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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: Hong Kong, Hong Kong SAR OKX will be prioritising applicants who have a current right to work in Hong Kong, and do not require OKX's sponsorship of a visa. Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About The Opportunity We're looking for a hands-on product manager to drive growth across our platform's trading and asset business — spot, perpetuals, TradFi, and beyond. You'll ship the product features behind our growth programs, run the campaigns (including token-listing campaigns) that power them, and grow the trading volume and assets they generate — owning the full lifecycle from requirements and delivery through launch, execution, data, and iteration. What You’ll Be Doing Drive product feature delivery. Own the end-to-end delivery of related product features — requirement grooming, UI/UX reviews, tracking dev and QA progress, and launch acceptance — to ship on time and at high quality. Run campaigns end-to-end. Set up, configure, and manage the full lifecycle of marketing campaigns — including token-listing campaigns, new-token Staking, and related Campaigns — ensuring each integrates smoothly with the underlying product features. Grow trading volume and assets through campaigns. Use campaigns and incentives to grow trading volume across the platform's asset categories (spot, perpetuals, TradFi); design and rapidly iterate growth mechanics with clear hypotheses, validate them against real data, and tailor the lever to each category's users and mechanics. Own channel attribution and analysis. Build and maintain channel attribution — breaking trading volume down by channel, campaign, and incentive — and use data analysis to run volume breakdowns, channel ROI, and user segmentation to find the highest-leverage opportunities and guide resource allocation. Monitor and optimize. Track real-time data during launches and campaigns — user engagement and conversion funnels — respond quickly to anomalies and risk-control alerts, and produce regular retrospective reports. What We Look For In You 3+ years in product management, growth, or campaign operations — ideally with trading or fintech products. Strong data analysis skills; able to reach conclusions independently from data and turn them into decisions. Solid understanding of trading products (spot, derivatives, TradFi) and their users. Comfortable driving execution across functions and keeping many moving parts on track. Fast and decisive under ambiguity; a clear communicator who can turn complex data into recommendations leadership can act on. Nice-To-Haves Crypto-native or fintech background. Genuine interest in trading, with hands-on trading experience. Global market growth experience. Comfortable leveraging AI tools to boost output. Perks & Benefits Competitive total compensation package L&D programs and education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! Please note that Hong Kong is a group-level service hub, and OKX does not carry on a business of operating a virtual asset trading platform in Hong Kong. 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: Singapore, Singapore OKX will be prioritising applicants who have a current right to work in Singapore, and do not require OKX's sponsorship of a visa. Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About The Opportunity We're looking for a hands-on product manager to drive growth across our platform's trading and asset business — spot, perpetuals, TradFi, and beyond. You'll ship the product features behind our growth programs, run the campaigns (including token-listing campaigns) that power them, and grow the trading volume and assets they generate — owning the full lifecycle from requirements and delivery through launch, execution, data, and iteration. What You’ll Be Doing Drive product feature delivery. Own the end-to-end delivery of related product features — requirement grooming, UI/UX reviews, tracking dev and QA progress, and launch acceptance — to ship on time and at high quality. Run campaigns end-to-end. Set up, configure, and manage the full lifecycle of marketing campaigns — including token-listing campaigns, new-token Staking, and related Campaigns — ensuring each integrates smoothly with the underlying product features. Grow trading volume and assets through campaigns. Use campaigns and incentives to grow trading volume across the platform's asset categories (spot, perpetuals, TradFi); design and rapidly iterate growth mechanics with clear hypotheses, validate them against real data, and tailor the lever to each category's users and mechanics. Own channel attribution and analysis. Build and maintain channel attribution — breaking trading volume down by channel, campaign, and incentive — and use data analysis to run volume breakdowns, channel ROI, and user segmentation to find the highest-leverage opportunities and guide resource allocation. Monitor and optimize. Track real-time data during launches and campaigns — user engagement and conversion funnels — respond quickly to anomalies and risk-control alerts, and produce regular retrospective reports. What We Look For In You 3+ years in product management, growth, or campaign operations — ideally with trading or fintech products. Strong data analysis skills; able to reach conclusions independently from data and turn them into decisions. Solid understanding of trading products (spot, derivatives, TradFi) and their users. Comfortable driving execution across functions and keeping many moving parts on track. Fast and decisive under ambiguity; a clear communicator who can turn complex data into recommendations leadership can act on. Nice-To-Haves Crypto-native or fintech background. Genuine interest in trading, with hands-on trading experience. Global market growth experience. Comfortable leveraging AI tools to boost output. Perks & Benefits Competitive total compensation package L&D programs and education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! 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: Remote (Germany) Workplace: remote ELEKS Product Design Office is looking for a Middle/Senior UX Designer in Poland, Croatia and Germany. Our customer is a major German university hospital. The role focuses on designing and continuously evolving the user experience across complex public-facing and internal web applications. REQUIREMENTS 6+ years of professional experience in UX/UI design Strong expertise in design systems and complex digital platforms C1-level German and excellent command of English Proven experience working in agile, interdisciplinary teams and projects Willingness to attend approximately 10 on-site meetings in Magdeburg throughout the project Experience in healthcare, public sector, education, CMS platforms (Drupal, TYPO3, Sitecore, AEM), and the implementation of accessibility standards is a strong advantage Strong experience in user research, user-centered design, information architecture, interaction design, and usability Proven ability to create user journeys, wireframes, user flows, clickable prototypes, and detailed design specifications Excellent practical knowledge of Figma and FigJam Practical experience with Miro or comparable collaborative workshop tools Strong expertise in responsive and mobile-first design approaches Experience conducting design reviews and ensuring implementation quality Reliable availability during agreed CET/CEST core business hours RESPONSIBILITIES Analyze and optimize user journeys for different internal and external target groups Develop and continuously improve information architecture, navigation, and user guidance Plan and conduct user research, interviews, stakeholder workshops, and usability tests Create wireframes, clickable prototypes, user flows, and detailed design specifications Derive functional and technical design requirements from the style guide and approved Figma mock-ups provided under Lot 1 Define and maintain design tokens, breakpoints, grid systems, and layout rules Build and evolve a version-controlled design system Design reusable templates, page types, modules, and components Develop responsive and mobile-first designs Define all relevant component and interaction states Ensure a consistent visual experience across both the website and intranet Consider long labels, varying content volumes, and multilingual content. Ensure compliance with WCAG 2.1 AA, BITV 2.0, and EN 301 549 requirements Design accessible navigation, forms, controls, and interactive components Conduct design reviews and verify implemented interfaces against approved designs Collaborate closely with business analysts, frontend and backend developers, quality assurance, content editors, and project management Document design decisions and provide implementation-ready specifications to the development team Participate in required on-site meetings in Magdeburg

Location: USA Workplace: remote JTX is our trading app, and it runs on the fastest market infrastructure on Solana, which we also built. What nobody has done yet is make that speed something a trader can feel. That is this job. JTX is live. Two frontend engineers built it to this point and you would be the third. The work now is one to a hundred: harden what exists, make it hold up under real volume, expand onto mobile, and raise the ceiling on every screen a trader touches. We're a small team with product-market fit. That means: High ownership: every team member drives significant technical decisions and shapes our product roadmap. Fast execution: we ship rapidly and iterate based on real-world feedback. Progress, not motion. High quality bar: the details are the product. We don't trade them for speed. About the Position You'll own the surface of JTX across web and mobile: order entry, market data, charts, positions, execution quality, onboarding, and the wallet flows underneath all of it. The role suits a generalist with strong taste. You'll partner with design, product, and the infrastructure team, and you'll make architectural calls that stick for years. If you've spent time thinking about how markets actually work on Solana and want to build the product layer on top of that, this is the role. Stack: React 19 + TypeScript on Next.js. Jotai + TanStack Query. Tailwind with a token-based design system. TradingView Advanced Charts on our own datafeed. Privy wallets. WebSockets to our engine. Web ships as a PWA; native mobile apps are in development. What's Hard Right Now Data freshness: several live WebSocket streams (order book, trades, candles, stats) feed many panels at once; keeping them fast, consistent with each other, and honest through async gaps (stale quotes, pending fills) Performance: a data-dense terminal that stays smooth under constant streaming updates, including on mid-range hardware Security: wallet signing, session auth, strict CSP, hardened supply chain Shipping volume: three engineers own the entire surface of a live exchange; the backlog is bigger than the team, so throughput and prioritization are part of the job Keeping product behavior and design language consistent between web and mobile while being very attentive to nuances of each mobile platform Making execution quality something a trader can see in a glance instead of something they take on faith What You'll Do Build and own the JTX client across web and mobile Ship real-time trading interfaces: order books, charts, order entry, positions, fill and execution visibility Hit tight latency and render budgets against streaming market data, and decide what belongs on the client versus the server Build wallet and signing flows, including self-custodial and embedded wallet onboarding Own the shared component, state, and data layers the rest of the product team builds on Make architectural decisions that hold as the codebase, the team, and the user base grow by an order of magnitude Ship fast, watch real users, iterate What We're Looking For Attention to detail bordering on obsessive. You can look at a screen and say what is wrong with it, and it bothers you until it's fixed. 5+ years building production frontend, including something real-time, data dense, or financial Deep React and TypeScript. You can explain why a component re-rendered and then fix it. Mobile experience: React Native, Expo, or native iOS and Android Strong fundamentals: browser performance, memory, websockets, network behavior under load Security-first instincts around signing flows, key handling, and what should never touch a log Comfortable in a codebase that is already live. You can refactor and clean up without stopping shipping. Able to weigh business and engineering tradeoffs, and to explain complicated things simply Relevant Background If you have experience in any of the following, you may be a good fit: Trading terminals, exchange or brokerage frontends Consumer fintech apps at scale Charting, time series, or high-frequency data visualization (canvas, WebGL) Solana or EVM app development, wallet integrations, transaction signing Maintaining a public TypeScript library or design system

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 Companies are adopting AI across more teams, but most still struggle to produce real workflows, measurable outcomes, and efficient spend. Ramp’s AI Solutions team helps customers turn that spend into working systems: agents, automations, and integrations that run real finance operations, built on top of Ramp’s growing AI product stack, including Glass, Inspect, Router, and Token Spend Management. As a software engineer on AI Solutions, you'll co-lead customer engagements with an AI Solutions Strategist while also helping turn repeated customer needs into platform capabilities across Ramp’s AI product stack. The Strategist owns business discovery, the ROI story, stakeholder alignment, and rollout planning. You own the technical side: discovery, solution design, prototyping, implementation, production readiness, and the product feedback loop back into our platform and AI primitives. This is a deeply client-facing, hands-on building role based in New York, with occasional travel depending on engagements. You'll take projects from a customer's first workflow-discovery sessions through launch and into steady, measurable production use — then turn what you learned into reusable product patterns the next customer can adopt without starting from zero. WHAT YOU'LL DO - Ship production AI workflows for the companies we partner with — agents, automations, and integrations their teams use every day. - Translate customer work into platform work by identifying needs across deployments and helping improve Ramp’s AI primitives. - Make the next deployment easier by turning customer specific work into reusable components, product feedback, reference architectures, and playbooks. - Run technical discovery with customers: current workflows, systems, data quality, constraints, and what's blocking adoption. - Turn customer goals into concrete requirements, including security, privacy, reliability, performance, scalability, and cost. - Prototype fast with end users to de-risk the approach before you build it out. - Own the technical plan end to end: architecture and data flow, integrations across Ramp and customer systems, permissions and auditability, evals and acceptance tests, and monitoring and runbooks. - Measure what you ship — quality, adoption, and cost — and stay with it until it's reliable, supportable, and handed off. WHAT YOU NEED - A track record of building from 0 to 1 in ambiguous environments: finding the real problem, shipping a first version quickly, learning from users, and hardening it over time. - Hands-on experience building LLM systems — agents, RAG, evals, and monitoring — and sound judgment on trade-offs like quality, latency, cost, and model choice. - Strong coding ability in Python, TypeScript/JavaScript, Java, Go, or similar. - Comfort working across APIs, integrations, data pipelines, and cloud infrastructure (AWS, GCP, or Azure), and designing systems that are secure and scale. - Experience working directly with customers or end users: you can scope an ambiguous problem with a room of stakeholders and write clear technical docs afterward. - Strong written communication. You can produce technical plans, customer facing explanations, handoff docs, and clearly explain tradeoffs. - Willingness to travel up to ~50%, flexible based on project and customer needs. Nice to have - Background in forward deployed engineering, solutions architecture, technical consulting, or sales engineering. - Familiarity with finance operations workflows such as AP, procurement, expenses, close, reconciliation, and reporting. - Experience turning repeated customer needs into reusable product primitives, internal tools, or implementation playbooks. - Experience optimizing AI cost or performance, such as model routing, caching, or token spend analysis. 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: Remote - EMEA Workplace: Remote ABOUT US Constructor powers product search and discovery for some of the largest retailers in the world. We serve billions of requests every week, and you’ve probably seen our results somewhere and used our product without knowing it. We differentiate ourselves by focusing on metrics over features, and reinventing search and discovery from the ground up as a machine learning challenge with the specific goal of improving metrics like revenue. We’re approximately doubling year over year despite the market slowing down and have customers in every eCommerce vertical. We’re a passionate team of technologists who love solving problems and want to make our customers’ and coworkers’ lives better. We value empathy, openness, curiosity, continuous improvement, and are excited by metrics that matter. We believe that empowering everyone in a company to do what they think is best can lead to great things. JOB SUMMARY We’re looking for a highly technical, systems-minded Senior Product Manager to lead two critical search intelligence teams: Machine Learning & Recall and Query. Search at Constructor is fundamentally an ML challenge, and this role sits at the absolute entry point of our discovery pipeline, right where shopper intent meets candidate retrieval. In this role, you will bridge the Query team (understanding what a shopper means across intent, entities, and language) with the Machine Learning & Recall team (retrieving the exact right set of candidate products across massive catalogs). You will define strategy across both domains, balancing state-of-the-art techniques, such as vector search, semantic parsing, dense embeddings, and LLM-assisted query interpretation, with low-latency production execution. You won’t be measured on shipping features for the sake of it; you’ll be measured on candidate quality, query accuracy, and driving business outcomes like conversion rate, search-attributed revenue, and revenue per visit. WHAT YOU’LL DO - Set a unified roadmap: Define the multi-quarter vision and strategy across both the Machine Learning & Recall and Query teams, ensuring query understanding and candidate generation evolve hand-in-hand. - Drive Query intelligence: Lead the Query team to push boundaries in tokenization, spell correction, entity extraction, intent classification, and LLM-assisted query parsing across multiple languages. - Advance Recall systems: Lead the Machine Learning & Recall team in evolving candidate generation architecture, seamlessly combining traditional keyword search with modern dense embeddings, vector retrieval, and hybrid recall models. - Move core business metrics: Own measurable lift in search-attributed conversion, revenue per visit, and GMV across all retail customer verticals. - Turn research into production wins: Work shoulder-to-shoulder with ML researchers, data scientists, and software engineers to take SOTA models from research to low-latency, cost-effective production systems. - Balance ML performance trade-offs: Make data-backed decisions balancing model complexity, accuracy, inference latency, compute costs, and real-time execution constraints. - Build evaluation frameworks: Establish robust offline and online measurement systems to evaluate retrieval precision and query understanding accuracy against customer revenue outcomes. - Orchestrate pipeline handoffs: Ensure candidate product sets and query context flow cleanly into downstream ranking and search quality models without signal loss. - Solve systemic issues: Lead technical triage when query interpretation or retrieval anomalies occur, building durable, automated fixes rather than one-off patches. WHAT SUCCESS LOOKS LIKE Within your first year, you will have: - Evolved our hybrid recall framework to measurably improve candidate generation precision for long-tail queries and complex catalog structures. - Driven quantifiable lift in search-attributed conversion and revenue per visit across major customer verticals. - Stood up an integrated evaluation framework connecting query parsing and candidate recall directly to business outcomes. - Optimized inference latency and compute infrastructure to ensure high-capacity ML models run fast and cost-effectively in production. BENEFITS - Unlimited vacation time - we strongly encourage all of our employees to take at least 3 weeks per year. - A competitive compensation package including stock options. - Company-sponsored US health coverage (100% paid for employee). - Fully remote team - choose where you live. - Work-from-home stipend! We want you to have the resources you need to set up your home office. - Apple laptops provided for new employees. - Training and development budget for every employee, refreshed each year. - Parental leave for qualified employees. - Work with smart people who will help you grow and make a meaningful impact. THIS POSITION IS FULLY REMOTE — CONSTRUCTOR.IO http://Constructor.io IS A REMOTE-FIRST COMPANY. DIVERSITY, EQUITY, AND INCLUSION AT CONSTRUCTOR At Constructor.io http://Constructor.io we are committed to cultivating a work environment that is diverse, equitable, and inclusive. As an equal opportunity employer, we welcome individuals of all backgrounds and provide equal opportunities to all applicants regardless of their education, diversity of opinion, race, color, religion, gender, gender expression, sexual orientation, national origin, genetics, disability, age, veteran status or affiliation in any other protected group. How we handle your data. By submitting this application, you acknowledge that Constructor will collect and process the personal data you provide for the purpose of evaluating your candidacy for this role. If you are not selected, we will retain your data for a limited period as described in our Recruitment Privacy Notice https://constructor.com/recruitment-privacy-notice. After that period your data will be deleted or anonymized.

Location: Barcelona, Spain Workplace: remote Welcome to OLX  We're building marketplace sustainable ecosystems that millions of people depend on every month – to buy and sell cars, find homes, land jobs, and trade secondhand goods. It's commerce that matters: safe, smart, and environmentally responsible. We do this with courage to innovate, commitment to outcomes, collaboration across 50+ nationalities and 7 markets, and a customer-led approach that puts real people first. Add a desire to win – and you get a culture that's ambitious, fast-moving, and built on trust. Our brands – including AutoTrader, OLX, Otomoto, Property24, and more – are loved by millions. And we're backed by Prosus, one of the world's largest tech investors.  Join OLX and see how far you can go. We believe the future of our products sits at the intersection of AI and design. Our ambition is to become an AI-native organization, where intelligent systems and human-centered design come together to create faster, smarter, and more meaningful customer experiences. We’re rethinking how products are built, how experiences are shaped, and how teams deliver impact. A key part of this transformation is creating the right foundations and infrastructure to enable high-quality experiences at scale - where design systems, patterns, and workflows are structured, scalable, and AI-readable, unlocking new levels of speed, consistency, and innovation. The role We're looking for a Senior Product Designer to join our Design System team, working across our Real Estate products. You'll play a key role in evolving our design system, helping designers and engineers across the business design and build with greater consistency, quality and pace. You'll work day to day within a small, dedicated pod, spanning web and app. But the system serves designers across multiple tribes, each shipping their own product work. You'll work within our contribution model, helping teams outside the pod propose, adopt and evolve components without fragmenting the system. We're looking for someone with strong craft, attention to detail, and curiosity about systems thinking and AI-assisted workflows. You'll help create a coherent product experience across our brands while developing your own design systems practice. Key responsabilities: Design and evolve reusable components, patterns and foundations within our design system, reducing duplication and improving consistency across tribes Define component behaviour, states and variants, working directly with engineering to ship them Run and improve the contribution model: the process and standards that let designers outside the core pod propose and ship components without breaking system coherence Support design work from problem framing through to documentation and handover, using research and feedback from teams to inform decisions Create clear documentation and specifications covering variants, edge cases and usage guidance Collaborate closely with engineers on token strategy and the practical link between Figma and production code Resolve conflicts between a tribe's local need and the system's long-term coherence Work with product design teams to identify gaps and embed stronger systems thinking across products AI-enabled Design Systems: Use AI-assisted tooling as part of your daily workflow, from research through to prototyping and component definition Contribute to making the system well-structured for AI-assisted workflows, including tokens, documentation and reusable patterns Know when to override AI output with your own design judgment, and be able to explain why What we're looking for: Proven experience designing and maintaining a design system at scale, not just documenting one Experience running or contributing to a contribution model, or a clear point of view on how you'd build one Strong technical fluency: you understand how your decisions translate into code, and work with engineers as a peer, not a handoff Sharp judgment on trade-offs: when to enforce consistency, when to allow exceptions Strong communicator, able to justify design system decisions to stakeholders who don't share your priorities, and bring other designers along rather than dictate to them Comfortable with AI-assisted tools, with an interest in applying them in practical ways to improve speed, quality and consistency Required experience A portfolio demonstrating strong product and systems thinking, with evidence of shipped impact, not just documented patterns Experience working in Figma, including component libraries, variables and tokens, alongside experience with built or coded prototypes Experience working closely with engineers to deliver high-quality, scalable outcomes Experience or strong interest in AI-assisted design or development workflows Hiring Process First Stage - Recruiter Screen This is your first interview with our Talent Acquisition team. We’ll explore your background, skills, and experience, as well as your approach to autonomy, ownership, and critical thinking. It’s also a chance to discuss your aspirations and ensure alignment with our culture and values. Second Stage - Portfolio Review In this stage, you’ll meet with the Hiring Manager and a Designer from the team. We’ll explore your process thinking and approach to design through a case study of your choice. This is also a great opportunity to discuss how you collaborate with others and how your values align with our team culture. Third Stage  - AI Sandbox Challenge This is a dynamic and interactive session where you’ll have the chance to demonstrate your thought process in action. It’s designed to give us insight into how you approach challenges, integrate AI into your workflows, and apply your skills in a practical setting. We aim to make this process clear, collaborative, and reflective of the way we work as a team. DEI statement OLX values diversity and welcomes applicants of all races, ethnicities, disabilities, ages, genders, sexual orientations, religions, backgrounds, and experiences to apply. If this role excites you, we encourage you to apply, even if you don't meet all the requirements - you may be just the right fit for this or other opportunities with us.  Privacy Data disclaimer OLX will process your personal data to assess your fit for the applied position. You may optionally consent to store your data for up to 12 months after the application process for consideration in future OLX roles. For more details on how your application data will be processed please check our Privacy Statement.

Mayflower is a technology company focused on transforming the live entertainment industry by providing high-quality live streaming experiences. The Design System Designer role involves evolving and maintaining the design system across product and engineering teams. Responsibilities: — Evolve and maintain the existing UI foundation using Figma, Storybook, and code — Design and refine core UI components such as inputs, buttons, form elements, and patterns — Refine and extend a scalable token architecture (primitive → semantic → component) with theming support — Improve alignment between Figma, frontend implementation, and Storybook to ensure product consistency — Contribute to and improve the design-to-code workflow using Figma Variables, Tokens Studio, Style Dictionary, and CI/CD pipelines — Support migration of components toward a token-based structure, prioritizing impactful areas — Help shape and maintain contribution guidelines and system standards for design and engineering teams — Contribute to documentation and knowledge sharing to facilitate system understanding and usage — Explore and support AI-assisted workflows, including structured and machine-readable design system practices

Задачи: — построить единую платформу для работы AI-агентов в рамках кластера — от концепции до внедрения; — разработать инструменты наблюдаемости, оценки качества и проводить исследования, чтобы понимать, какие подходы, фреймворки и технологии работают в реальных сценариях; — внедрять архитектурные решения для ключевых инициатив в области GenAI, обеспечивая масштабируемость, надёжность и эффективность. Требования: — опыт разработки на Python/Go; — глубокое понимание ограничений LLM: контекстные окна, галлюцинации, задержки и стоимость — умение проектировать решения с учётом этих факторов; — опыт построения RAG-пайплайнов на realtime данных; — понимание архитектурных выборов: когда использовать harness, а когда — framework (Claude Code, Dify, n8n и др.), и как правильно подбирать модель под задачу; — умение считать token economics: оптимизировать маршрутизацию моделей, кешировать промпты, оценивать ROI on-prem решений; — проведение бенчмаркинга AI-агентов с помощью precision/recall, LLM-as-judge и A/B-тестов на production-данных; — автономное ведение квартальных проектов «под ключ» — от постановки цели до сдачи результата.

Location: Palo Alto, California, United States About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role As a Senior Machine Learning Engineer on the Applied AI team at Nebius Token Factory, you will own model and endpoint optimization from model artifacts through production deployment. Your work will span model internals, quantization and model compression, speculative decoding, KV-cache optimization, inference engines, serving architecture, and benchmarking to improve latency, throughput, memory efficiency, GPU utilization, and cost per token while preserving model quality and reliability. You will work with kernel and platform engineers to investigate serving problems, compare configurations, and resolve performance and quality regressions. You will evaluate model-and engine-level optimizations together with distributed inference designs, including request routing, scheduling, prefill/decode coordination, and multi-node GPU execution. Your improvements will be validated through reproducible benchmarks and safe production rollouts under real-world workloads. Your responsibilities : Own optimization projects for specific model families, customer endpoints, or serving backends. Compare inference engines and recommend practical serving configurations suited to individual workloads. Diagnose model-quality and performance regressions during production rollouts. Improve LLM and VLM endpoint latency, throughput, memory efficiency, GPU utilization, quality, and cost per token. Deploy, configure, benchmark, and extend inference engines such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, and NVIDIA Dynamo. Develop production model-compression workflows covering quantization, quantization-aware training, distillation, low-bit serving, and accuracy recovery. Implement or integrate speculative decoding, draft-model approaches, KV -cache optimization, prefix caching, chunked prefill, continuous batching, and disaggregated prefill/decode serving. For prefill/decode disaggregation (PDD), evaluate KV-cache transfer, worker placement, and capacity balancing to determine which workloads benefit from the architecture. Design and improve LLM request routers and scheduling policies that balance worker utilization queuing, request characteristics, and KV-cache locality while meeting latency and reliability targets Scale dense and mixture-of-experts inference across multiple GPU nodes. Select and tune tensor, pipeline, data, and expert parallelism - including wide expert parallelism (WideEP) - with attention to hardware topology, expert load balance, and communication overhead. Build reproducible benchmark harnesses measuring for TTFT , TPOT , tokens per second per GPU, p95/p99 latency, GPU memory, reliability, and cost per token. Validate architecture choices under representative traffic and consistent GPU budgets. Collaborate with GPU kernel engineers and platform engineers to trace bottlenecks across model code, kernels, runtime, scheduler, gateway, and cluster layers. Produce design documents, performance reports, rollout plans, and customer-facing technical explanations. Must-haves : Strong engineering skills in Python and PyTorch. Hands-on experience deploying or optimizing LLM, VLM , or high-throughput transformer inference. Practical knowledge of at least one modern inference stack, such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, NVIDIA Dynamo, Ray Serve, KServe, or an equivalent internal system. A strong understanding of transformer inference bottlenecks involving KV cache, attention, memory bandwidth, batching, parallelism, and long-context serving. Ability to quantify trade-offs among latency, throughput, quality, utilization, and cost. Experience designing or optimizing distributed inference system architecture, with hands-on work in one or more areas such as request routing, distributed scheduling, PDD, multi-node inference, or expert parallelism. Strong communication skills and collaboration skills across research, kernel, infrastructure, product, and customer teams. Nice - to - have s : Experience with quantization-aware training, post-training quantization, FP8 , INT8 , INT4 , NVFP4 , MXFP4 , AWQ , GPTQ , SmoothQuant. Experience with distillation, speculative decoding, EAGLE, Medusa, multi-token prediction, or related inference acceleration methods. Experience supporting agentic workloads involving including tool calling, structured outputs, streaming APIs, high concurrency, and multi-step orchestration. Familiarity with CUDA or Triton; the role does not require kernel engineering to be the candidate's primary specialization. Contributions to open-source projects such as vLLM, SGLang, TensorRT-LLM, FlashInfer, LMCache, PyTorch, Triton, Ray, or KServe. Implementation experience with cache-aware request routing, PDD, or WideEP, including diagnosing communication bottlenecks and load imbalance. Familiarity with GPU communication libraries and interconnects, such as NCCL, NVLink, Infiniband, or RoCE. Key employee benefits in the US: Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families. 401(k) plan: Up to 4% company match with immediate vesting. Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers. Remote work reimbursement: Up to $85/month for mobile and internet. Disability & life insurance : Company-paid short-term, long-term and life insurance coverage. #LI-BH3 Pay Transparency We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. Base Compensation Range $195,200 — $262,200 USD Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: Palo Alto, California, United States About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role Nebius Token Factory is looking for scientists who can turn frontier LLM and VLM inference bottlenecks into research questions, conduct rigorous experiments, and translate their findings into production capabilities. You will own focused research and optimization projects, write strong code, and produce prototypes, publications, and technical artifacts that engineers can build on. Your research will span quantization, distillation, speculative decoding, KV-cache optimization, and model/runtime co-optimization, alongside inference engines and distributed inference architectures. You will investigate how these approaches interact, evaluate their trade-offs across model quality, latency, throughput, memory footprint, and cost per token, and work with engineering teams to bring promising results into production. Your responsibilities : Lead research projects in efficient LLM and VLM inference, from hypotheses and experiments through ablations, prototypes, and production handoff. Develop and evaluate methods spanning quantization, quantization-aware training (QAT), distillation, speculative decoding, KV-cache reuse, KV-cache compression, long-context inference, MoE routing, and model/runtime co-optimization. Build prototypes using PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks, and collaborate with MLEs and platform engineers to turn them into production components. Research LLM request routing and scheduling strategies, including cache-aware load balancing and prefill–decode disaggregation (PDD). Evaluate how queueing, KV-cache transfer, worker placement, and prefill/decode capacity allocation affect latency, throughput, and serving cost. Investigate multi-node inference for dense and mixture-of-experts models, including wide expert parallelism (WideEP). Study expert placement, load imbalance, and computation/communication trade-offs, and use the findings to guide model and system architecture choices. Develop rigorous evaluations covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token. Compare serving architectures under consistent workload conditions and GPU budgets. Work with MLE, GPU kernel, backend infrastructure, product, and customer teams to select research priorities with measurable production impact. Share results through internal reports, technical blogs, papers, and open-source artifacts, and mentor engineers and scientists on experimental design, scientific rigor, and model/system trade-offs. Must-haves : A PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied mathematics, or a closely related discipline. A strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas. Strong Python and PyTorch implementation skills, with the ability to turn ideas into experiments and working prototypes. Deep knowledge of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving trade-offs. Strong experimental design skills covering ablations, baselines, metrics, statistical reasoning, and failure analysis. Excellent written and verbal communication. Nice - to - have s : First-author publications at venues such as NeurIPS, ICML, ICLR, MLSys, ACL, EMNLP, ASPLOS, OSDI, SOSP, ISCA, or HPCA. Experience deploying ML models or inference optimizations in production. Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA, or PyTorch internals. Experience applying post-training, SFT, DPO, RLHF, RLAIF, preference optimization, or synthetic data generation to inference quality or efficiency. Open-source research artifacts, widely used benchmarks, technical blogs, or invited talks demonstrating contributions to efficient AI systems. Research or implementation experience in one or more areas of distributed inference system architecture, such as LLM request routing, PDD, multi-node serving, or MoE expert parallelism, including WideEP. Key employee benefits in the US: Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families. 401(k) plan: Up to 4% company match with immediate vesting. Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers. Remote work reimbursement: Up to $85/month for mobile and internet. Disability & life insurance : Company-paid short-term, long-term and life insurance coverage. Pay Transparency We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. Base Compensation Range $195,200 — $262,200 USD Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: Palo Alto, California, United States About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role Nebius Token Factory is building an AI training and model post-training capability for frontier model improvement. This role owns the infrastructure that makes large-scale training and RL experiments possible, reliable, reproducible, and efficient. The work sits at the intersection of distributed systems, GPU performance, model training frameworks, RL pipelines, and production engineering. A Senior Machine Learning Engineer owns substantial ML work end to end. They can translate an ambiguous capability goal into concrete experiments, implement and debug training and RL recipes, build the supporting data and systems, and deliver measurable improvements in model quality, experiment throughput, and reliability. They are deeply hands-on and can independently debug both model-behavior failures and distributed training failures. Your responsibilities : Design and run model-training and post-training experiments, including SFT , continued pretraining, preference optimization ( DPO /IPO/ KTO ), and RL methods such as RLHF / RLAIF , PPO , and GRPO . Build reward functions, judge models, verifiers, task environments, and evaluation sets for reasoning, coding, tool use, and agentic workflows. Create synthetic data and data pipelines, including teacher-student generation, self-play, rejection sampling, filtering, and quality scoring. Analyze model-behavior failures and turn them into targeted data, reward, or algorithm improvements. Build and maintain distributed training and RL infrastructure using frameworks such as Megatron- LM , DeepSpeed, PyTorch FSDP /DTensor, Ray, verl, slime, AReaL, or OpenRLHF. Implement and debug parallelism strategies (tensor, pipeline, sequence/context, expert, and data parallelism) and build reliable rollout, reward-serving, checkpointing, and experiment-orchestration components. Profile and improve GPU utilization, memory usage, communication efficiency, training throughput, and inference/serving performance. Design rigorous evaluations and ablations for capability, instruction following, reasoning, tool use, safety, and regression risk. Write clear experiment plans, design docs, benchmark reports, and runbooks, and partner across research and platform teams. Must-haves : Strong Python and PyTorch engineering skills, with the ability to move quickly from idea to experiment to working system. Hands-on experience across at least two of: model training, post-training/ RL , applied modeling, data pipelines, or large-scale ML systems. Ability to design rigorous experiments with baselines, ablations, metrics, and failure analysis. Practical understanding of modern LLM behavior, instruction tuning, preference optimization, and evaluation challenges. Practical understanding of transformer training bottlenecks, memory pressure, communication overhead, and checkpointing. Ability to reason quantitatively about model quality, throughput, utilization, reliability, cost, and research velocity. Strong communication skills and ability to collaborate with researchers, engineers, and leadership. Nice - to - have s : Experience with LLM post-training, RL , agents, reward modeling, synthetic data, or model evaluation. Experience with RL frameworks or pipelines such as verl, slime, AReaL, OpenRLHF, TRL , or custom PPO / GRPO / RLHF systems. Experience with Megatron- LM , DeepSpeed, PyTorch FSDP /DTensor, Ray, Slurm, or Kubernetes on large GPU clusters. Familiarity with NCCL , CUDA , Triton, Nsight, InfiniBand/ RDMA , and H100/H200/B200 clusters, or with model serving and inference optimization. Publications, open-source contributions, or production impact in LLM post-training, RL , reasoning, coding models, synthetic data, distributed training, or evaluation. Experience designing agent environments, tool-use tasks, or verifier-based rewards. Key employee benefits in the US: Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families. 401(k) plan: Up to 4% company match with immediate vesting. Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers. Remote work reimbursement: Up to $85/month for mobile and internet. Disability & life insurance : Company-paid short-term, long-term and life insurance coverage. Pay Transparency We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. Base Compensation Range $195,200 — $262,200 USD Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: San Francisco Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW As the Engineering Manager for Model Infrastructure, you'll lead the team responsible for the platform powering every model request across Harvey. You'll partner closely with AI Research, Product Engineering, Infrastructure, and external AI providers to ensure our platform remains reliable, scalable, and cost-efficient as our business grows. Model Infrastructure is one of Harvey's most strategic engineering organizations. Every product capability—from chat experiences and agents to document workflows and future reasoning systems—depends on this platform. Over the next several years, the team will evolve beyond operating third-party models to building the infrastructure that enables Harvey to train, evaluate, deploy, and operate our own frontier AI models. This role offers the opportunity to shape the technical foundation of Harvey's AI platform and build an organization that will power the company's next phase of growth. WHAT YOU'LL DO - Lead and grow a high-performing team of software engineers responsible for Harvey's Model Infrastructure platform. - Define the technical roadmap for model reliability, scalability, and operational excellence. - Build highly reliable systems for model provisioning, capacity management, failover, and incident response across multiple AI providers. - Own Harvey's multi-provider model platform, including provider integrations, SDK upgrades, API migrations, and onboarding new model providers. - Drive the evolution of our Unified Model Controller (UMC) and Model Selector platform to automatically detect degraded models and intelligently route traffic based on health, latency, quality, compliance, and cost. - Improve observability through health dashboards, alerting, token usage analytics, cost reporting, and end-to-end model telemetry. - Partner with Product Engineering to support new model launches, capacity planning, experimentation, and proactive production monitoring. - Lead initiatives to improve inference efficiency, reduce infrastructure costs, and increase model utilization across providers. - Build the infrastructure foundation for Harvey's future model training efforts, including data pipelines, model operations, training environments, and AI platform capabilities. - Partner with executive leadership on long-term AI infrastructure strategy and vendor relationships. - Recruit, mentor, and develop exceptional engineering talent while fostering a culture of technical excellence and operational ownership. WHAT YOU HAVE - 8+ years of software engineering experience, including multiple years managing high-performing engineering teams. - Experience leading teams responsible for large-scale distributed systems or cloud infrastructure. - Strong technical background that enables you to guide architectural decisions and mentor senior engineers. - Experience operating highly available production services with strong reliability and operational excellence. - Experience building platforms that require scalability, observability, automation, and cost optimization. - Strong cross-functional leadership skills with the ability to partner effectively across Engineering, Research, Product, and external vendors. - Excellent communication skills and the ability to influence technical strategy across organizations. - A passion for building teams and developing engineering talent. NICE TO HAVE - Experience with AI infrastructure, LLM serving, or machine learning platforms. - Experience working with multiple model providers such as OpenAI, Anthropic, Azure OpenAI, Fireworks, Baseten, or open-source model ecosystems. - Experience building inference platforms, model gateways, traffic routing systems, or policy-based serving infrastructure. - Experience with Kubernetes, cloud infrastructure, distributed systems, and large-scale observability platforms. - Experience supporting GPU infrastructure, model training platforms, or ML infrastructure. - Familiarity with data platforms and technologies such as Spark, Kafka, Flink, Airflow, or Iceberg. - Experience leading organizations through periods of rapid growth and technical transformation. COMPENSATION $260,000 - $350,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-AN2 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: Remote: United States Workplace: Remote At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure. Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users. Our platform is trusted by over 7 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $260M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development. We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you. APPLYING TO RENDER We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team. We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed. Our interview process is unique to each role, and we value the candidate experience just as much as our customer experience. We hope your conversations with us reflect a thoughtful process that is illuminative, enjoyable, and respectful of your time. We're looking for a Staff Product Manager to own the vision and roadmap for observability at Render. The role spans both the systems layer and the fast-emerging world of agent observability. This is a role for someone who wants to define what it means to understand your software in an era where AI is fundamentally changing how it gets built and run: where a production incident might trace through services, queues, model calls, and autonomous agent decisions, and where cost is measured in tokens as much as CPU-hours. This is a new specialization at Render, and you will own the visibility layer for AI workloads and drive the technical and strategic direction for Render's observability surface, including logs, metrics, traces, and the OpenTelemetry ecosystem. You'll engage with Render's customers and our product development teams to develop a deep understanding of how they debug, monitor, and manage spend, and build conviction about where observability needs to go next. WHAT YOU'LL DO - Own the vision, strategy, and roadmap for observability at Render. Your scope spans systems telemetry (logs, metrics, distributed tracing), OpenTelemetry-native instrumentation and export, agent and LLM observability (traces of model calls, tool use, and multi-step agent runs), and the cost and usage layer that makes token economics legible. - Drive prioritization across observability investments, balancing foundational telemetry infrastructure against near-term product needs. - Partner deeply with Engineering & other Product teams to shape the technical direction of Render's telemetry pipeline, ensuring architectural decisions optimize for signal fidelity, query performance, and cost at scale. Observability touches every product surface at Render, so the dexterity to understand the shape of our other investment areas is essential. - Develop a strong, opinionated point of view on what observability means for AI-native builders. How will OTel conventions extend to agent workloads, what a trace of an agent run could look like inside Render, and how teams should reason about token spend, model routing, and cost attribution. WE'RE LOOKING FOR - 7+ years in Product Management, with substantive experience in observability, monitoring, developer tools, or infrastructure products. - Working fluency with the OpenTelemetry ecosystem — signals, semantic conventions, collectors, and the tradeoffs of instrumenting real production systems. Bonus if you've tracked the emerging conventions for GenAI and agent observability. - Familiarity with the economics of AI workloads: token pricing, model selection tradeoffs, and how teams budget for and attribute LLM spend. Major bonus if you've worked on an LLM gateway, proxy, or metering product. - Deep developer empathy, for both internal engineering teams and our customers, and the technical depth to make sound architectural tradeoffs in collaboration with engineering. - A track record of taking ambiguous, cross-cutting problems and turning them into clear strategy and shipped outcomes. - Strong communication and storytelling skills. WHAT WOULD BE NICE TO HAVE BUT NOT REQUIRED - Experience as an SRE, observability engineer, or infrastructure engineer. - Hands-on experience building AI agents, or instrumenting and evaluating them in production. - Contributions to OpenTelemetry or adjacent open-source telemetry projects. If this role excites you but you don't meet every single requirement or your experience is in an adjacent role such as engineering management, we'd still love to hear from you. Your unique experience might be just what we need. If this role excites you but you don’t meet every single requirement, we’d still love to hear from you—your unique experience might be just what we need. BENEFITS - 4 weeks of paid vacation. - 14 weeks of fully paid parental leave for all parents to bond with a newly born, adopted, or fostered child. We will also work with you to create a supportive plan of return. - Long-term disability, life insurance, and 401K plans. - 100% employer-paid medical coverage and 99% employer-paid dental and vision coverage for you and a dependent. FSAs and HSAs are available as well. - Monthly lifestyle stipend for wellness, mental health and therapy, hobbies, etc. - Monthly cell phone and internet subsidy. - Commuter benefits for Renders in the Bay Area, and home office stipends for remote Renders. - Continuous learning benefits & related support. This position is generally not eligible for new visa sponsorship. At Render's discretion, the business may sponsor existing visa transfers. Applicants who require sponsorship must receive business authorization. Render is an equal-opportunity employer. We know that employing a team rich in diverse thoughts, experiences, and opinions allows our employees, product, and community to flourish. We make all employment decisions including hiring, evaluation, termination, promotional, and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. We encourage all who are interested to apply. We can't wait to hear from you! Render — CCPA Applicant Privacy Notice https://drive.google.com/file/d/1wKr9IejoT5McFrs9I2mahQnf6AFwb3z2/view Render — GDPR Applicant Privacy Notice https://drive.google.com/file/d/1_8jtyXQ1HdRdTdQn9sZ7n-R-zAGBmsFa/view

Location: Remote - London MinIO is the data and memory foundation for enterprise AI. Built for the speed, scale, and economics that AI and analytics demand, AIStor and MemKV unify every layer of the data stack, from agentic and inference context memory to tables and objects across core, edge, and cloud. Trusted by 77% of the Fortune 100, MinIO is redefining how AI factories, intelligent applications, and autonomous agents secure, persist, and unlock the full value of their data. The European cloud landscape is undergoing a massive structural shift. Specialized GPU cloud providers, alternative infrastructure platforms, and sovereign cloud consortiums—collectively known as NeoClouds —are scaling exponentially to fuel the generational demand for enterprise AI/ML training and inference. As an Account Executive for the NeoCloud market in Europe, you will own MinIO’s commercial footprint across this hyper-growth sector. This role is open as a remote role in any Major European AI Hub for a qualified candidate. You will be selling a revolutionary AI data infrastructure portfolio, headlined by: MinIO AIStor: Our exascale AI data store purpose-built for massive concurrency, sub-10ms latency, and high-throughput training pipelines. MinIO MemKV: Our purpose-built context memory store that eliminates the inference "recompute tax" by turning NVMe flash into a shared memory tier that GPU pods access at microsecond speeds over RDMA. Why this role matters: AI infrastructure cannot achieve true efficiency using legacy storage frameworks. By positioning MinIO at the foundation of European NeoClouds, you will directly enable cloud providers to maximize GPU utilization (95%+), collapse time-to-first-token latencies from seconds to milliseconds, and drastically lower operational costs for their enterprise tenants. What You Will Do Drive Revenue & Market Share: Execute a strategic enterprise sales motion to identify, sign, and expand high-value commercial partnerships with European NeoClouds, specialized AI hosters, and sovereign cloud providers. Value-Based Portfolio Positioning: Lead complex technical and business conversations illustrating how MinIO products meet current and future requirements. Full Sales Lifecycle Management: Actively manage the end-to-end sales pipeline, from prospecting and initial technical qualification to executive alignment, pilot orchestration, pricing architecture, and contract closure. Cross-Functional Alignment: Collaborate closely with MinIO Solution Architects, Product Engineering, and corporate leadership to handle demanding infrastructure environments involving S3 over RDMA, PCIe Gen6, and NVIDIA reference architectures (e.g., Spectrum-X Ethernet, BlueField-4 STX). Ecosystem Amplification: Leverage alliances with key physical hardware and networking providers (e.g., NVIDIA, regional data center developers) to position MinIO as the foundational storage choice for modern AI deployment blueprints. Your Skills and Experience Proven Infrastructure Sales Record: 10+ years of quota-carrying enterprise software sales experience, with a documented history of successfully selling to cloud service providers (CSPs), telcos, managed services providers (MSPs), or high-performance computing (HPC) hubs. Familiarity with NVIDIA ecosystem:  AI Factory architecture and experience selling with NVIDIA field teams is a huge plus. Deep AI/ML Infrastructure Literacy: Fluency in the mechanics of modern AI infrastructure stacks. You can confidently discuss GPUs, Kubernetes operators, high-speed networking fabrics (RDMA/InfiniBand), KV Cache eviction challenges in LLMs, and modern data platforms like Apache Iceberg. Strategic Deal Architect: Proven ability to navigate complex, multi-layered corporate accounts, building deep trust with everyone from infrastructure engineers to executive decision-makers (CTOs, CEOs, Heads of AI Infrastructure). European Landscape Expertise: Strong understanding of regional dynamics within European tech markets (UK, DACH, France, Benelux, Nordics) and the data sovereignty requirements reshaping the continent's infrastructure policies. Entrepreneurial Engine: A proactive, self-motivated operator who thrives in high-velocity, high-innovation spaces and enjoys building a market segment from the ground up. Equal Opportunity Policy (EEO) MinIO is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.

Location: Brussels, Belgium Workplace: remote Join Tether and Shape the Future of Digital Finance At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction. Innovate with Tether Tether Finance: Our innovative product suite features the world’s most trusted stablecoin, USDT , relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services. But that’s just the beginning: Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities. Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET , our flagship app that redefines secure and private data sharing. Tether Education : Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity. Tether Evolution : At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways. Why Join Us? Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry. If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you. Are you ready to be part of the future? About the job As part of the Technology Distribution team of Tether Data, we are seeking an Engagement Manager to lead the implementation of AI-driven initiatives powered by QVAC, Tether’s SDK for local AI and delegated inference. The role focuses on orchestrating complex, multi-stakeholder deployments of decentralized AI solutions across enterprise, government, and institutional environments. This position combines client engagement, technical coordination, and delivery oversight to ensure successful onboarding and execution of AI use cases, ranging from edge AI deployments to privacy-preserving inference systems. The Engagement Manager plays a central role in aligning client objectives with product capabilities, coordinating internal and external stakeholders, and driving implementations from initial scoping through production rollout. Responsibilities Client & Partner Engagement Act as the primary point of contact for clients and partners during AI implementation initiatives, ensuring clear communication, expectation alignment, and structured execution. Guide clients in translating business requirements into AI deployment strategies leveraging QVAC capabilities (local inference, delegated compute, privacy-preserving architectures). Support Expansion team in shaping AI-related opportunities by providing input on feasibility, integration complexity, and delivery approach. Identify opportunities to extend implementations across additional use cases, geographies, or Tether technologies. Implementations Oversight Lead end-to-end coordination of QVAC-based implementations from kickoff through production deployment. Define implementation roadmaps, milestones, and dependencies across AI models, infrastructure, and integration layers. Ensure alignment between client expectations and actual product capabilities, avoiding scope drift or mispositioning. Track progress across multiple concurrent AI deployments, ensuring timely delivery and readiness for production environments. Cross-functional Coordination Coordinate closely with product, engineering, and research teams to align on QVAC capabilities, limitations, and roadmap evolution. Facilitate integration between client systems and QVAC components, including model deployment pipelines, APIs, and compute environments. Work with legal and compliance teams where required, particularly in sensitive AI deployments involving data locality or privacy constraints. Maintain structured communication flows across all stakeholders involved in the implementation lifecycle. Governance & Reporting Establish and maintain governance frameworks including implementation plans, risk tracking, and decision logs. Produce executive-level updates summarizing progress, risks, blockers, and next steps. Ensure documentation of implementation architectures, deployment patterns, and key learnings for reuse across future projects. Support escalation management and ensure timely resolution of technical or operational challenges. Core Experience 5+ years of experience in program management, technical account management, or delivery roles within AI, data infrastructure, or complex technology environments. Proven experience managing cross-functional implementations involving multiple stakeholders (internal teams, clients, external partners). Strong ability to operate at the intersection of technical and business domains. Technical Understanding Familiarity with AI/ML deployment concepts, including model inference, edge/local AI, and distributed compute architectures. Understanding of APIs, SDK integrations, and system architecture patterns. Ability to engage in technical discussions with engineering teams while maintaining business-level clarity with clients. Communication & Execution Strong communication and stakeholder management skills, including experience working with enterprise or government entities. Structured approach to project tracking, documentation, and governance. Ability to manage ambiguity and operate in fast-evolving, early-stage environments. Nice to Have Experience with decentralized technologies, blockchain, or privacy-preserving systems. Exposure to AI infrastructure tooling or MLOps workflows. Experience in regulated industries or public sector projects. Basic familiarity with programming or scripting environments (Python, APIs, CLI tools). Important information for candidates Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles: Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/ Verify the recruiter’s identity. All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website. Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms. Double-check email addresses. All communication from us will come from emails ending in @ tether.to or @ tether.io We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately. When in doubt, feel free to reach out through our official website.

Location: Paris, France Workplace: remote Join Tether and Shape the Future of Digital Finance At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction. Innovate with Tether Tether Finance: Our innovative product suite features the world’s most trusted stablecoin, USDT , relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services. But that’s just the beginning: Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities. Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET , our flagship app that redefines secure and private data sharing. Tether Education : Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity. Tether Evolution : At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways. Why Join Us? Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry. If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you. Are you ready to be part of the future? About the job As part of the Technology Distribution team of Tether Data, we are seeking an Engagement Manager to lead the implementation of AI-driven initiatives powered by QVAC, Tether’s SDK for local AI and delegated inference. The role focuses on orchestrating complex, multi-stakeholder deployments of decentralized AI solutions across enterprise, government, and institutional environments. This position combines client engagement, technical coordination, and delivery oversight to ensure successful onboarding and execution of AI use cases, ranging from edge AI deployments to privacy-preserving inference systems. The Engagement Manager plays a central role in aligning client objectives with product capabilities, coordinating internal and external stakeholders, and driving implementations from initial scoping through production rollout. Responsibilities Client & Partner Engagement Act as the primary point of contact for clients and partners during AI implementation initiatives, ensuring clear communication, expectation alignment, and structured execution. Guide clients in translating business requirements into AI deployment strategies leveraging QVAC capabilities (local inference, delegated compute, privacy-preserving architectures). Support Expansion team in shaping AI-related opportunities by providing input on feasibility, integration complexity, and delivery approach. Identify opportunities to extend implementations across additional use cases, geographies, or Tether technologies. Implementations Oversight Lead end-to-end coordination of QVAC-based implementations from kickoff through production deployment. Define implementation roadmaps, milestones, and dependencies across AI models, infrastructure, and integration layers. Ensure alignment between client expectations and actual product capabilities, avoiding scope drift or mispositioning. Track progress across multiple concurrent AI deployments, ensuring timely delivery and readiness for production environments. Cross-functional Coordination Coordinate closely with product, engineering, and research teams to align on QVAC capabilities, limitations, and roadmap evolution. Facilitate integration between client systems and QVAC components, including model deployment pipelines, APIs, and compute environments. Work with legal and compliance teams where required, particularly in sensitive AI deployments involving data locality or privacy constraints. Maintain structured communication flows across all stakeholders involved in the implementation lifecycle. Governance & Reporting Establish and maintain governance frameworks including implementation plans, risk tracking, and decision logs. Produce executive-level updates summarizing progress, risks, blockers, and next steps. Ensure documentation of implementation architectures, deployment patterns, and key learnings for reuse across future projects. Support escalation management and ensure timely resolution of technical or operational challenges. Core Experience 5+ years of experience in program management, technical account management, or delivery roles within AI, data infrastructure, or complex technology environments. Proven experience managing cross-functional implementations involving multiple stakeholders (internal teams, clients, external partners). Strong ability to operate at the intersection of technical and business domains. Technical Understanding Familiarity with AI/ML deployment concepts, including model inference, edge/local AI, and distributed compute architectures. Understanding of APIs, SDK integrations, and system architecture patterns. Ability to engage in technical discussions with engineering teams while maintaining business-level clarity with clients. Communication & Execution Strong communication and stakeholder management skills, including experience working with enterprise or government entities. Structured approach to project tracking, documentation, and governance. Ability to manage ambiguity and operate in fast-evolving, early-stage environments. Nice to Have Experience with decentralized technologies, blockchain, or privacy-preserving systems. Exposure to AI infrastructure tooling or MLOps workflows. Experience in regulated industries or public sector projects. Basic familiarity with programming or scripting environments (Python, APIs, CLI tools). Important information for candidates Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles: Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/ Verify the recruiter’s identity. All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website. Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms. Double-check email addresses. All communication from us will come from emails ending in @ tether.to or @ tether.io We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately. When in doubt, feel free to reach out through our official website.