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Location: United States Workplace: Remote At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 JOB SUMMARY   As a Business Systems Engineer on the GTM Engineering team, you will design, build, and operate the automation and AI systems that power ClickUp's Go-To-Market business — spanning core business products and the integration platforms that connect them. This role is AI-native at its core: you won't just maintain existing workflows, you'll actively advance our GTM systems with intelligent agents, LLM-powered automations, and next-generation integration patterns built on MCP, ClickUp Super Agents, and modern iPaaS tooling.   You'll sit at the intersection of business systems architecture and applied AI — partnering with Sales, Finance, Revenue Operations, and fellow GTM Systems engineers to eliminate toil, accelerate revenue workflows, and build the automated, AI-augmented infrastructure the company runs on. This is a hands-on engineering role for someone deeply fluent in enterprise business systems, excited about deploying production AI, and committed to genuine ownership of the platforms they build — directly supporting GTMSOE's broader mission of operational excellence across the GTM org.   KEY RESPONSIBILITIES   AI-NATIVE AUTOMATION & AGENT DEVELOPMENT   - Design and build AI-powered automations and agentic workflows across the GTM tech stack — including Salesforce, NetSuite, Workato, and MuleSoft — to eliminate manual effort and accelerate business operations. - Develop and deploy ClickUp Super Agents and LLM-based automations to automate tasks such as deal data enrichment, quote generation assistance, order validation, revenue recognition triggers, and exception handling in quote-to-cash workflows. - Architect and implement MCP (Model Context Protocol) integrations that allow AI agents to interact with business systems contextually and safely — enabling intelligent, event-driven actions across the GTM platform. - Explore and evaluate emerging AI capabilities (RAG, fine-tuning, multi-agent orchestration) and determine which are production-ready for GTM business systems use cases. - Build reusable AI templates, automation patterns, and agent blueprints that can be extended across the GTM Engineering team.   BUSINESS SYSTEMS INTEGRATION & ARCHITECTURE   - Build and maintain integrations across Salesforce, NetSuite, Workato, MuleSoft, DealHub (CPQ), and other GTM platforms — with a strong bias toward clean architecture, low technical debt, and supportable design. - Own end-to-end integration patterns for critical business flows such as lead-to-opportunity, quote-to-cash, order-to-fulfillment, and revenue reporting pipelines. - Design data flows and transformation logic that keep business data accurate, consistent, and accessible across systems without creating fragile point-to-point dependencies. - Apply a build-vs-buy mindset: evaluate whether a given automation need is best solved with native platform capabilities, iPaaS tooling, or custom code — and make the case clearly.   PLATFORM DEVELOPMENT & TOOLING   - Build internal tooling, low-code/no-code solutions, and lightweight applications using platforms such as Retool, Replit, or similar to extend business systems capabilities with minimal overhead. - Write automation scripts and data transformation logic in Python, JavaScript, or Apex as needed to bridge gaps that platform tooling cannot address natively. - Utilize Zapier, Workato, and similar iPaaS platforms to orchestrate cross-system workflows that are maintainable, observable, and well-documented. - Own the full lifecycle of what you build: discovery, design, development, testing, deployment, documentation, and ongoing optimization.   RELIABILITY, OBSERVABILITY & CONTINUOUS IMPROVEMENT   - Monitor the health and performance of automations and integrations you own; proactively identify degradation, data inconsistencies, or failure patterns before they impact business operations. - Conduct root-cause analysis of integration failures or automation breakdowns and drive durable fixes — not just incident patches. - Maintain runbooks and operational documentation so that platform behavior is understandable and recoverable by the broader team. - Gather feedback from business stakeholders and iterate on existing automations to improve accuracy, reduce edge cases, and adapt to evolving GTM processes.   CROSS-FUNCTIONAL COLLABORATION & STAKEHOLDER ENGAGEMENT   - Partner with Sales, Revenue Operations, Finance, and Customer Success stakeholders to translate business requirements into well-scoped technical solutions. - Work closely with GTM Systems Engineering, DevOps, and BSA teammates on architecture decisions, intake prioritization, and delivery execution. - Contribute to the GTM Systems Engineering operating model: maintain task hygiene, communicate proactively on large initiatives, and log AI/automation work in the team's AI Excellence registry. - Serve as a subject matter expert for business systems automation and AI — educating stakeholders on what's possible and setting realistic expectations on scope and delivery.   QUALIFICATIONS   EXPERIENCE   - 3–5+ years in a business systems engineering, systems administration, or integration engineering role. - Demonstrated experience building and shipping automations or integrations that delivered measurable business value in production environments. - Hands-on experience with Salesforce and at least one ERP platform (NetSuite strongly preferred). - Experience deploying AI or LLM-powered automations in a production business systems context — or a clear, demonstrated trajectory toward it. - Experience working in a high-velocity environment where you manage multiple concurrent priorities and adapt quickly to changing business needs. - Optional but valued: experience with DealHub (CPQ), ClickUp, quote-to-cash workflows, or revenue operations systems.   SKILLS & COMPETENCIES   Technical   - Salesforce configuration, automation (Flow, Process Builder), Apex, and data model design — admin or developer-level proficiency required. - NetSuite workflows, SuiteScript, SuiteBundler, saved searches, and data model — particularly as it relates to order management, billing, and revenue recognition. - Hands-on experience with Workato, MuleSoft, Zapier, or comparable iPaaS platforms — including multi-step flows, error handling, and observability. - Practical experience with LLM APIs (OpenAI, Claude, etc.), prompt engineering, agentic workflow design, and MCP integrations. Experience with ClickUp Super Agents is a strong plus. - Proficient with Python, JavaScript, or Apex for automation scripting and data transformation; comfortable with REST APIs, webhooks, JSON, and OAuth-based integrations. - Strong understanding of business systems data models and integration patterns (event-driven, batch, real-time).   Operational & Mindset   - Ownership: You take full responsibility for the systems you build — from reliability and documentation to stakeholder trust and continuous improvement. You don't hand off and walk away. - Velocity: You move fast, iterate, and ship. You know when "good enough and deployed" beats "perfect and blocked," and you never sacrifice reliability or data integrity to get there. - AI & Automation mindset: You default to asking "how can an agent or LLM handle this?" before reaching for a manual workflow — experimenting confidently and evaluating critically. - Collaboration: You bridge the gap between technical architecture and business impact, asking clarifying questions, challenging assumptions respectfully, and earning trust with the stakeholders you support. - Growth: You stay current on emerging AI capabilities, evaluate what's production-ready, and continuously raise the bar on what GTM systems can do.   WHAT YOU'LL WORK WITH   - Salesforce: CRM platform — automations, Flow, Apex, data model, reporting, and CPQ/OTC integrations. - NetSuite: ERP platform — SuiteScript, workflows, order management, billing, and revenue recognition flows. - ClickUp Super Agents: AI-powered automation and agentic task orchestration within the ClickUp ecosystem. - Integration stack: Workato, MuleSoft, Zapier — recipe/flow development, cross-system orchestration, and platform observability. - AI & MCP tooling: LLM APIs, Model Context Protocol (MCP), agentic workflow design, and production AI integration patterns. - Low-code tooling: Retool, Replit, or similar for internal applications and workflow extensions. - Scripting & APIs: Python, JavaScript, Apex, REST/webhook integrations, and JSON-based data transformation. Equal Opportunity Employer ClickUp is an Equal Opportunity Employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin. Privacy Notice ClickUp collects and processes personal data in accordance with applicable data protection laws. You can find further details by viewing our Global Candidate Privacy Notice. https://clickup.com/careers-terms/candidate-privacy-notice If you are a Philippine Job Applicant, please also see our Philippine Data Privacy Notice https://t333.s.clickup-attachments-stg.com/t333/d9a53ce2-6d2c-48cd-84b1-ed4e525f9613/Philippine%20Data%20Privacy%20Notice_2024.pdf?view=open for further details. Visa Sponsorship Please note we are unable to sponsor or take over sponsorship of an employment visa for roles outside of engineering and product at this time. Sponsorship for engineering and product roles is not guaranteed, but is instead based on the business needs for that specific role at that time. Please reach out to the recruiter with any questions. Fraud Alert ClickUp Talent Acquisition will only initiate contact via an @clickup.com http://clickup.com email or through our official careers portal on clickup.com http://clickup.com. We will never request fees, payments, or sensitive personal information. Please disregard any offers received outside these channels and report them to support@clickup.com. AI Processing Notice ClickUp may use artificial intelligence and machine learning technologies to help review and screen candidates' employment applications against role-related criteria. These tools support, but do not replace, human decision‑making. If you have questions or need an accommodation in the recruitment process, please contact us at AskPeople@ClickUp.com.

Location: Amsterdam, Netherlands; Germany; United Kingdom 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 We're looking for a Senior Software Engineer to help us build the best Managed PostgreSQL for AI workloads. The service is already in production; the mission now is to make it the obvious choice for teams running AI applications on Postgres — first-class vector search, painless migrations from RDS / Cloud SQL / self-managed clusters, and the operational quality of a mature managed database. You'll work across the stack: control plane and lifecycle automation in Go, Postgres internals and performance, migration tooling, and the customer escalations where it actually matters. You're welcome to work from our offices in Amsterdam or London, hybrid or remotely from EU timezones. Your responsibilities : Develop the control plane and lifecycle automation for Managed PostgreSQL — provisioning, HA, failover, backups, PITR, version upgrades, zero-downtime maintenance. Tune and harden PostgreSQL itself — replication, WAL, vacuum, query planner, connection pooling, extensions — and turn that into product features and sane defaults customers don't have to think about. Build migration tooling that gets customers off AWS RDS, Google Cloud SQL, Azure Database for PostgreSQL, and self-managed clusters with minimal downtime. Drive the AI-Postgres story end to end — vector search (pgvector, pgvectorscale), hybrid retrieval, integration with the wider Nebius AI Cloud stack. Run the service like an SRE — define SLOs, build observability, lead incident response, feed every postmortem back into the platform. Work directly with customers on architecture reviews, performance escalations, and the production problems that don't fit a ticket template. Must-haves : 5+ years of professional software engineering experience, with significant time spent building or operating production PostgreSQL at scale (TB+ datasets, replication topologies, real failure modes you've debugged in production). Strong software engineering skills in Go or another backend/systems language, with a willingness to work primarily in Go. Deep knowledge of PostgreSQL internals: MVCC, WAL, replication (physical and logical), vacuum, query planning, extensions, partitioning. Hands-on experience with the surrounding ecosystem: Patroni / Stolon / pg_auto_failover, pgBackRest / WAL-G, pgBouncer / PgCat, logical replication tooling. The instincts of an ex-DBA — you can read EXPLAIN ANALYZE fluently, reason about lock behaviour, and know how to handle database corruptions. Ability to write reliable code and dig into complex problems. Teamwork-oriented approach. Nice - to - have s : Experience with pgvector and pgvectorscale — vector search at scale, index choice, recall vs. latency trade-offs. Background building managed-database control planes at a cloud provider (RDS, Cloud SQL, Aiven, Crunchy, Timescale, Supabase, Neon, or similar). Experience writing Kubernetes operators (Go + controller-runtime / kubebuilder). Contributions to PostgreSQL itself, popular extensions, or the surrounding OSS ecosystem. AI/ML workload experience — RAG pipelines, embedding stores, GPU-resident workloads. We conduct coding interviews as part of the process. 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: Hong Kong, Hong Kong SAR; Singapore, Singapore 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 team The Finance Data Team is responsible for the data infrastructure that powers OKX's compliance, regulatory, and financial reporting operations globally. Our Finance Data domain covers everything from raw transaction ingestion to consolidated group financials — supporting statutory reporting, board-level financials, and audit readiness across 100+ markets. This is a team that treats data correctness as a non-negotiable. We operate at the intersection of engineering rigour, financial domain knowledge, and regulatory accountability. About the role We are looking for a Staff Data Engineer to be the technical anchor for Finance Data at OKX. You will define how Finance data is architected, validated, and delivered, and set the standard for how the team operates in an AI-native way. You will work directly with Finance, Accounting, and Treasury stakeholders to ensure that financial data is complete, reconciled, traceable, and audit-ready. You will also be the domain's primary escalation point and the technical voice of Finance Data within the broader engineering organisation. This role suits someone who has operated as a de facto domain lead before — someone who has built financial data systems that have been reviewed by auditors, regulators and who knows what "good" looks like in a regulated financial data environment. Responsibilities: Domain Architecture & Technical Direction Own the end-to-end Finance data architecture: from ODS ingestion through CDM transformation to reporting mart, with clear data lineage documented at every layer Define and enforce data modelling standards for Finance: period cut-off immutability, multi-entity consolidation logic, revenue recognition alignment, and audit trail completeness Lead the design of scalable pipelines supporting trading data, asset positions, P&L, and cost accounting across multiple legal entities and jurisdictions (SG, EU, US, and others) Make architectural decisions independently and articulate trade-offs clearly to both engineering peers and non-technical Finance stakeholders Financial Reporting & Audit Readiness Partner with Accounting, Finance PMO, and Treasury to deliver datasets for month-end close, statutory reporting, and board-level financials on time and to audit standard Ensure every financial figure is traceable back to the source system with full transformation history — no black boxes Build the data foundation that supports OKX's regulatory reporting obligations and long-term financial reporting maturity Data Quality & Controls Design proactive, self-validating DQC frameworks — reconciliation logic, SLA monitoring, and anomaly detection built into pipelines, not bolted on after incidents Own incident response for Finance-critical pipeline failures; conduct structured post-mortems and drive permanent fixes Define "done" for financial correctness in partnership with Accounting; hold the line on data quality standards even under delivery pressure AI-Native Finance Data Lead the team's adoption of AI-assisted engineering: LLM-assisted development, automated anomaly detection, intelligent reconciliation, AI-generated reporting summaries Evaluate and introduce AI tooling into Finance data workflows with production evidence — not POC demos Set the bar for what an AI-native Finance data team looks like, and bring junior engineers along Technical Leadership & Influence Be the go-to escalation point for Finance data domain questions across the team Mentor and grow engineers working in the Finance domain; translate domain complexity into learnable patterns Represent Finance Data in cross-team architecture discussions, sprint planning, and stakeholder reviews Document domain knowledge that outlasts any individual — data dictionaries, pipeline specs, onboarding guides Requirements: 6+ years in data engineering, with at least 3 years owning a Finance, Accounting, or financial reporting data domain end-to-end Deep understanding of financial data fundamentals: period close and cut-off rules, revenue recognition, multi-entity consolidation, reconciliation, and audit trail requirements Demonstrated experience building data systems that have been reviewed in a statutory audit or regulatory review Strong SQL and Python; proven ability to design and maintain complex production pipelines at scale Experience designing for immutability and lineage — financial data that can be rolled back, re-run, and traced without manual intervention Track record of operating with significant autonomy: defining requirements from ambiguous stakeholder input, not just executing tickets Preferred Qualifications: Experience at a crypto exchange, fintech, or company that has gone through IPO preparation or public company financial reporting Familiarity with regulatory reporting requirements across multiple jurisdictions (MAS SG, SEC, FCA, or equivalent) AI/ LLM tooling applied to data engineering workflows in production — concrete examples required; "exploring" does not count Experience with Spark, Airflow, or equivalent orchestration at scale Prior experience as a de facto domain lead or tech lead without formal people management title Background working with Accounting/Controllership teams as a technical counterpart 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: Auckland Workplace: OnSite ABOUT HALTER At Halter, we’re on a mission to enable farmers and graziers to run the most productive and sustainable operations. Our customers are using Halter to break free from the time-intensive constraints of conventional practices. Imagine watching 500 cattle stand up and walk calmly towards their next break? No quad bikes, no dogs, no fences. Just a group of cattle walking at their own pace. People say it looks like magic. Our customers are revolutionizing grazing with Halter. It's changing lives and transforming an industry. People join Halter to do meaningful work. By joining us you’ll be solving challenging problems within a talented team and a culture built for high performance. Our team out-think, out-work and out-care. We’re committed to delivering real change in the world - this isn’t easy, and in truth, we love that it’s hard. We’re backed to deliver on a mission that matters by Tier 1 investors including Founders Fund https://foundersfund.com, Bessemer Venture Partners https://www.bvp.com/, BOND, https://www.bondcap.com/ DCVC https://www.dcvc.com/, Blackbird https://www.blackbird.vc/, Promus Ventures https://www.promusventures.com/, Rocket Lab’s Peter Beck and Icehouse ventures https://www.icehouseventures.co.nz/?utm_term=icehouse%20ventures&utm_campaign=Brand+Keywords&utm_source=adwords&utm_medium=ppc&hsa_acc=4064636360&hsa_cam=16902737884&hsa_grp=134004309485&hsa_ad=592971340272&hsa_src=g&hsa_tgt=kwd-1082530126230&hsa_kw=icehouse%20ventures&hsa_mt=b&hsa_net=adwords&hsa_ver=3&gclid=Cj0KCQjw2v-gBhC1ARIsAOQdKY0J0DepRVFDmjQlAkJPbZuQnLSA5UVzUzOXYiPxkjX-SeVa513_BhkaAr-MEALw_wcB. To find out more, visit our LinkedIn https://www.linkedin.com/company/halter-limited & Instagram https://www.instagram.com/lifeathalter/. ABOUT THE ROLE Halter is searching for a Lead Supply Quality Engineer to take responsibility for ensuring that every component in our supply chain is delivered at quality and on time. If you are an expert in implementing and managing quality systems to catch issues early, resolve them quickly, and ensure high-quality components are always delivered on-time at our Contract Manufacturers, we want to talk to you! Our Hardware manufacturing is accelerating quickly to satisfy our growing global markets and it is vital that every component that is shipped to our contract manufacturers in Asia is ready for the tough environment it will face on farm, once it is assembled into Halter hardware. WHAT YOUR DAY COULD LOOK LIKE - Implement statistical process control methods for the manufacturing process of critical parts and work with the suppliers to ensure this is reflected in their process control plan - After a failure during production or OQC inspection at a supplier, run a rapid sprint analysis with design engineers to unblock the release of the shipment with risk-mitigative actions and keep production running with effective preventive measures - Update and implement quality control documentation to protect against future failures, based on root cause analysis that identified a component issue after, first flagged when a collar went offline on a farm in Australia - Audit the compliance with Halter’s quality requirements at a new supplier and work with the supplier to quickly close any non-conformances you found - Frequent travel between Auckland HQ (where you will be based) and China   WHAT WE ARE LOOKING FOR - 5+ years of experience in quality management for high-volume manufacturing. Production of electromechanical products is preferred - Committed to personal development and staying current with relevant industry standards, methods, and trends - Proven experience in responding to and resolving quality issues rapidly to minimise production disruption - Demonstrated first principles thinking and ability to hone in on the most important issues during audit or reviewing problems - Experience in working with suppliers to achieve required outcomes based on context - High proficiency (written, verbal and reading) in English and Mandarin (preferred) - Relevant quality-related qualifications such as ASQ certification (for example CQE or CQA) are beneficial, as is formal Internal Auditor Certification - Willing to travel regularly to China (50%+ of your time) - Someone who will thrive in a close team environment and can work well in the self-directed and demanding environment of a rapidly scaling company - A commitment to personal development and staying current with relevant industry standards, methods, and trends.   JOIN OUR TEAM Halter is committed to promoting a diverse and inclusive workplace — a place where we can each be ourselves and do the best work of our lives. Research shows that while men apply to jobs when they meet an average of 60% of the requirements, women and under-represented groups of candidates tend to only apply when they meet every requirement. If you think you have what it takes but don’t necessarily tick every requirement on this job description, please still get in touch and apply to Halter. We’d love to chat to see if you’ll be an epic fit! If this opportunity sounds like you, please apply below by sending through your cover letter explaining why you’re excited about this role and working at Halter, along with your CV, and we’ll be in touch! Please also feel free to check out the careers page https://www.halterhq.com/careers for more information on working at Halter and don't forget to follow us on LinkedIn https://www.linkedin.com/company/halter-limited & Instagram https://www.instagram.com/lifeathalter/. WHY OUR TEAM LOVES WORKING AT HALTER: - Work that genuinely matters. Every now and again a company comes along that transforms an entire industry and leaves the world in a better place. Our team gets to be part of something truly meaningful, helping farmers improve their livelihoods, spend more time with their families, and build more sustainable operations. - Spectacular people solving hard problems. Our culture is designed for talented people to do work that changes lives. The team is filled with diverse, kind, and driven people who push each other to do their best work. You'll be thrown into the deep end, tackling complex challenges and building something tangible that solves real problems. - You'll grow here. Autonomy, mastery, and learning define how we work. You'll have the freedom to work on interesting problems, master new skills, and continuously develop yourself, both through your role and our personal growth fund. - This isn't easy, and we love that it's hard. Working at Halter will be the most rewarding and the most challenging work of your life. We move fast, take bold bets, and work hard to reshape an entire industry. As one team member put it: "Joining Halter is a bit like strapping yourself to a rocket ship, but it's an epic journey to be a part of!"

Location: Seattle, WA ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. ABOUT THE TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes WHAT YOU’LL BRING - 5+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $165,000–$380,000 USD Looking for a hands-on implementation role focused on custom delivery, bespoke integrations, and scoped consulting projects? Please check out the Deployed Engineer (Professional Services) roles. COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: United States, Madison, WI Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Sr. Software Development Engineer In Test, ML/AI At SIE, we believe in making play safer for everyone. Within our Information Security team, we protect our people, platforms, and products with smart, scalable, and thoughtful solutions. Our mission is to provide clear, actionable risk and security insights that guide the business and enable amazing player experiences. We’re building a team that thrives on collaboration, curiosity, and delivering real value. Come help us make a difference! Overview We are hiring a Sr Software Engineer in Test specializing in ML/AI quality, including automation for model evaluation, LLM-assisted test generation, and validation of AI-powered workflows. The role includes guiding quality strategy and developing automation frameworks. You will also manage implementation for complex, cross-functional, machine learning-powered products and services. This role involves more than test development. You will lead quality initiatives from start to finish, ensuring teams stay synchronized, dependencies are managed, and releases are delivered confidently. You will work closely with ML, engineering, product, and infrastructure teams. You will shape how quality is built, monitored, and expanded while leading embedded QE efforts within projects. What you’ll do Define and complete quality strategies, test plans, and automation coverage for ML-powered services and platform components. Use LLMs and other AI-assisted techniques to generate, expand, and maintain high-value test cases for ML-powered workflows. Design scenario-based test suites for AI features, including adversarial prompts, edge cases, ambiguous inputs, and underrepresented user scenarios. Lead QE efforts for multi-functional projects, driving risk assessment, dependency management, and release readiness. Design, develop, and maintain scalable automation frameworks for backend services, APIs, and ML inference systems using Python and/or Java. Build automated validation for ML and LLM outputs, including ranking behavior, score distributions, prompt/response quality, hallucination indicators, and probabilistic model evaluation. Debug test failures, service anomalies, model inconsistencies, and AI behavior regressions to identify root causes and drive resolution. Perform functional, integration, regression, API, end-to-end, performance, and reliability testing for distributed systems. Improve automation reliability, reduce flakiness, and optimize execution efficiency. Partner with engineering and ML teams to integrate automated testing into CI/CD pipelines and release workflows. Collaborate across teams to establish scalable quality standards, tooling, and guidelines. Required qualifications Bachelor’s degree in Computer Science or equivalent 5+ years of experience as an SDET or QE engineer focused on backend and distributed systems. Experience using LLMs to generate, transform, and prioritize test cases for AI-powered experiences. Experience with AI evaluation tooling, prompt evaluation frameworks, model monitoring, or human-in-the-loop review workflows. Strong experience testing RESTful APIs, microservices, and distributed architectures. Proficiency in Python, Java, JS or similar languages for automation development. Hands-on experience with automation frameworks such as pytest, JUnit, Selenium, Playwright, Cypress, or Appium. Experience with CI/CD systems and test pipelines (Jenkins, GitHub Actions, etc.). Experience with cloud and container technologies (AWS, GCP, Kubernetes, Docker). Familiarity with databases, monitoring, and observability tools. Strong understanding of SDLC, Agile methodologies, and release processes. Excellent problem-solving, debugging, and communication skills. Preferred qualifications Experience validating ML outputs using statistical analysis or scenario-based testing approaches. Familiarity with ML infrastructure, data pipelines, or model-serving platforms (Seldon, KServe, Ray Serve, etc.). Prior work in content moderation ML, security, fraud detection, or adversarial ML. Experience testing high-scale, low-latency online services. Experience with Databricks or similar ML platform tooling. Familiarity with Node.js, React, or modern frontend technologies. Experience testing mobile, console, or other non-PC platforms. What sets you apart Strong combination of automation engineering and delivery ownership. Ability to drive quality across complex cross-functional initiatives. Practical understanding of how to test non-deterministic AI systems and separate model variance from quality regressions. Proven risk management and dependency coordination skills. Ability to influence engineering teams and promote quality guidelines. Passion for scalable, reliable, and maintainable automation systems. At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location. Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location. In addition, this role is eligible for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more. The estimated base pay range for this role is listed below. $152,500 — $228,700 USD Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Team Description Reddit's Ads business is at an inflection point, and generative AI is reshaping how advertisers plan, build, launch, measure, and optimize campaigns. The Agentic Ads Experience team is building the next generation of advertiser-facing interfaces: campaign assistants, creative and ad copy generation, one-click campaign creation, audience discovery, conversational analytics, and optimization recommendations. This is a unique opportunity to join a fast-moving team shipping generative AI/agentic systems into a high-growth Ads product, where every launch has direct advertiser and revenue impact. Role Description As a Senior Software Engineer on the Agentic Ads Experience team, you will design, build, and ship AI-powered product experiences that change how advertisers work with Reddit Ads Platform. You will own features end-to-end: framing the problem, choosing the right combination of software, LLM calls, tools, orchestration, and guardrails, and driving them through rollout, measurement, and refinement. The ideal candidate is a strong product-focused software engineer with hands-on generative AI application experience, who has an opinionated point of view on where agents, workflows, skills, and retrieval belong, and who cares deeply about shipping reliable systems that advertisers actually trust. Responsibilities: Product Execution: Design and ship advertiser-facing AI features and platform (campaign assistants, creative generation, audience discovery, performance analytics, optimization recommendations) end-to-end, from prototype to GA. Agentic Systems Design: Make the right architectural calls on if and how to use generative AI, whether it’s a single-shot LLM call, a workflow, a skill, a retrieval system, an agent loop, human review, or no AI at all. Reliability and Guardrails: Build for the failure modes of LLMs — structured outputs, tool/action boundaries, retries, cost controls, tracing, evals, and human-in-the-loop where it matters. Measurement: Define offline and online evals, instrument traces, run A/B tests, and connect model and product metrics to advertiser and business outcomes. Safety and Trust: Design for data isolation, permissioning, auditability, and policy compliance when AI systems take action on behalf of advertisers. Collaboration: Partner closely with PM, Design, Data Science, ML Platform, Trust, and sales/ops to turn ambiguous problems into concrete, shippable systems. Collaborate with other product teams on how best to expose their services and capabilities to the platform’s centralized agent(s). Craft and Communication: Write clear design docs, explain trade-offs to non-engineers, and raise the bar on how the org ships gen AI features. Required Qualifications: 5+ years of experience as a software engineer, with a track record of shipping and operating production systems. Hands-on experience building generative AI applications: structured outputs, function/tool calling, prompt and context design, RAG, model routing, and handling model failure modes. Genuine enthusiasm for agents and LLMs — you follow the space closely, have opinions on the tools, and can talk shop about the evolving ecosystem. Strong systems fundamentals: APIs, distributed systems, queues, data stores, service ownership, auth, idempotency, retries, and observability. Experience defining evals and measurement for AI systems — offline datasets, online metrics, and knowing when and how to measure a launch quality bar. Fluent with AI coding tools and code-assistant workflows as part of your day-to-day engineering practice. Excellent communication skills. You can collaborate effectively in a remote environment and explain complex AI system trade-offs to technical and non-technical audiences. Extensive software development experience in one or more general purpose languages: Python, Golang, Rust, Java, JavaScript, etc. Bonus Points: Experience in Ads, marketing technology, marketplaces, growth, recommendations, search, or analytics. Experience building AI systems where mistakes are expensive: customer-facing products, regulated workflows, policy review, payments, or high-scale infrastructure. Experience building internal workflow automation for sales, ops, support, policy, trust, or engineering productivity. Benefits: Comprehensive Healthcare Benefits and Income Replacement Programs 401k Match Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Reddit Global Days Off Generous paid Parental Leave Paid Volunteer time off #li-remote Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $190,800 — $267,100 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Location: San Francisco; Palo Alto; New York City ABOUT THE ROLE The Data Platform team owns the end-to-end data lifecycle at Perplexity, from ingestion through processing, storage, and serving, powering product features, analytics, experimentation, AI workloads, and the company’s data lake. The team defines the architecture for batch and streaming systems, the orchestration and observability stack, and a self-serve data platform, while thoughtfully combining platforms such as Databricks and Snowflake with open-source technologies including Spark, Kafka, Flink, Airflow, Dagster, dbt, Iceberg, Delta Lake, and ClickHouse. In this senior/staff role, you will shape architecture, set standards, and drive the long-term technical direction of Perplexity’s data ecosystem. KEY RESPONSIBILITIES - Design and operate large-scale batch and streaming data pipelines that directly power Perplexity product features, AI training and evaluation workflows, analytics, and experimentation. - Build event-driven and streaming systems (Kafka, Kinesis, PubSub, or similar) for real-time ingestion, transformation, and delivery, alongside batch frameworks for backfills, aggregations, and offline computation. - Lead the architecture of data orchestration using tools like Airflow or Dagster, owning scheduling, dependency management, retries, SLAs, and end-to-end observability for critical data flows. - Set and enforce guarantees for data correctness, freshness, lineage, and recoverability, designing systems that handle rapid scale growth, partial failures, and evolving schemas without disrupting AI workloads or product experiences. - Build self-serve data platforms that let engineers, data scientists, and analysts safely discover data, define contracts, and create and operate their own pipelines with minimal friction. - Improve developer experience through better abstractions, opinionated paved paths, and standards for data modeling, testing, validation, and deployment, treating the data platform as a product used by many teams. - Drive architectural decisions across storage, compute, orchestration, and data APIs, partnering closely with product engineering and data science to align the data ecosystem with Perplexity’s roadmap. - Mentor engineers, review designs, and raise the technical bar for data infrastructure through thoughtful feedback, documentation, and hands-on collaboration. QUALIFICATIONS - 5+ years (Senior) or 8+ years (Staff) of software engineering experience. - Strong experience building production data infrastructure systems. - Hands-on experience with batch and/or streaming data processing at scale. - Deep familiarity with data orchestration systems (Airflow, Dagster, or similar). - Proficiency in Python and at least one additional backend language (Go, TypeScript, etc.). - Strong systems thinking around reliability, latency, cost, and complexity tradeoffs. - Experience supporting ML/AI workflows, training pipelines, or evaluation systems. - Familiarity with data quality, lineage, observability, and governance tooling. - Prior ownership of internal platforms used by many teams. If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above.

Location: San Francisco; Palo Alto; New York City ABOUT THE ROLE The Data Platform team owns the end-to-end data lifecycle at Perplexity, from ingestion through processing, storage, and serving, powering product features, analytics, experimentation, AI workloads, and the company’s data lake. The team defines the architecture for batch and streaming systems, the orchestration and observability stack, and a self-serve data platform, while thoughtfully combining platforms such as Databricks and Snowflake with open-source technologies including Spark, Kafka, Flink, Airflow, Dagster, dbt, Iceberg, Delta Lake, and ClickHouse. In this senior/staff role, you will shape architecture, set standards, and drive the long-term technical direction of Perplexity’s data ecosystem. KEY RESPONSIBILITIES - Design and operate large-scale batch and streaming data pipelines that directly power Perplexity product features, AI training and evaluation workflows, analytics, and experimentation. - Build event-driven and streaming systems (Kafka, Kinesis, PubSub, or similar) for real-time ingestion, transformation, and delivery, alongside batch frameworks for backfills, aggregations, and offline computation. - Lead the architecture of data orchestration using tools like Airflow or Dagster, owning scheduling, dependency management, retries, SLAs, and end-to-end observability for critical data flows. - Set and enforce guarantees for data correctness, freshness, lineage, and recoverability, designing systems that handle rapid scale growth, partial failures, and evolving schemas without disrupting AI workloads or product experiences. - Build self-serve data platforms that let engineers, data scientists, and analysts safely discover data, define contracts, and create and operate their own pipelines with minimal friction. - Improve developer experience through better abstractions, opinionated paved paths, and standards for data modeling, testing, validation, and deployment, treating the data platform as a product used by many teams. - Drive architectural decisions across storage, compute, orchestration, and data APIs, partnering closely with product engineering and data science to align the data ecosystem with Perplexity’s roadmap. - Mentor engineers, review designs, and raise the technical bar for data infrastructure through thoughtful feedback, documentation, and hands-on collaboration. QUALIFICATIONS - 5+ years (Senior) or 8+ years (Staff) of software engineering experience. - Strong experience building production data infrastructure systems. - Hands-on experience with batch and/or streaming data processing at scale. - Deep familiarity with data orchestration systems (Airflow, Dagster, or similar). - Proficiency in Python and at least one additional backend language (Go, TypeScript, etc.). - Strong systems thinking around reliability, latency, cost, and complexity tradeoffs. - Experience supporting ML/AI workflows, training pipelines, or evaluation systems. - Familiarity with data quality, lineage, observability, and governance tooling. - Prior ownership of internal platforms used by many teams. If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above.

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. We're seeking an exceptional Research Scientist to join our Life Sciences team at Anthropic. Our team is building a world-class research group focused on making Claude a superhuman life sciences research assistant. This role sits at the intersection of machine learning, software engineering, and biology — you'll directly improve model capabilities on scientific tasks through post-training, evaluation design, and RL environment development. As a core member of our Life Sciences team, you'll work in a high-impact team that translates deep biological domain knowledge into model training objectives, benchmarks, and agentic workflows. You'll help establish Anthropic as a leader in AI-accelerated biology while shaping how frontier models reason about and execute computational biology tasks. This role offers a unique opportunity to shape how frontier AI models learn to do biology. You'll work alongside some of the world's best AI researchers while tackling problems that matter for human health and scientific understanding. If you're excited about turning your computational biology expertise into model capabilities, we want to hear from you. Key Responsibilities Build and ship agentic tools and integrations that let Claude execute real life science workflows — bioinformatics pipelines, database queries, analysis notebooks, literature review Design and build evaluation benchmarks that measure model capabilities on biology tasks — figure interpretation, bioinformatics, protocol reasoning, literature synthesis Work closely with product and design teams to scope, prototype, and ship features for life sciences users Partner with external biotech, pharma, and academic users to understand their workflows and turn feedback into product improvements Build and maintain the engineering infrastructure behind our biology product surface — tool scaffolding, data pipelines, eval harnesses Translate biological domain knowledge into product requirements and evaluation criteria that guide model improvement Minimum Qualifications Experience applying ML and software engineering to biological problems — computational biology, bioinformatics, protein ML, genomics, or similar Experience working in drug discovery or development at a biotech or pharma company, or conducted fundamental research in an academic setting — with an understanding of what real scientific workflows look like and where they break down Strong software engineering skills: comfortable building production-quality Python, working in large codebases, and owning infrastructure end-to-end Hands-on experience training or fine-tuning ML models (LLMs, protein language models, or other deep learning architectures) A track record of shipping computational tools or pipelines that biologists actually use Comfortable navigating ambiguity and defining problems in a rapidly evolving research environment Able to work independently while collaborating tightly with research, product, and domain-expert teams Results-oriented with a bias toward rapid iteration and measurable impact Passionate about using AI to accelerate scientific discovery while maintaining high ethical standards Preferred Qualifications 5+ years of experience applying ML and software engineering to biological problems — computational biology, bioinformatics, protein ML, genomics, or similar Ph.D. in computational biology, bioinformatics, bioengineering, CS, or a related quantitative field — or equivalent industry experience Experience with LLM post-training: RLHF, RL from verifiable rewards, SFT data curation, or eval-driven development Direct experience with therapeutic discovery pipelines — target identification, lead optimization, ADMET modeling, or clinical data analysis Familiarity with bioinformatics tooling and pipelines (sequence analysis, structure prediction, single-cell, variant calling, etc.) Experience building agentic systems or tool-use environments Published research in ML for biology, or open-source contributions to computational biology tools Fluency with biological databases (UniProt, PDB, Ensembl, NCBI) and the ability to reason about their schemas and failure modes The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Europe We are toogeza, a Ukrainian recruiting company that is focused on hiring talents and building teams for tech startups worldwide. People make a difference in the big game, we may help to find the right ones. Currently, we are looking for AI Video Agent Engineer for Elva. Location: Remote Job Type: Full-Time OVERVIEW: We are building an AI-driven video production system designed as an intelligent multi-agent orchestration layer capable of transforming raw ideas and references into fully structured video content. The system operates as a black-box creative engine for different types of users: - professional video creators - casual users - creators of short narrative concepts Users provide an idea, references, or media fragments, and the system automatically orchestrates multiple AI agents responsible for analysis, scripting, editing, and production of video content. We are looking for an engineer who can design and implement multi-agent pipelines, orchestrate AI tools, and build intelligent workflows that combine video analysis, storytelling logic, and automated editing. This role sits at the intersection of AI systems architecture, creative tooling, and multimodal content generation. RESPONSIBILITIES: AI Agent Architecture Design and implement the architecture of a multi-agent video editing system including agents responsible for: - video analysis - narrative generation - editing orchestration - production and output synthesis Define system prompts, behavioral rules, and structured instructions for agents interacting within the pipeline. Pipeline Orchestration (n8n) Develop and maintain complex orchestration pipelines in n8n, including: - multi-agent workflows - tool-calling logic - dynamic routing between tools and models - context passing between agents Pipelines must be capable of selecting the most appropriate models, tools, and strategies depending on the task. Multimodal Data Processing Design robust pipelines for handling: - video materials - image assets - user text prompts - structured metadata Ensure proper data transformation and context transfer across the pipeline stages. Tool & API Integration Integrate both external and internal APIs for multimodal generation and processing, including: - image generation - video generation - speech synthesis - audio generation - video processing services Rapidly evaluate available APIs and select the best quality tools and models for each task. Model Orchestration & Optimization Tune and optimize model interactions, primarily based on Gemini models, including: - prompt engineering - structured outputs - tool-calling workflows - agent collaboration logic Optimize pipelines for quality, reliability, and execution efficiency. Future Architecture (RAG & Knowledge Systems) Design systems that support: - vector databases - retrieval-augmented generation (RAG) - memory and contextual reasoning between agents EXPECTED OUTCOMES: The pipeline system should be capable of: 1. Taking an idea + references as input 2. Analyzing the content 3. Generating a coherent narrative structure 4. Selecting appropriate visual and audio elements 5. Producing a high-quality, structured video output REQUIREMENTS: AI Systems & Agent Architecture Strong experience building multi-agent systems, including: - intent and sub-intent modeling - agent orchestration - agent communication and transport layers - summarization pipelines - context passing between agents Workflow Orchestration Hands-on experience with: - n8n - Agent tool-calling - n8n MCP Experience designing complex automation pipelines is essential. Programming Strong practical coding skills with vibe coding mindset: Primary languages: - Python - JavaScript Bonus experience: - ComfyUI custom nodes - lightweight APIs (e.g., HuggingFace Spaces or inference endpoints) Multimodal Tooling Knowledge Ability to quickly navigate API documentation and integrate tools for: - image generation - video generation - speech synthesis - audio generation - multimodal analysis You should know where and how to obtain the best generation quality for each modality. Creative Thinking - Strong sense of visual rhythm and composition - Creative intuition and storytelling awareness - Good taste in video structure and montage - Ability to evaluate AI-generated output not only by metrics, but also by creative quality and narrative coherence Video & Media Processing Preferred experience with: - FFmpeg - video processing pipelines - image processing workflows NICE TO HAVE: The following qualifications are not mandatory, but will significantly strengthen a candidate’s profile during the evaluation process: Agentic Frameworks Deep understanding of frameworks such as LangGraph and LangChain for building complex cyclic state graphs and stateful agent systems. Advanced RAG & Memory Management Experience designing long-term memory systems for agents, including mechanisms for storing and retrieving successful execution patterns or scenarios to improve future performance through experience-based retrieval. Self-Correction & Reflection Experience building agents with feedback loops such as self-reflection, self-critique, or strategy correction, enabling them to verify their own actions and adapt execution logic dynamically. Evaluation & Observability Experience with tools for monitoring, debugging, and evaluating agent chains and prompt behavior, such as LangSmith, Arize Phoenix, or Promptfoo, with the ability to identify logical failures, quality regressions, and orchestration bottlenecks. IDEAL CANDIDATE: The ideal candidate is someone who naturally operates between engineering and creative production, capable of building systems that automate complex media workflows while preserving narrative coherence and aesthetic quality. You enjoy designing systems where AI agents collaborate to produce meaningful creative outputs. What’s next? If this role sounds like a fit — we’d love to hear from you! Just send over your CV and anything else you’d like us to consider. We’ll review everything within five working days, and if your background matches what we’re looking for, we’ll get in touch to set up a call and get to know each other better.

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 Team The SRE team is dedicated to deeply integrating large language models (LLMs), AI Agents, and engineering platform capabilities to build an intelligent application system for R&D, operations, stability, and business scenarios. By creating an AI application architecture that is observable, evaluable, governable, and continuously evolving, the team is driving the company's shift from "tool-assisted" to "intelligent collaboration," improving R&D efficiency, system stability, fault diagnosis efficiency, and the quality of business decisions. What You’ll Be Doing Design and build AI Harness capabilities for SRE / DevOps scenarios, including fault detection, change analysis, capacity risk identification, automated inspection, drill evaluation, and recovery recommendations. Drive the development of an automated RCA (Root Cause Analysis) system, combining logs, metrics, distributed tracing, events, changes, topology, and other data to achieve root cause analysis, impact scope assessment, and post-incident review support. Build AIOps platform capabilities, including intelligent alert noise reduction, anomaly detection, event correlation, trend prediction, fault attribution, and automated closed-loop remediation. Collaborate with R&D, SRE, platform, data, and business teams to embed AI capabilities into Code Review, CI/CD, GitOps, DevOps, incident response, and stability governance processes. What We Look For In You Bachelor's degree or above in Computer Science or a related field, with 8+ years of experience in R&D, architecture, or platform engineering; experience building AI applications, SRE, AIOps, or DevOps platforms is preferred. Strong software architecture skills, familiar with microservices architecture, distributed systems, high-availability design, service governance, observability, and platform engineering. Familiar with LLM application development; understanding of core technologies such as LLM, RAG, Embedding, vector databases, Agents, Function Calling / Tool Calling, and Prompt Engineering. Understanding of the production challenges of AI applications, including hallucination control, result evaluation, permission boundaries, data security, cost control, observability, and failure fallback mechanisms. Experience delivering AI Agent or intelligent assistant products, able to design complex task decomposition, multi-tool invocation, multi-turn reasoning, context management, and human-machine collaboration workflows. Familiar with RCA or AIOps capability development, including log analysis, metric anomaly detection, distributed tracing, event correlation, alert noise reduction, topology analysis, and root cause localization. Proficient in at least one mainstream development language, such as Java, Python, Go, or TypeScript, with strong engineering implementation and system design skills. Familiar with cloud-native technology stacks and common middleware, such as Kubernetes, Docker, Kafka, Redis, MySQL, Elasticsearch, Prometheus, Grafana, OpenTelemetry, etc. Strong complex problem analysis skills and holistic architectural thinking, able to drive problem-solving from business, platform, process, and organizational collaboration perspectives. Ability to communicate in both Chinese and English is preferred as the role requires collaborating with cross-region stakeholders 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 dependents 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: New York, NY Workplace: OnSite We are building AI to simulate the world through merging art and science. We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world. World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached. Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you. *Titles posted to our careers page are updated regularly to best advertise the role and expected seniority, but internally we have a flat titling system with two types of titles: one for individual contributors and one for people managers. ABOUT THE ROLE *Open to candidates based near our NYC office or those willing to relocate. Building general world models — systems that understand and simulate reality across tasks, modalities, and domains — requires closing the loop between learned representations and real-world action. We're looking for a Robotics Engineer to bring our video-native foundation models onto real hardware: deploying world-model-based policies on real robots and making them work in the real world. You will work across the full stack of robot learning — from data collection and task design, to policy deployment, to physical evaluation. This is a hands-on, execution-oriented role at the intersection of foundation models, learned robot policies, and hardware. You'll bring deep robotics domain expertise and help us ship world-model-based robot policies end-to-end, with applications ranging from manipulation to mobile robotics. WHAT YOU’LL DO - Own the deployment loop for learned policies (VLAs, diffusion policies, World Action Models) on real robot arms: inference serving, action decoding, controller integration, latency budgets, and safety limits - Diagnose real-world policy failures — determining whether the problem is data coverage, camera/proprioception mismatch, or execution — and partner with the research team to fix it at the right layer - Design demonstration data collection protocols (task setup, camera placement, teleop conventions) that produce data our world models can actually learn from — working with our existing teleop and lab infrastructure - Partner with research to run controlled experiments connecting world model representations, data composition, and fine-tuning recipes to physical success rates - Define and run physical evaluation protocols so results are trustworthy and comparable across policy iterations - Adapt our policy recipe to partner hardware and new embodiments WHAT YOU’LL NEED - You have personally deployed software on real robot hardware and iterated to make it work — whether learned policies, motion planning, classical control, or perception-driven manipulation. You can walk through a specific system you shipped, what broke on the physical robot that didn't break in sim or testing, and how you fixed it. - Fluency in the software-to-robot interface: action/command spaces, control frequencies, observation pipelines, calibration, and how each affects real-world behavior - Comfort working at the intersection of software and physical systems: you can reconfigure a robot workspace and trace a policy failure in the same afternoon - Bonus: direct experience deploying learned policies (VLAs, diffusion policies) on real hardware; experience with video/multimodal generative models or world models Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide. There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates. WORKING AT RUNWAY Great things come from great teams. https://www.youtube.com/watch?v=kwmj4ato2kw&ab_channel=Runway We’d love to hear from you. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply. More about Runway - Universal World Simulator https://runwayml.com/world-simulator.html - GWM-1 https://runwayml.com/research/introducing-runway-gwm-1 - Gen-4.5 https://runwayml.com/research/introducing-runway-gen-4.5 - General World Models https://runwayml.com/research/introducing-general-world-models - Robotics SDK https://runwayml.com/research/introducing-runway-gwm-1#robotics-section - Conversational Real-time Agents https://runwayml.com/research/introducing-runway-gwm-1#avatars-section - Runway Studios https://runwayml.com/studios We're excited to be recognized as a best place to work: Crain's https://www.crainsnewyork.com/awards/best-places-work-2023 | InHerSight https://www.inhersight.com/companies/best/city/new-york-city-ny | BuiltIn NYC https://builtin.com/awards/new-york-city/2024/best-places-to-work | INC https://www.inc.com/best-workplaces/2024

StellarTech is building a Customer Tech Care unit - a specialised engineering squad embedded within Customer Care, whose sole purpose is to technically resolve every user issue that cannot be solved by a standard support agent. As the Lead, you will be the technical authority and organisational backbone: triaging escalated tickets, directing your team of automation engineers, coordinating with product and infrastructure engineering, and personally architecting or approving every solution shipped. This is not a traditional support lead role. You will spend the majority of your time in systems - querying databases, reproducing bugs in staging, reading logs, designing automation flows, and evaluating LLM agents. You are the bridge between what support teams observe and what engineering teams build. What You’ll Do: 1. Team Leadership & Unit Operations • Own day-to-day operation: capacity planning, sprint structure, task distribution, and quality standards. • Mentor and grow automation engineers; define code and architecture review processes. • Establish and track unit KPIs: ticket deflection rate, automation coverage ratio, recurrence prevention. • Report unit performance to management; propose headcount and tooling investments backed by data. 2. Escalation Triage & Technical Investigation • Serve as the primary technical intake point for all escalated issues: reproduce problems, isolate root causes, scope resolution paths. • Access production/staging systems, internal dashboards, and databases (SQL/NoSQL) to investigate issues directly. • Analyse logs, event streams, payment records, subscription states, and user journey data. • Own the diagnostic protocol and ensure team members follow structured investigation runbooks. 3. Automation Solution Architecture • Design and oversee automation solutions that resolve recurring issue categories without human intervention. • Architect multi-step pipelines spanning Zendesk triggers, internal API calls, and database state changes. • Define the solution taxonomy (macro vs. API vs. LLM agent vs. DB script) and enforce it across the team. • Approve all automation flows before production deployment; enforce rollback and monitoring standards. 4. LLM & AI Agent Delivery • Lead design and deployment of LLM-based agents capable of diagnosing and resolving issues autonomously. • Define agent architecture for context injection: user profile, subscription state, events, ticket history from DB. • Oversee training loop quality: curate high-quality resolved tickets to improve agent accuracy. • Evaluate agent performance quantitatively; own escalation decisions vs. further automation. 5. Engineering–Support Interface • Act as authoritative translator between support teams (who observe symptoms) and engineering teams (who own systems). • Maintain a shared escalation taxonomy and SLA matrix agreed with both Support Director and Engineering leads. • Own the feedback loop: unit diagnostic output becomes the engineering bug report that ships a fix. • Coordinate with Product, Backend Engineering, and Data teams to secure required system access and API endpoints. 6. Documentation & Knowledge Management • Maintain a live runbook library: automation flows, escalation paths, investigation procedures. • Ensure every automation has a documented failure mode and rollback path. • Create onboarding materials for new automation engineers. What We’re Looking For: • 5+ years in automation engineering, technical support engineering, or platform engineering - with 1–2 years in a team lead or tech lead capacity. • Demonstrated ability to investigate production issues via direct system access: logs, SQL/NoSQL databases, API responses, event streams. • Hands-on experience building LLM-based agents or AI-driven automation (OpenAI API, function calling, embeddings, or equivalent). • Strong Python skills; production-quality scripts for automation, data remediation, and API orchestration. • Experience designing Zendesk automation pipelines (triggers, automations, ZAF apps) or equivalent support platforms. • Event-driven architecture and API integration patterns (REST, webhooks, async queues). • Track record owning support metrics: deflection rate, FCR, CSAT, time-to-resolution. Nice to have: • Low-code/no-code orchestration tools (n8n, Zapier, Make, Rivet) in hybrid architectures. • B2C or subscription-based product background with high user volume and complex billing/access state. • CI/CD pipelines and production-level monitoring for automation systems. • Data engineering concepts: pipeline design, idempotency, retry logic, dead-letter queues. • RAG architectures, vector databases, or knowledge-base-augmented LLM agents. • Experience in a regulated environment (GDPR, PCI-DSS, SOC 2). Why You'll Love Working With Us: Innovative Environment: We're all about trying new things and pushing the envelope in EdTech. We are global remote Health: company-provided medical expense compensation. AI solutions: АІ subscription and other tools. Balance: Flexible paid time off, you get 21 days of annual leave + 10 bank holidays. Collaborative Culture: Work alongside passionate professionals who are as driven as you are. Interview Stages: HR Screen/Introduction Technical Interview Technical Assignment Final Interview

Location: Hamburg Workplace: Hybrid adjoe is redefining the future of mobile advertising. Powered by advanced AI, first-party data, and world-class engineers, we’ve perfected the offerwall experience for monetizing and scaling app publishers with solutions like Playtime and Arcade – now the fastest growing rewarded advertising channel globally – driving incremental engagement, retention, and revenue. At the same time, we’re breaking into programmatic advertising with our intelligent bidding system of adjoe Ads. Together, this ecosystem connects app developers to over 700 million users worldwide for scalable growth. Backed by Europe’s leading media powerhouse Bertelsmann and operating from offices in Hamburg (HQ), Boston, Singapore, and Tokyo, adjoe is defining the next stages of app and ad experience – right now. Join us. What You Will Do: - Executive Relationship Management: Navigate and manage high-stakes technical relationships with C-level stakeholders (CTOs, Architects, and Engineering Leads) at our most strategic publisher partners. - Success & Service Excellence: Ensure industry-leading satisfaction levels and uphold rigorous Service Level Agreements (SLAs) for our global publisher base. - Technical Implementation: Oversee end-to-end complex onboardings and technical integrations, ensuring seamless alignment between publisher tech stacks and our proprietary systems. - Strategic Escalation: Act as the final point of escalation for “unsolvable” technical bugs, delivery discrepancies, or high-priority system failures. - Product Advocacy: Partner closely with Product and Engineering teams to translate direct publisher feedback and technical pain points into actionable items for the product roadmap. - Mentorship & Growth: Lead, mentor, and scale a team of Technical Account Managers (TAMs), fostering a culture of technical curiosity and client-first problem-solving. - Standardization: Develop and refine “Playbooks” for onboarding, troubleshooting, and partner management to ensure a consistent, world-class partner experience. Who You Are: - You bring 8+ years of experience in Ad Tech, MarTech, or SaaS, including at least 5 years in a formal leadership or people-management capacity. - Executive Ownership: You embody a “driver” mentality. You take full accountability for key initiatives, navigating ambiguity with a sense of urgency and ensuring projects reach the finish line through proactive leadership. - Analytical Power: You possess elite problem-solving skills and are comfortable “getting into the weeds” with data. You are proficient in SQL for database querying, as well as Excel and other advanced analytics tools. - Technical Literacy: You have a solid understanding of HTML and JavaScript (or a similar scripting language). You understand the architecture of the web and how disparate technical systems communicate. - Systems Expertise: You have a working knowledge of HTTP REST endpoints and the ability to diagnose failures within API-driven environments. - Master Communicator: Fluent in English, with the ability to clearly translate complex technical concepts for executive stakeholders and business priorities for engineering teams—without anything getting lost in translation. How You’ll Stand Out: - Fluency in German is a strong plus, enabling close collaboration with teams and stakeholders across our Hamburg HQ and wider DACH region. - Familiarity with Java, Kotlin, or Swift, or personal experience building and deploying your own applications. - A deep understanding of the mobile ad tech landscape, including SDK integrations and current industry best practices. We welcome applications from people who will contribute to the diversity of our company.

Location: Lappeenranta, Finland 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 We are seeking a skilled and motivated Data Center Electrical Lead to support the operation and maintenance of critical infrastructure within a mission-critical data center environment in Lappeenranta, Finland. The successful candidate will have a strong electrical background and experience working with power distribution systems, industrial maintenance, or critical facilities operations. This role is responsible for ensuring maximum uptime, reliability, and safety of data center electrical and mechanical systems while supporting 24/7 operations. Key Responsibilities Critical Infrastructure Operations Operate and maintain critical electrical systems including: UPS systems Medium- and low-voltage switchgear Transformers Backup generators ATS/STS equipment Battery systems Power distribution units (PDUs) Monitor facility systems using BMS/EPMS platforms. Perform routine inspections and operational checks of critical infrastructure. Maintenance & Troubleshooting Perform preventive and corrective maintenance on electrical and mechanical systems. Diagnose and troubleshoot equipment failures and alarms. Support emergency response and incident recovery activities. Coordinate with vendors and contractors during maintenance activities. Safety & Compliance Follow Finnish electrical safety regulations and company safety procedures. Support lockout/tagout (LOTO) procedures and safe switching operations. Maintain compliance with SFS 6002, occupational safety requirements, and site policies. Ensure all maintenance activities are properly documented. Operational Support Participate in 24/7 shift operations, including nights and weekends. Maintain accurate logs, reports, and maintenance records. Assist with commissioning and testing of new equipment and infrastructure upgrades. Support continuous improvement initiatives for operational efficiency and reliability. Qualifications Required Vocational qualification, diploma, or degree in: Electrical Engineering Industrial Maintenance Automation Technology Power Systems Experience working with electrical infrastructure or industrial systems. Knowledge of: Power distribution systems Electrical troubleshooting Preventive maintenance practices Ability to read electrical schematics and single-line diagrams. Good English communication skills. Preferred Data center or mission-critical facility experience. SFS 6002 Electrical Safety certification. Experience with medium-voltage systems. Knowledge of HVAC/cooling infrastructure. Experience using CMMS, BMS, or EPMS systems. Finnish language skills are an advantage. 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: Armenia; Spain; Serbia; Poland; Kyiv City; Kyiv; Odesa; North Macedonia Workplace: remote About Provectus Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide.   Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture.   Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDE and an FDX, Forward Deployed Executives (FDX) own the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs. Forward Deployed Engineers (FDE) embed with a client, map the client workflow, identify the business problem underneath it, design and build a working AI solution, present to the client, and transfer the knowledge to the client's team. Owns technical direction of the whole solution. Senior AI Engineer. When an FDE comes back from the client with the business problem, you will help turn that into an agentic system that runs in production and will be responsible for evaluation, observability, and guardrails.  You'll have real ownership of components and of the technical decisions inside them. Requirements: Mindset Proactive and self-directed; you push for clarity rather than waiting for a ticket Excellent communication and problem-solving skills Comfort with ambiguity and ownership. B2+ English, comfortable collaborating across distributed, multicultural teams. Technical depth 5+ years in software or ML engineering, with production systems you were accountable for . Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes. Shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks. Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production. Strong engineering fundamentals. Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure. Python and/or TypeScript proficiency; depth matters more than stack. Dropped into an unfamiliar codebase, you're productive. Hands-on AWS in production: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus. Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release. Model and agent monitoring, drift detection. Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs. Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus. MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus. Responsibilities: Work in a pair with an FDE and an FDX. Build and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Build and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Integrate AI components into backend services and RESTful APIs Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD. Implement LLMOps and AgentOps practices: agent tracing, prompt and version management, cost and latency monitoring, regression testing, drift detection Start from the blueprint, contribute to enablement and handover: clear documentation, runbooks, and pairing with the client engineers who will inherit the system. Feed reusable components and lessons back into the Provectus Blueprints Participate in technical discussions and architectural decisions Conduct model evaluation, improve failure modes you find, optimize model performance, efficiency, and reliability Mentor junior and mid-level AI engineers, conduct code reviews and share knowledge across the team through documentation, presentations, and workshops. Nice to Have: Experience in one of the industries: financial services, insurance, healthcare. Consulting, professional services, or other embedded customer-facing delivery. AWS and Claude Code Certifications A2A: you can explain agent-to-agent interoperability CI/CD pipeline experience (GitHub Actions, GitLab CI) Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines. Experience in an additional language (Go, TypeScript, or Rust). Experience with Apache Spark, Apache Airflow, Kafkа What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside FDE and FDX A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire:   Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant  HR Interview. Soft skills and expectations HM interview. Tech questions; a live engine

Location: European Union Workplace: Remote ABOUT THE ROLE We're looking for someone who owns delivery - not tracks it, not reports it, owns it. You'll be responsible for a specific area: games, features, or platform work. From the first conversation about a requirement through to production - you're on the hook for the whole thing. This isn’t a coordination-only role. We need someone with previous hands-on software engineering, DevOps, release engineering, or similar technical experience who can actively improve and automate the way software is built, tested, and released. You set the timeline, track it, and communicate changes before people start asking questions. If there's a blocker, you've already seen it. If a release isn't ready, you say so - clearly and early. You'll look at how work flows through your area and fix what's broken. Not just follow whatever process exists. You'll design something that actually works, iterate on it, and make it better over time. A key part of the role will be identifying manual steps, bottlenecks, and failure points in development and release workflows, and then building practical automation to remove them. This may include improving CI/CD pipelines, automating release checks, connecting tools through APIs, and developing scripts or lightweight internal solutions. Quality is yours too. Not QA's problem alone, not the tech lead's problem. You own release readiness: is it tested, is it documented, does anyone know the operational risk. If the answer is no, it doesn't ship. You'll work closely with product, engineering, QA, and client-facing teams, keep them aligned, and report directly to the VP of Delivery. What we expect from you First 30 days - Understand how delivery actually works in your area - not how it should work, how it actually works - Map where work gets stuck, what the recurring blockers are, and who the key people are - Meet everyone who matters: product owners, tech leads, QA, release managers, client teams - Write up what you found and share it with the VP of Delivery First 60 days - Take ownership of delivery tracking for your area - Pick the biggest workflow problem you found and start fixing it - Show you can catch a blocker before it causes a delay - at least twice First 90 days - Own and communicate a delivery forecast that stakeholders actually trust - Ship at least one release with no last-minute surprises - quality gates passed, documentation done, everyone aligned - Present your view on how delivery should work in your area going forward What we're looking for - 3+ years in an engineering delivery, software delivery leadership, or similar role where you owned outcomes, not just process - Previous hands-on experience as a Software Engineer, DevOps Engineer, Release Engineer, Build Engineer, Developer Productivity Engineer, or in a similarly technical role. - Strong understanding of the software development lifecycle, including builds, automated testing, versioning, deployment, monitoring, and rollback. - You catch problems early. Not because you're lucky, but because you know what signals to watch - You've worked across engineering, product, and QA and you know how to keep them moving together - Strong communicator - you can give a clear, honest delivery update to a VP without needing a slide deck - You care about quality beyond closing tickets - release readiness, testing coverage, operational risk are things you think about naturally - You're genuinely interested in the product you're delivering, not just the process around it - You actively look for repetitive manual work and replace it with reliable, maintainable automation. Nice to have - Background in iGaming, gaming, or another regulated product environment - Experience in a B2B or multi-operator delivery model - Familiarity with incident management and post-mortems - Experience working with external studios or third-party development partners - OKR-based planning and how it connects to delivery cadence - Jira or similar tooling - configuration, not just usage     WHAT WE OFFER - Competitive Salary - Quarterly Bonuses - Unlimited Paid Time Off - Unlimited Paid Sick Leave - Remote & Flexible Working - Private Medical Insurance - Financial Support for Life Events - Professional Development Budget - International Exposure - Regular Company Events *Benefits may vary depending on location and contractual agreement By submitting your application, you acknowledge that your personal data will be processed in accordance with our Privacy Policy https://playson.com/privacy. #LI-DNI