-readable Shop Builder platform. This is the most senior individual contributor role on the DevX and AI team, and the decisions you make here — which surfaces to expose, which formats to support, which standards to set — will bind the platform for years. You are not a manager, but your influence is org-wide. You define how developers and AI agents interact with Shop Builder's foundational capabilities: UI as Data, custom blocks, themes, data binding, catalog, payments. You are the technical authority on what the platform exposes and how, and you are deeply hands-on with the hardest parts of that work.   ABOUT US Xsolla is a global payments and commerce platform for the games industry, used by thousands of publishers to monetize, distribute, and operate their titles worldwide. Shop Builder is Xsolla's storefront platform — used by publishers and game developers to launch and operate game shops, from straightforward catalog and webshops to fully custom storefronts built headless on our backend. For more information, visit xsolla.com. The DevX and AI team owns the public APIs, documentation, and AI features that give developers — and AI agents — the full surface they need to customize and extend Shop Builder. This is a net-new team of seven, standing up to fill a real gap: no dedicated team has owned the developer surface end to end. That changes now. Responsibilities Own the technical architecture of the agent-readable Shop Builder platform: which APIs to expose, in what shape, through which surfaces (REST, SDK, MCP, CLI). Define the interface contracts that LLMs and developers interact with — React component APIs, custom block schemas, theme tokens, data binding formats — and maintain them with the rigor of a public API. Design and lead delivery of the MCP server that allows AI agents (Claude Code, Cursor, etc.) to build, deploy, and operate Shop Builder storefronts end-to-end without the editor in the loop. Architect the CLI and local development environment: how developers scaffold projects, iterate locally, preview changes, and push to production. Define the deploy, versioning, and rollback model for developer-published content — custom blocks, themes, and layouts. Design the sandbox and preview environment system so agents and developers can iterate without touching live partner sites. Set the documentation standard: written for LLMs and humans as first-class users, maintained from single canonical sources and published to every surface (CLI help, dev docs, MCP tool descriptions, AI context). Lead the eval harness architecture: how the team measures whether an LLM-generated block, theme, or layout is correct before it ships. Collaborate with Principal/Staff Engineers across payments, auth, live ops, and catalog to pull inbound capabilities into coherent developer-facing surfaces. Serve as the technical bar-raiser for the team: define code standards, review critical implementation decisions, and mentor the Tech Lead and engineers. Contribute to hiring and define the technical culture of the team from day one. Qualifications & Skills 10+ years of professional engineering experience, with a demonstrated track record as a Staff or Principal engineer who has shaped platforms, APIs, or developer tooling used by external builders. Deep expertise in designing and shipping public APIs and SDKs, including versioning strategy, backwards compatibility, and developer ergonomics — strong opinions about what makes an API delightful vs. painful. Expert-level proficiency in JavaScript/TypeScript and React — the primary interface language for LLMs and developers on this platform. Hands-on experience building CLI tooling and local developer workflows (scaffolding, hot reload, file-based config, deploy commands). Solid understanding of the Model Context Protocol (MCP) or equivalent agentic tool-use interfaces, and practical experience building tools that AI agents can reliably invoke. Experience building systems at global scale on cloud infrastructure (AWS or GCP), with deep knowledge of containerization, CI/CD, and infrastructure-as-code. Ability to write and reason about LLM-friendly documentation and API surfaces: you understand that token-efficiency, predictability, and schema clarity matter as much as human readability. Exceptional technical communication: clear RFCs and ADRs, productive architecture reviews, and the ability to explain second-order consequences to engineering and business leadership. Comfort operating in a greenfield context — you define the structure rather than inherit it. Nice to Have Prior experience in game tech, digital commerce, or storefront platforms — understanding the publisher/developer relationship and headless vs. hosted deployment patterns. Experience building platforms where AI agents are a first-class user: MCP servers, LLM tool registries, agent eval pipelines. Familiarity with Figma's plugin/component API, design token standards, and design-to-code pipelines. Contributions to open-source developer tooling, SDK frameworks, or API standards. Background in block or extension marketplace design: sandboxing third-party code, schema validation, publisher ecosystems. Published technical writing, conference talks, or influential community presence in developer tooling or AI-native development. Benefits: We are passionate about fostering a supportive environment for our team, so we prioritize the physical, mental, and emotional well-being of our employees and their families through a comprehensive Benefits Program. This includes medical, dental, and vision, PTO, and a personalized career roadmap for each employee. By investing in professional development through training and educational opportunities, we ensure that our team thrives both personally and professionally. Together, we’re not just building a business; we’re cultivating a community that values creativity, collaboration, and the transformative power of play.    Equal Employment Opportunity Statement: Xsolla is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or any other characteristic protected by law.   We consider qualified applicants with criminal histories in accordance with the Fair Chance Act.   Criminal History Consideration: For this role, we will conduct a background check that may include the following: Criminal history check Employment verification Education verification Relevance to Job Responsibilities: The background check is relevant to this position because of the following role responsibilities: Accessing confidential company data Ensuring compliance with regulatory requirements Handling sensitive financial information/managing budgets/accessing funds Rights Under the Fair Chance Act: Applicants are encouraged to inquire about their rights under the Fair Chance Act. If you have questions regarding our hiring practices, please contact careers@xsolla.com.

Location: United States What The Role Is As a Senior Engineer at Babylist, you take on hard problems and own them end-to-end. Millions of families depend on what we build. Agents write most of the code now. So the hard part is yours: what to build, how it should work and whether what shipped was right. You're still in the code for the genuinely hard problems. Agents handle the volume. You spend your time on the parts that need a person. We're building well beyond the registry now: the financial side of raising a kid, maternal health made simpler and more human, the education new parents are looking for and the community around them. The hard problems run across all of it, plus the platform underneath and the AI we already ship to families. You'll start on a team, but you won't be boxed into it. The roadmap is open, your scope grows as you do and you have a say in what you take on next. Senior here means owning whole problems; Staff is the next step up, setting direction across a domain. What You'll Own A Senior Engineer here owns problems, not just features. You're handed an outcome, you decide what to build, ship it and own whether it worked. You act on incomplete information and change course fast when the evidence says you were wrong. What you do depends on what the team needs: Frame the problem with your PM as a peer, run the experiment and bring customer evidence into what gets built. Harden a critical path, kill a class of incidents or design the abstraction your team builds on. Be the reviewer people want on the risky changes. Manage up with crisp choices: raise the risks early and protect the right tradeoffs. Share what you're learning about AI openly, so the whole team gets sharper. A few problems people at this level are working on right now: Deciding what the registry recommends to each family, from the ranking to the model behind it, and proving in a live experiment that it actually helps. Building the evals system that catches our AI support agent making things up before a customer does. Making a child's info one source of truth instead of five disconnected flows, so parents set it up once and new products like Early Investor build on it. Who You Are You've been shipping production systems for years, and you've got the judgment to show for it. You can pick up an ambiguous problem and start moving before anyone hands you the full picture. The strongest Senior engineers here are generalists, and usually the most prolific builders on their team. You go wherever the problem leads: a backend service one week, a stubborn frontend bug the next, the data pipeline after that. When it's hard you dig in, and you learn unfamiliar parts of the stack fast. Range is the Senior signature. Compensation We post real numbers. For a US-based Senior Engineer, the starting base salary range is $202,200 to $251,700, plus a target annual bonus of 15 percent of base. That's total target cash of roughly $232,530 to $289,455. On top of that you get meaningful equity and a 401(k) match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope. How We Build AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome. The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers. The Stack Core app: Rails, Packwerk, React, TypeScript, Sidekiq Mobile: iOS (Swift), Android (Kotlin) Data, search & events: MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma Machine learning: deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow AI & dev tooling: Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim Infra & ops: AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly Key integrations: Shopify (payments), Iterable (CRM) Why Babylist An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done. Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide. How We Work Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis. How We Hire Three rounds, usually two to three weeks, start to finish. Recruiter conversation (30 minutes). Trade context: what you want next, what we're building and straight answers on comp, team and remote. Technical screen (1 hour). One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles. Final round (4 hours). Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours. If your timeline is tight, tell us and we'll move faster. Benefits Company-paid medical and fully covered dental and vision A 401(k) match Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program Winter Wonder Week, a paid company-wide week off at the end of the year A remote-work stipend Mental-health and wellness support A Few Things To Know We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws. We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking. If you have a family member or close relationship with a Babylist employee, let your recruiter know. Official outreach only ever comes from an @babylist.com address.

Location: San Francisco, CA | New York City, NY | Seattle, WA 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: We're hiring several Product Operations Managers to embed within our core product teams. Each will contribute to a key component of our stack. Whether you are ensuring models work within each of our harnesses, prioritizing a great experience across cloud offerings, or building the application layer that keeps users on the frontier, the Product Operations team is an integral part of delivering great products to the world. Product Operations is the connective tissue between Research, Product, and the market. We shorten the distance between what our models can do and what people get to use. Each of us sits inside one product team as an extension of its leadership, and together we run one shared operating system for how Anthropic ships and learns. On a given day you might get a launch through its final review, run an early access window, or triaging customer feedback. The rest of the week you build the systems so the team ships and learns faster next time. Our team is small and gets unusual leverage from Claude enabling us to fill gaps across the company and deliver outsized value. Responsibilities: 1. Ship with confidence Own launch readiness for your team. Keep our launch calendar the source of truth for what is shipping and when. Get every major launch through go/no-go: pre-read written, Security, Safeguards, Legal, and Commercial sign-offs recorded, and any accepted risk written down on purpose. Run early access and beta programs that return signal Product and Research can act on. Define the question before the window opens, give testers the scaffolding to answer it, and close each one with a retro on whether the feedback landed. Program manage new model launches on your surface: readiness goals set in advance, testing and eval coverage tracked, issues triaged, prompting changes landed, retro run. You won't write the evals. You run the program around them. 2. Close the loop with users Turn a lot of noise into two clear signals: what users are asking for, ranked by impact and mapped to the roadmap, and which customers or cohorts are blocked, on what, and why it matters. Plug your team into Anthropic's shared feedback systems rather than building a private one, and improve the shared systems where they fall short. Make sure the field, Support, and Research hear back about what happened with what they sent. 3. Run the team's operating system Set the team's pace: planning, business and execution reviews, goal tracking, offsites. Own how your team works with Legal, Safeguards, Security, GTM, and other product teams so partnering with your team is predictable. Push reporting overhead toward zero. Reviews and digests should be generated from data that already exists. Fill the gaps. Every embedded seat carries one or two projects unique to its team, for example managing Monthly Business Reviews and helping track progress between cycles. 4. Build with Claude Build the tools you need yourself: Claude-powered triage, dashboards that read and write to our systems of record, skills and agents that take the chasing out of the job. Contribute what you build back to the ProdOps team as reusable patterns (launch checklists, EAP setup, lookbacks, deprecations) so nobody starts from scratch. You may be a good fit if you have: Have owned an operational program end to end (launches, early access, feedback, or planning) that a product team relied on to make decisions. You designed it and ran it, not just executed someone else's plan. Have built a process from zero to one and then simplified it as it scaled. You treat process as a product: it has users, metrics, and a happy path people want to follow. Have worked embedded with product leadership and can move a team without formal authority. Build with AI yourself. You have shipped Claude or other LLM-powered workflows, written the prompts, iterated on the outputs, and can describe model behavior with specifics. Have direct experience managing evals, refining system prompts, and adapting harnesses to new models. Have direct experience working with Cloud providers in partnership or GTM capacity Have commitment to safe deployment of AI. Bonus if experience with AI Safety and Safeguards. Bonus: Program managed model launches or model quality at an application-layer AI product. Run early access, beta, or design partner programs. Product management, technical program management, chief of staff, or strategy and operations experience at a startup or fast-growing product company. 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: $260,000 — $325,000 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 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 for using AI in our application process.

Location: Toronto; London; New York; Montreal Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! ABOUT COHERE AND NORTH Cohere is revolutionizing enterprise AI with North, an agentic AI platform designed to securely deploy AI agents and automations within organizations' infrastructure. North empowers employees to streamline workflows, automate repetitive tasks, and unlock actionable insights while ensuring data privacy and compliance. North combines cutting-edge generative and search models with customizable integrations to drive productivity and innovation at scale. ROLE OVERVIEW We are seeking an Agent Harness Product Manager to own the execution layer that makes North agents reliable, capable, and production-ready. This is a role that sits at the intersection of three domains: Agent Loop and Execution. Own the core agent runtime: tool orchestration, parallel execution, sub-agent delegation, sandbox code execution, and failure recovery. You will define how North agents plan and act across long, multi-step workflows and ensure the execution environment is robust enough for the most demanding enterprise tasks. You are expected to engage at the implementation level, contributing to architecture decisions alongside engineering rather than simply handing off requirements. Context Engineering. Own how our Agents manage the context window as a deliberately controlled resource. This includes progressive disclosure of tools and skills, context compaction and summarization, offloading of large payloads to a persistent filesystem, and the instrumentation that keeps agents oriented across extended trajectories. Model-Scaffolding Co-evolution. Own the feedback loop between North's harness and the Modeling Team. This PM is the connective tissue that makes that possible: ensuring harness design decisions are validated by Modeling before they are built, that evals are the shared bridge between both teams, and that as the harness evolves the model evolves with it. RESPONSIBILITIES - Define and own the roadmap for North's agent harness, including the agent loop, context engineering layer, tool orchestration, sandbox execution, and sub-agent delegation - Serve as the primary interface between North engineering and Cohere's Modeling team, ensuring new harness capabilities are validated before being built and that neither team paints itself into a corner - Own North's agentic evaluation framework, ensuring evals are compatible with both the North harness and Modeling's training infrastructure, and that they serve as a reliable bridge between product and research - Engage enterprise customers to surface real-world agentic failures and translate findings into concrete product and model requirements - Partner with the agentic expert modeling team to define goals that maximize the impact of our models and prioritize model capabilities and evals most critical for delivering on those goals. Establish a clear roadmap for our agentic modeling capabilities. - Stay current with the open-source and commercial agent ecosystem and drive adoption decisions that keep North's architecture aligned with emerging standards. REQUIREMENTS - 5+ years of product management experience as a research PM, in agentic AI systems,, or applied ML products - Deep understanding of agentic harnesses, including the latest paid and open source offerings. - Deep understanding of modern LLM agent architectures, including multi-agent systems, tool-augmented reasoning, memory and retrieval, programmatic orchestration, RAG, and long-horizon execution - Strong grasp of agentic evaluation design, including how to measure task completion, failure recovery, and long-horizon reliability, and how to diagnose model vs. scaffolding gaps - Technically deep enough to contribute to architecture decisions at the implementation level: comfortable reviewing and shaping design docs, reasoning about async execution patterns, sandboxed environments, filesystem design, and the tradeoffs that come with building harness capabilities into a production platform - Ability to flex between ML research conversations and engineering architecture discussions with equal fluency - Track record of shipping platform-layer products with demonstrated impact on reliability, performance, or capability. NICE-TO-HAVES - Direct experience in developing and shipping leading agentic harnesses. - An active practitioner of agent frameworks who regularly builds with and follows the latest developments in open-source harnesses, coding agents, and orchestration tools in both professional and personal work - Hands-on experience with enterprise agentic deployments: multi-tenant orchestration, tool permissioning, audit trails, and compliance requirements - Familiarity with infrastructure constraints relevant to enterprise deployments: on-premises environments, scalability challenges, and the operational tradeoffs of running complex agent workloads in restricted or air-gapped settings - Prior work at the intersection of research and product, translating nascent model capabilities into shipped product features - Background working within or closely alongside an ML research or post-training team. WHY JOIN COHERE? - Impact: Shape how Canada's most important public institutions adopt and deploy frontier AI. - Innovation: Work alongside leading researchers and engineers solving complex ML challenges. - Growth: Competitive compensation, equity options, and opportunities for professional development. - Flexibility: Hybrid work model with offices in key global locations (Toronto, Montreal, New York, San Francisco, London, Paris, and Korea) FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.