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Location: Intellias Meet your recruiter Olha Huk olha.huk@intellias.com https://www.linkedin.com... Vacancy details AI/ML Engineering GenAI Engineer Senior Romania Hybrid APPLY NOW REFER A FRIEND Intellias helps retailers deliver consistent, omnichannel experiences through technology. Join us to develop scalable solutions that drive performance and customer value What project we have for you We are looking for a hands-on Senior AI Engineer to lead the technical design and delivery of enterprise AI agents and MCP-based integrations. The team will develop Model Context Protocol (MCP) services for local business applications and build AI agents that consume both these local MCPs and MCP services provided by a global platform team. The Senior AI Engineer will own solution design, support use-case discovery, provide technical leadership to the engineering team, and participate directly in implementation. What you will do Lead technical discovery and translate business use cases into AI/agentic solution designs. Design the architecture of AI agents and their interaction with local and global MCP services. Design and develop MCP services exposing capabilities of local applications to AI agents. Build enterprise AI agents and agentic workflows. Integrate agents with multiple MCP servers, APIs and enterprise systems. Define agent instructions, reasoning flows, tool-selection logic, approval workflows and human-in-the-loop guardrails. Define reusable patterns and engineering standards for MCP and agent development. Lead and support other AI engineers during implementation. Ensure compliance with enterprise security, architecture and AI governance requirements. Define and monitor agent quality and performance metrics, including task completion, tool failures, hallucinations, latency and cost. Collaborate with global AI/platform teams to ensure interoperability between local and global MCP capabilities. What you need for this Required skills Strong hands-on Python engineering experience. Experience building LLM-based applications, AI agents or agentic workflows . Strong knowledge of REST APIs and enterprise integrations. Strong Microsoft Azure experience. Experience with authentication/authorization such as OAuth 2.0 and Microsoft Entra ID. Understanding of tool/function calling and agent-to-system integration patterns. SQL, JSON, Git and CI/CD. Ability to design production-grade solutions and provide technical leadership. Strong English communication skills. Strong advantage Hands-on Model Context Protocol (MCP) experience. Azure AI Foundry / Azure OpenAI. Copilot Studio. Power Automate. Agent orchestration frameworks such as Semantic Kernel, LangGraph or similar. Azure Functions / API Management / Logic Apps. Experience with enterprise AI governance, evaluation and observability. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

Location: New York Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. We are looking for an experienced Trading Systems Software Engineer to help build the applications, platforms and engineering capabilities that support QRT’s global trading environment. This is a broad software engineering role spanning application development, distributed systems, cloud technology, deployment automation and production engineering. You will design and build software used by traders, quantitative researchers, operations teams and other engineers across the firm. Your Future Role within QRT Design, develop and maintain production-grade applications, services and APIs supporting QRT’s trading platform. Build shared platforms and reusable capabilities that can be adopted across multiple trading desks and engineering teams. Develop modern web applications and operational tools that improve visibility, control and efficiency across trading workflows. Design scalable distributed and event-driven systems that integrate with trading platforms, market data services and internal infrastructure. Build deployment tooling, release automation and self-service capabilities that make software easier and safer to deploy and operate. Develop automated workflows for data processing, operational tasks and engineering processes using technologies such as Apache Airflow. Partner with traders, quantitative researchers and operations teams to understand their needs and solve practical business problems. Design software for latency-sensitive environments, balancing performance with reliability, scalability and operational simplicity. Build observable and resilient systems with appropriate monitoring, alerting, recovery and failure-handling capabilities. Work alongside infrastructure, cloud and DevOps engineers to deploy and support software across global production environments. Contribute to technical design and architectural decisions, evaluating new technologies where they can deliver meaningful value. Take ownership of software throughout its lifecycle, from initial design and implementation through to production support and continuous improvement. Your present skillset At least five years of experience developing and supporting production-grade software. Strong programming and software engineering skills in one or more languages such as Python, Java, Go, Node.js or C++. Experience designing maintainable, testable and scalable applications and services. A strong understanding of software design principles, data structures, algorithms and engineering fundamentals. Experience building RESTful APIs, distributed systems or event-driven architectures. Exposure to containerisation, orchestration and delivery technologies such as Docker, Kubernetes and CI/CD pipelines. Experience with public cloud technologies, preferably AWS. An understanding of messaging technologies such as Kafka or RabbitMQ. Experience considering reliability, observability, performance and failure recovery when designing production systems. Strong analytical and problem-solving skills, with the ability to make sound engineering decisions and explain the associated trade-offs. The ability to work effectively with both technical and non-technical stakeholders. Base salary range for this position is $180,000 to $300,000 per year. QRT Total Compensation includes discretionary performance-based bonuses and a competitive benefits package.

* Build and operate batch and incremental ingestion pipelines in Google Cloud to Smartly Data Platform. * Develop Airflow workflows using Python with best orchestration practices, including dag dependencies, retries, backfills, alerting, and recovery.

Location: Intellias Meet your recruiter Khrystyna Derpak khrystyna.derpak@intellias.com https://www.linkedin.com... Vacancy details AI/ML Engineering Machine Learning Engineer Senior Bulgaria, Croatia, Poland Remote APPLY NOW REFER A FRIEND We are seeking a AI Engineer to transition our AI capabilities from “prototype” to “production.” In this role, you will not just experiment with models; you will architect robust Agentic Systems that can plan, reason, and execute complex workflows autonomously for a wide variety of business user needs while experimenting with cutting-edge models and tools to push the boundaries of what’s possible. The ideal candidate is a forward-thinking engineer who thrives on hands-on experimentation with AI models and frameworks, learns quickly, and is naturally curious. You will collaborate closely with product managers, business partners, and platform teams to deliver high-value AI agents that solve real-world problems across the enterprise. What project we have for you Client is a leading multi-brand technology solutions provider to business, government, education and healthcare customers in the United States, the United Kingdom and Canada. A Fortune 500 company and member of the S&P 500 Index, Client was founded in 1984 and employs approximately 10,000 coworkers. For the trailing twelve months ended September 30, 2020, the company generated Net sales over $18 billion. Broad array of offerings range from hardware and software to integrated IT solutions such as security, cloud, data center and networking What you will do Agentic Engineering & Orchestration Workflow Design: Architect complex, multi-agent workflows using Microsoft AI tech stack. Design, Develop and Deploy agents to handle loops, interruptions, and human-in-the-loop interventions. Tool Use & Function Calling: Build reliable “tool layers” that allow LLMs to safely interact with internal APIs, databases, and third-party SaaS platforms (e.g., SalesForce, Workday, ServiceNow etc.) State Management: Design persistence layers to manage agent memory, conversational history, and context windows efficiently. Advanced Data & RAG Strategy Retrieval Pipelines: Build production-grade data retrieval and integration systems. Optimize vector indexing, document chunking, and re-ranking algorithms to ensure high-precision context retrieval. Data Quality: Collaborate with Data Engineers to curate “Golden Datasets” for agent consumption LLMOps, Evaluation & Quality Automated Evaluation: Build CI/CD pipelines for AI that include “LLM-as-a-Judge” testing. Leverage frameworks to score agent outputs for accuracy, hallucination, and safety before deployment. Observability: Instrument applications with tracing tools to visualize agent reasoning chains, monitor latency, and debug failures in production. Cost Optimization: Monitor token usage and latency, optimizing prompt density and caching strategies to maintain high performance at sustainable costs. Innovation & Collaboration Prototyping to Production: Rapidly validate new ideas using state-of-the-art models, then refactor successful prototypes into maintainable, tested production code. Standards Adoption: Stay ahead of the curve by evaluating emerging technologies to standardize agent connectivity. What you need for this Core Engineering Bachelor’s degree and 5 years of software engineering experience, with exposure to AI/ML applications OR 9 years of software engineering experience, with exposure to AI/ML applications. Programming: Strong hands-on experience with Python for AI/LLM application development. Agentic AI: Hands-on experience designing and building AI agents / Agentic AI solutions. LLM APIs: Experience integrating and working with LLM model APIs (e.g., OpenAI, Azure OpenAI, Anthropic, Gemini). AI Specialization 2+ years specifically building with LLMs, with deep familiarity in: Orchestration: LangChain, LangGraph, or similar state-based frameworks. Vector DBs: Pinecone, Weaviate, or pgvector. Prompt Engineering: Advanced techniques (Chain-of-Thought, ReAct, Few-Shot). Production Mindset: Experience not just building demos, but operating them. You know how to handle rate limits, context window overflows, and non-deterministic errors. Soft Skills: Ability to explain “probabilistic software” to non-technical stakeholders—managing expectations that agents are never 100% accurate, but can be 100% useful. Communication: Excellent communication skills, with experience in documenting technical designs, sharing insights, and enabling team knowledge transfer. Nice to Have Microsoft Foundry What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

Location: Valencia Workplace: OnSite ROLE HIGHLIGHTS - Location: Valencia (Paterna), Spain - Reports to: VP Engineering, ICEYE Spain - Employment type: Permanent - Workplace model: Onsite, in the room with the team - SUPO: Employment is subject to applicable security screening. Parts of this work fall under export control. WHY THIS ROLE MATTERS ICEYE builds radar satellites, and nobody yet knows where AI turns a week of hardware design into an afternoon. The vendors who claim to know are mostly wrong. So we're setting up a five-person skunkworks in Valencia to find out, by building real hardware with AI - outside of the program schedules with a pure focus on finding the things that “move the needle”. You'll hire the team of four or five builders and build alongside them. "Lead" here means first builder. You get a room next to the lab and a budget you spend without an approval process, and the team keeps two standing obligations: build something every week and show it to the rest of ICEYE every month. WHO WE ARE ICEYE is the world leader in sovereign intelligence from space. We deliver persistent monitoring capabilities to detect and respond to changes in any location on Earth. ICEYE owns the world's largest and most advanced SAR (synthetic aperture radar) satellite constellation. To our customers we provide intelligence with unmatched quality, latency and revisit times, in any weather, day or night. To governments who choose to operate their own constellation we provide this proven capability as a sovereign system. ICEYE-built constellations serve customers in defence and intelligence, environmental monitoring, insurance and emergency management. We enable fast decisions that contribute to a safer future. Founded and headquartered in Finland, ICEYE operates globally with over 1000 employees across Europe, North America, the Middle East, and Asia-Pacific. YOUR DAY-TO-DAY RESPONSIBILITIES - Build the team: bring in 4 to 5 builders covering electrical (power and digital), RF, mechanical, and agents and tooling. You choose them, and the sponsor holds a veto. - Pick the problems and build them yourself: work only on real design intent, with real frequency bands, power levels, launch loads and interfaces. Think a representative X-band receive chain, a payload power distribution board, a bracket family or a digital backend. Toy problems teach us nothing about where AI breaks. - Run the bet portfolio: keep six to ten live bets, each with an owner and a one-line "this is dead if". The team reviews them monthly and decides to continue, graduate or kill. Roughly a third should die each quarter, including yours. - Hold the budget and spend it: you have full budget authority, with a same-day conversation with the sponsor for anything above 50k. Spend is reported in one table on the demo day slide, and that is the whole finance process. - Get what works into production hands: a capability has graduated when an engineer outside the team uses it without you in the room. That takes a working tool, a one-page how-to, the notebook pages behind it, and one of your people sitting with the receiving team for a month. - Run the team rhythm: something physical or runnable every week, and a public demo day every month that anyone at ICEYE can walk into. Failures get shown too, because they usually teach more. You won't write status reports or sit on steering committees. Spending below the limits needs nobody's permission. WHAT WE'RE LOOKING FOR We're looking for a tinkerer who finishes things. Both halves matter equally, and the combination is rare. You probably have a bench at home with something on it nobody asked for, and it works. You also have a day job designing real hardware to real requirements, so you know the difference between a clever prototype and a thing that survives launch. MUST HAVES - Hardware you designed and shipped yourself (circuit boards, RF chains, mechanisms or structures, any one of them), taken from intent to something measured on a bench - Instincts that come from hardware that got built, measured and signed off, including the judgement to tell when a simulation is lying to you - Code you're not embarrassed by, Python at minimum, because you'll be inside the agent loop daily - Hands-on use of modern AI tooling, with specific opinions about where it's useless - At least one unreasonable thing you built fast, and the ability to show it to us - Experience hiring people, or clear evidence that you know a builder when you meet one - Working English (Spanish helps and isn't required) NICE TO HAVES - Space, defence or another high-reliability domain, so qualification campaigns hold no surprises - Code-defined EDA or CAD, such as atopile, KiCad scripting, build123d or something you wrote yourself - Simulation in the loop (SPICE, FEA or full-wave EM), enough to know when the answer is wrong - Experience running a small team with its own money HOW YOU WORK - You're creative and you deliver. You start unreasonable things and finish enough of them, and you have taste in what to abandon. - You take risks deliberately. You'll spend two weeks attacking the thing everyone says can't be done, write down exactly how it failed, and stop. - You lead through change. You can keep four people steady while everything around them is uncertain, and help them tell the one result worth another month from the demo that will never survive a real requirement. - You're honest in the room. You can tell an executive or a vendor that something doesn't work, without softening it into a recommendation. This may not be the role for you if you want a predictable workday, if you need phases and gates to feel safe, if you lead mainly by reviewing other people's work, or your best story about building something is more than ten years old. WHAT SUCCESS LOOKS LIKE - First 4 weeks: the one-page charter is agreed with the sponsor and the team structure is defined. - By week 12: you've started building before hiring finishes, you and the team have chosen the first two or three design problems, and the bench has its first instruments. - End of month 3: first internal demo day, in whatever state things are in. That date doesn't move. - Over the 18 months: capabilities graduate into production use by engineers outside the team. APPLICATION PROCESS You've probably been turned down for jobs like this one. A CV that reads as scattered, a degree that doesn't match the title, a stint running your own thing that didn't become a company: we read that pattern as a plus. Send us your CV and show us what you built. Interview stages: 1. Recruiter Screen 2. Show us something you built and talk us through what went wrong in it. 3. Spend a day building something with us, on a real problem, with the tools you'd actually use. There's no case study, no panel and no competency grid. We discuss export control and personnel screening openly in the first conversation. WORKING AT ICEYE At ICEYE, you'll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win. HOW WE WORK (OUR VALUES) - Make the impossible possible: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way. - Be curious: Go deep, ask questions, listen carefully, and think critically. Understand the "why" behind decisions. - See the big picture: Stay close to what's happening across the company so you can make better decisions. Consider how your work affects others. - Drive effective teamwork: Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions. - Act as one team: We win together. We match tasks to the right owner and stay agile as priorities shift. - Have fun: What we do matters, and it should be enjoyable. Celebrate progress, take pride in results, and share the wins. BENEFITS Our benefits are designed to support your health and wellbeing, at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process. This role also comes with a competitive salary and equity. OUR COMMITMENT TO DIVERSITY, EQUITY, AND INCLUSION We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table. We're committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us, and we'll do our best to help. Apply now to start your ICEYE journey, and help us continue to make the impossible possible together. Read more about ICEYE and working with us at iceye.com http://iceye.com.

Location: United States (Remote) Workplace: Remote ROLE SUMMARY As AI agents move into production, they need a foundation that keeps them running through failures, retries, and long waits. Temporal is that foundation, and building AI-native experiences on top of it is paramount to where we are headed. We're looking for a technical, AI-native Staff Product Designer to shape how developers build, run, and scale agents on Temporal, from the agent platform and harness down to the compute and workers that execute them. You'll design with AI and for AI. You use AI as a core part of how you work, and you bring that fluency to the products developers use to run AI in production. You're comfortable going deep on how workers execute tasks, how compute scales, and what it costs, and you turn that depth into experiences that feel simple. This role owns a focused domain while spanning the full developer experience, well beyond our UI. WHAT YOU’LL DO - Design the experiences developers use to build, run, deploy, and observe agentic workloads on Temporal, across Agent Platform, Agent Harness, and Serverless Workers. - Shape the compute experience end to end, from configuring and scaling workers to understanding usage and cost. - Create future state prototypes with your design leadership that show where Temporal's agent and compute experiences are headed, giving Product and Engineering a concrete vision to align roadmaps around. - Work across the surfaces where developers meet Temporal, including the Cloud UI, CLI, SDKs, and documentation. - Design with AI as a daily practice, using it to explore, prototype, and test ideas faster, and bring that perspective into product decisions. - Partner with PMs and Engineers from discovery through delivery to define problems, validate direction, and ship at Temporal's pace and scale. - Contribute to and extend Temporal's Design System for agentic use cases, keeping our expanding product surface consistent. - Bring rigor to ambiguous, technical problem spaces, translating infrastructure complexity into interfaces that feel simple and clear. WHAT YOU’LL BRING - 8+ years of Product Design experience, including senior or staff-level ownership of complex, technical products, with a track record of influencing product direction through strong execution. - A solid understanding of compute and infrastructure concepts such as workers, scaling, queues, and resource usage, and the ability to discuss them credibly with engineers. - A portfolio that shows systems thinking and 0→1 work in developer tools, B2B or infrastructure products, dashboards, or similarly dense, data-heavy interfaces. - Experience designing AI-powered products or agent experiences. - Fluency with AI tools like Claude or Codex in your own design workflow, along with comfort in GitHub and terminal environments. - Hands-on experience with Figma. - Experience partnering directly with Engineering on technically constrained problems, ideally in developer tools, cloud infrastructure, or platform products. - Experience instrumenting and analyzing product usage to inform design decisions. - A bias for building. You prototype quickly, often in code or with AI, and you move through build, ship, learn, and iterate cycles in days rather than weeks. NICE TO HAVE - Working knowledge of distributed systems, workflow orchestration, or durable execution concepts. - Experience with serverless platforms, container orchestration, or cloud compute products. - Familiarity with agentic AI patterns and the challenges of running agents in production. - Familiarity with HTML, CSS, and JavaScript, and comfort reading code. Temporal Technologies is an Equal Opportunity Employer. Temporal Technologies does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status, or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need. We embrace and celebrate differences and diversity. Temporal is committed to providing access, equal opportunity, and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. If you need to request a reasonable accommodation, please let your Recruiter know so we can assist.

Location: Tel Aviv, HQ Workplace: OnSite We are looking for a Vertical Product Manager to own Wonderful's solutions for travel, transportation and hospitality: airlines, hotel groups, rail and ground transport, car rental, cruise, and travel technology. This role is responsible for the strategy, roadmap and go-to-market of repeatable solutions for these industries: products that solve a specific business problem for a travel operator and that we can sell and deploy again and again, in every country we work in. Our teams in the field already build valuable agents for travel and hospitality customers. As one of the first Vertical PMs, you will turn this field experience into a catalog of solutions that sales can pitch from the first meeting, and that our deployment teams can take to production faster each time. You will work closely with country GMs, Deployment Strategists, FDEs, HQ product groups, R&D and marketing. This vertical has two modes and a solution has to do both. On a normal day the job is commercial: bookings, changes, upgrades and extras. On a bad day, a cancelled flight or a storm, thousands of people need to be rebooked in the same hour and the agent is the only thing that can absorb the volume. A solution that only works on a quiet day will not be bought. WHAT YOU'LL DO - Drive the product vision, strategy and roadmap for Wonderful's travel, transportation and hospitality solutions, from the first solutions to a full catalog. - Identify the highest-value repeatable solutions, using what we have already built for customers in these industries, input from the field and market research. - Convert repeated customer needs into productized solutions rather than one-off builds, in partnership with HQ product groups and R&D. - Own the full solution offering for go-to-market, including demos, pricing, business case and reference deployments, so that solutions win deals in pre-sale. - Partner with marketing and sales on positioning, sales enablement and conversations with senior travel and hospitality buyers. - Build a deep understanding of airline, hotel and transport operations, buyer needs, seasonality and competitors, and use it to shape priorities. - Design for both modes of this industry, the growth day and the disruption day, and define how each is measured. Set what the solution must do when volume spikes and plans have to be rewritten at once. - Own the market rollout for each solution: which countries it enters and in what order, what has to change for it to work in each one, and how we grow penetration from there. A solution is judged by its total across every market, not by a single deal. - Lead a cross-functional team of engineers and designers from discovery to production, while maintaining team health. - Define and track the metrics that show each solution is working, and communicate progress to leadership. - Operate independently, think strategically and communicate clearly with executive and technical audiences. WHO YOU ARE - 5+ years of product management, solutions or strategy experience in B2B or enterprise software. - Experience building products for airlines, hotels, transport operators or travel technology companies, or working inside one. - Experience taking a product from customer discovery to repeatable sales. - Experience working closely with engineering, sales and customer-facing teams. - Experience presenting to and influencing senior executives. - AI-native PM with demonstrated ability to use AI tools to build prototypes and demos, and to redesign workflows. ADVANTAGES - Experience with AI agents, LLM-based products or workflow automation. - Experience in a pre-sales, solutions or forward-deployed role. - Knowledge of core travel processes and systems, such as reservations and booking, changes and cancellations, disruption handling and rebooking, loyalty programs, or property and fleet operations. - Experience with a product that had to hold up during a demand spike or a service failure. - Experience working across several countries or markets, or in a fast-growing startup. Candidate Privacy Notice https://www.wonderful.ai/careers/candidate_notice

Location: Intellias Meet your recruiter Bohdana Rubets bohdana.rubets@intellias.com https://www.linkedin.com... Vacancy details Data Engineering Data Engineer Senior Bulgaria, Croatia, Poland Remote APPLY NOW REFER A FRIEND Let’s breathe life into great tech ideas! With 3,000 people globally, Intellias is a company where benchmark technological solutions are born. Join in and take your part in digitalizing the world. What project we have for you Our client is building the standard path for governed data sharing across product services, analytics, and AI/ML. The Data Platform team owns the contracts, control mechanisms, publication paths, catalog metadata, lifecycle rules, lineage, permissions, and runtime building blocks that make reusable data safe and practical at scale. This is a role for someone who wants to shape a platform early, while working on concrete production problems from the start. Our client already has the production systems, Kafka backbone, PostgreSQL databases, analytical consumers, and AI/ML use cases that need a better data foundation. The challenge is to turn that reality into a standard path that engineers actually want to use. Our first milestone is focused: centrally managed publishing tables in service-owned PostgreSQL databases, captured through Debezium CDC into Kafka, and registered in DataHub with ownership, lifecycle, lineage, and impact-analysis metadata. Longer-term, the platform expands toward self-service data products, governed materialisations, durable shared state, and reusable data across the client’s operational and analytical systems. This is not a role where you only maintain an existing reporting pipeline. You will help design and build the platform path that other engineering teams use when they publish and consume shared data. What you will do Design and build platform services, tools, and workflows for contract-driven data publishing and consumption. Build the first production path for platform-managed PostgreSQL publishing tables, Debezium CDC, Kafka topics, and catalog registration. Create GitOps-style workflows where contracts, schemas, ownership, lifecycle, compatibility, policy metadata, and runtime desired state are reviewed, validated, and reconciled as code. Build tooling that gives product engineers fast feedback before they publish or change data products. Help define how client models data products, publishing contracts, schema evolution, field stability, deletion semantics, access policy, lineage, and cost attribution. Operate and improve the CDC runtime model, including Kubernetes workloads, source-specific isolation, offsets, schema history, heartbeats, signal channels, lag visibility, replay, resnapshotting, and recovery. Integrate platform metadata into DataHub so engineers can discover data products, understand ownership, trace lineage, and reason about the impact of changes. Work with product, infrastructure, data engineering, analytics, and AI/ML teams to make the standard path easier and safer than bespoke point-to-point integrations. What you need for this Strong experience building and operating production software systems, preferably in platform, infrastructure, backend, or data-intensive environments. Deep understanding of distributed systems trade-offs: reliability, idempotency, replay, eventual consistency, ownership boundaries, compatibility, and operational failure modes. Practical experience with PostgreSQL or other relational databases, including schema design, migrations, transactions, replication, or operational performance. Experience with Kafka, event streaming, CDC, Debezium, or adjacent data-movement technologies. Direct Debezium experience is valuable, but strong fundamentals matter more. Experience building software that other engineers use: CLIs, internal platforms, control planes, automation, CI validation, developer tooling, or self-service workflows. Familiarity with Kubernetes and cloud or infrastructure platforms, including runtime isolation, deployment, observability, and operational ownership. Ability to turn ambiguous architectural direction into practical increments, make trade-offs explicit, and deliver useful production systems without waiting for perfect certainty. Clear written and spoken communication in English. This role involves aligning multiple engineering teams around standards, contracts, and ownership boundaries. Nice to have: DataHub or other data catalog, lineage, or governance systems. Open table formats such as Apache Iceberg, object-store-backed data lakes, S3, BigQuery, ClickHouse, or analytical storage systems. GitHub Actions, policy-as-code, infrastructure-as-code, controllers, operators, or reconciliation-based systems. Data contracts, schema registries, Protobuf, Avro, JSON Schema, compatibility checking, field-level metadata, or contract testing. Experience supporting analytics, AI/ML, feature-store-style access patterns, or cross-domain product-service integrations. Experience with JVM languages and Python, TypeScript, Go, or Ruby. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

Location: London Workplace: remote ⚡️ About Merkle Science Merkle Science provides blockchain transaction monitoring and intelligence solutions for web3 companies, digital asset service providers, financial institutions, law enforcement and government agencies to detect, investigate and prevent illicit use of cryptocurrencies. Our vision is to make cryptocurrencies safe and provide infrastructure for the safe and compliant growth of cryptocurrencies. Merkle Science is headquartered in New York with offices in Singapore, Bangalore and London. The team has combined experience across Bank of America, Paypal, Luno, Thomson Reuters and Amazon. The company has raised over US$27 MM from SIG, Beco, Republic, DCG, Kenetic, GGV and several others. The Role You will design, build and run the systems behind our data products, covering ingestion, processing, analytical storage and serving. You own your work from the design document through to production. The people who design a pipeline also run it and answer for its numbers. Our stack is very wide, and we go deep in every part of it. We don't stop at "it works." We keep measuring, profiling and tuning to make systems faster, cheaper and more reliable. We want engineers who are razor sharp, pay close attention to detail, and care as much about why a query takes 800 ms as whether it returns the right answer. You don't need blockchain experience. If you're a strong data engineer who wants to learn it, we'd like to hear from you. What You'll Do Design and build scalable, high-throughput data pipelines and platform systems for blockchain data across 30+ chains. Build backend data services and loaders in Go and Python. Design and evolve data models and analytical workloads in ClickHouse, and tune them for sub-second queries. Build incremental, idempotent pipelines on Databricks over billions of rows and tens of terabytes. Keep improving the scale, reliability, freshness, performance and cost efficiency of the platform. Investigate hard performance and reliability problems and see them through to resolution. Work closely with the product, analytics and investigations teams that use the data, and turn their needs into platform designs. Help set technical direction through architecture discussions, design reviews and code reviews. Mentor engineers and help set strong engineering and operational practices. What You Bring 5+ years building and operating production data systems, including ETL and ELT pipelines. At least two of those years should be spent owning systems that other engineers depend on. Expert Python and strong SQL. You write typed, tested code, are comfortable with asyncio and concurrency, and have built incremental data models over billions of rows. Go for backend services. You have built and run high-throughput services or data loaders in Go in production. ClickHouse in production. You know MergeTree schema and sort-key design, materialised views, bulk loads and query tuning. Databricks in production. You have worked with PySpark, Delta Lake and Unity Catalog, designed incremental and idempotent tables, and kept an eye on compute cost. Large-scale data. You have hands-on experience with pipelines over billions of rows and tens of terabytes. You understand how partitioning, clustering and file sizing affect cost and latency. Kafka, Airflow and Kubernetes in production. You understand delivery semantics and idempotent writes, have handled backfills and failures, and have run data workloads with Docker and Helm. Google Cloud is preferred; AWS is fine. An operations and communication mindset. You instrument what you build, write runbooks and post-incident reviews, and can write a design document that a reviewer in another time zone can approve.   Nice to Have Blockchain data: EVM, UTXO or non-EVM chain data models, and pulling data from nodes over JSON-RPC or gRPC. Graph or distributed key-value stores: entity resolution or clustering on large graphs. Infrastructure as code, GitOps and observability: Terraform, Helm, ArgoCD, OpenTelemetry, Prometheus and Grafana, and load-test design. Experience building platforms that serve multiple data sources, datasets or product teams. AI-assisted development, and experience in fintech, compliance or AML. How We Work You'll join a small, senior team where everyone owns their work end to end. We make decisions based on measured evidence, not opinion. We keep design notes and runbooks next to the code. We test at production scale and run blameless post-incident reviews. We use AI coding tools every day, and we use judgement when reviewing what they produce. ❤️ Well Being, Compensation and Benefits We care about your well-being. Along with excellent health insurance, we offer flexible time off, learning & development initiatives and hours that are designed to provide work/life balance.  We regularly host team-building sessions and encourage discussions around mental health.   We reward talent and believe in acknowledging people for their contributions.  We offer industry-leading compensation, along with generous equity.  As a rapidly growing business, there are endless opportunities to grow your career with Merkle Science.

Location: New York Workplace: remote ⚡️ About Merkle Science Merkle Science provides blockchain transaction monitoring and intelligence solutions for web3 companies, digital asset service providers, financial institutions, law enforcement and government agencies to detect, investigate and prevent illicit use of cryptocurrencies. Our vision is to make cryptocurrencies safe and provide infrastructure for the safe and compliant growth of cryptocurrencies. Merkle Science is headquartered in New York with offices in Singapore, Bangalore and London. The team has combined experience across Bank of America, Paypal, Luno, Thomson Reuters and Amazon. The company has raised over US$27 MM from SIG, Beco, Republic, DCG, Kenetic, GGV and several others. The Role You will design, build and run the systems behind our data products, covering ingestion, processing, analytical storage and serving. You own your work from the design document through to production. The people who design a pipeline also run it and answer for its numbers. Our stack is very wide, and we go deep in every part of it. We don't stop at "it works." We keep measuring, profiling and tuning to make systems faster, cheaper and more reliable. We want engineers who are razor sharp, pay close attention to detail, and care as much about why a query takes 800 ms as whether it returns the right answer. You don't need blockchain experience. If you're a strong data engineer who wants to learn it, we'd like to hear from you. What You'll Do Design and build scalable, high-throughput data pipelines and platform systems for blockchain data across 30+ chains. Build backend data services and loaders in Go and Python. Design and evolve data models and analytical workloads in ClickHouse, and tune them for sub-second queries. Build incremental, idempotent pipelines on Databricks over billions of rows and tens of terabytes. Keep improving the scale, reliability, freshness, performance and cost efficiency of the platform. Investigate hard performance and reliability problems and see them through to resolution. Work closely with the product, analytics and investigations teams that use the data, and turn their needs into platform designs. Help set technical direction through architecture discussions, design reviews and code reviews. Mentor engineers and help set strong engineering and operational practices. What You Bring 5+ years building and operating production data systems, including ETL and ELT pipelines. At least two of those years should be spent owning systems that other engineers depend on. Expert Python and strong SQL. You write typed, tested code, are comfortable with asyncio and concurrency, and have built incremental data models over billions of rows. Go for backend services. You have built and run high-throughput services or data loaders in Go in production. ClickHouse in production. You know MergeTree schema and sort-key design, materialised views, bulk loads and query tuning. Databricks in production. You have worked with PySpark, Delta Lake and Unity Catalog, designed incremental and idempotent tables, and kept an eye on compute cost. Large-scale data. You have hands-on experience with pipelines over billions of rows and tens of terabytes. You understand how partitioning, clustering and file sizing affect cost and latency. Kafka, Airflow and Kubernetes in production. You understand delivery semantics and idempotent writes, have handled backfills and failures, and have run data workloads with Docker and Helm. Google Cloud is preferred; AWS is fine. An operations and communication mindset. You instrument what you build, write runbooks and post-incident reviews, and can write a design document that a reviewer in another time zone can approve.   Nice to Have Blockchain data: EVM, UTXO or non-EVM chain data models, and pulling data from nodes over JSON-RPC or gRPC. Graph or distributed key-value stores: entity resolution or clustering on large graphs. Infrastructure as code, GitOps and observability: Terraform, Helm, ArgoCD, OpenTelemetry, Prometheus and Grafana, and load-test design. Experience building platforms that serve multiple data sources, datasets or product teams. AI-assisted development, and experience in fintech, compliance or AML. How We Work You'll join a small, senior team where everyone owns their work end to end. We make decisions based on measured evidence, not opinion. We keep design notes and runbooks next to the code. We test at production scale and run blameless post-incident reviews. We use AI coding tools every day, and we use judgement when reviewing what they produce. ❤️ Well Being, Compensation and Benefits We care about your well-being. Along with excellent health insurance, we offer flexible time off, learning & development initiatives and hours that are designed to provide work/life balance.  We regularly host team-building sessions and encourage discussions around mental health.   We reward talent and believe in acknowledging people for their contributions.  We offer industry-leading compensation, along with generous equity.  As a rapidly growing business, there are endless opportunities to grow your career with Merkle Science.

Location: Home-based, Mauritius Workplace: OnSite Company Description We’re http://checkout.comCheckout.com http://Checkout.com. You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day. We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers. Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale. If you want to do career-defining work, you’ve come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact. With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech – and we’re just getting started. As a Level 2 Analyst, candidates will be at the heart of our financial ecosystem, ensuring the reliability and efficiency of our payment flows. Candidates will bridge the gap between technical engineering and operational excellence, using data, programming skills, and automation to optimize our core systems. We are looking for an individual with an Athlete Mindset who plans with rigor and constantly seeks more ambitious goals for our monitoring and reporting infrastructure.   KEY RESPONSIBILITIES 1. Operational Discipline & Daily Rigor - Daily Health Checks: As part of Ops engineering team, we are responsible for investigating and remediating transactional failures. We have automated dashboards that run periodically and raise alerts in case of failures - candidates will be expected to master daily checks (investigations and remediation) as this is the core priority of the team. - Incident Response: Candidates are expected to monitor real-time payment alerts, triage performance degradations, and drive issues to closure with a sense of urgency (Pace Matters). - Documentation: We are constantly taking work away from Engineering teams - candidates are expected to maintain and update Standard Operating Procedures (SOPs) for daily tasks, ensuring No Room for Approximation in our execution. 2. Payment Flow Expertise & Scheme Reporting - Lifecycle Management: Maintain a clear understanding of the end-to-end payment lifecycle, including authorization, clearing, and settlement across various payments methods - Card transactions, APMs, PTB etc. - Scheme Reporting: Accurate preparation and submission of reporting for Card Schemes (e.g., Visa, Mastercard), ensuring all data aligns with scheme-specific requirements. Candidates will be expected to investigate how we can reduce manual toil by automating our reporting - aim is 100% accuracy within SLA. - Data Validation: Use a data-driven approach to reconcile internal transaction records against scheme reports to identify and resolve discrepancies. - Compliance Support: Assist in the monitoring of scheme-mandated KPIs and reporting deadlines to ensure the business remains in good standing. 3. Technical & Automation Excellence - Data Analysis (SQL): Candidates are expected to write and optimize SQL queries to extract actionable insights from large datasets when required, keep our monitoring tools (Monte Carlo, Retool, BigQuery) up to date and assist peers with payment related queries. - AI & Automation: Proactively identify repetitive manual tasks and use AI tools or scripting to automate them, supporting our goal to Run Lean. Candidates will be expected to provide tangible results e.g. Number of hours saved, on use of AI and Automation. - Monitoring & Alerting Workflows: Work closely with Engineering to refine and update internal monitoring and alerting workflows, ensuring we maintain an Athlete Mindset toward system health. - Engineering Collaboration: Act as a technical bridge, taking initiative to solve minor bugs or configuration issues, embodying the Be the Owner principle - Continuous Improvement: Adopt a Better Every Day approach by researching new technical tools to enhance monitoring and reporting efficiency. 4. Soft Skills & Team Dynamics - High-Pressure Performance: Candidates should thrive in a fast-paced environment, remaining resilient and focused during critical system incidents (Never Give Up). - Collaboration: Act as a proactive One Team player, sharing knowledge with peers and communicating complex technical issues clearly to non-technical stakeholders. - Accelerated Learning: Demonstrate a desire to learn fast and adapt to new payment technologies and evolving regulatory landscapes. 5. On-Call Duties & Availability - In-Hours Support: Act as the primary technical point of contact for operational health during standard business hours. - On-Call Roster: Participate in a rotating on-call roster, where you may be called upon to support the platform outside of normal working hours to ensure 24/7 reliability. - Weekend & Shift Work: Be prepared to work outside of normal hours and during weekends as required by the business to maintain system uptime and address urgent issues. - Resilience: Demonstrate a Never Give Up attitude, showing resilience and accountability when handling high-priority alerts during off-peak hours. QUALIFICATIONS - Education: Bachelor’s degree in Computer Science, Finance, Engineering, or a related field. - Experience: 2+ years of experience in an operations support or payments-focused role. - Hard Skills: - Proficiency in SQL (data extraction and analysis). - Experience with automation tools or basic scripting (Python/JS is a plus). - Familiarity with AI tools for task optimization and productivity. - Operating Values: You must embody our values by being Fundamentally Positive and acting as an Owner of your work area. Additional Information Bring all of you to work We create the conditions for high performers to thrive, through real ownership, fewer blockers, and work that makes a difference from day one. Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where ambition gets met with opportunity, and where your growth is in your hands. We work as one team, and we back each other to succeed. So whatever your background or identity, if you’re ready to grow and make a difference, you’ll be right at home here. It’s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable. Life at Checkout.com http://Checkout.com We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection. Curious about what it’s like to be part of our team? Visit our Careers Page https://www.checkout.com/careers to learn more about our culture, open roles, and what drives us. For a closer look at daily life at Checkout.com http://Checkout.com, follow us on LinkedIn https://www.linkedin.com/company/checkout/life/ and Instagram https://www.instagram.com/checkout_com/

Responsibilities: — Build agentic tools — Develop evaluation systems — Create engineering workflow infrastructure The role involves working with infrastructure, data pipelines, LLMs, failure analysis, multi-agent orchestration, RAG, tool calling, evaluation, MCP, software engineering, DevOps, chip development, fine-tuning, agents, GPU kernels, and context management. Location: San Jose, CA, onsite.

You’ve got the spark, the curiosity that makes you ask “why?” when others move on. You love solving puzzles, learning new tools, and understanding how things work (and how they break).

Location: USA Flex is a growth-stage, NYC headquartered FinTech company that is building the payment layer for life's financial obligations, giving households one place to see, split, and pay their bills around how they live and get paid. By offering greater choice over how and when payments are made and allowing eligible on time payments to help build a positive credit history, Flex puts households back in control of their cash flow. That work brings together people with different perspectives who challenge the status quo and take ownership of solving difficult problems. For you, that means doing the best work of your career next to people who make you better, and together bringing ideas to life that make a real impact for the people we serve. About the role Flex is looking for a Staff Software Engineer to build and scale our Fraud and Payment Risk Platform . You will lead the architecture and hands-on development of backend services and shared infrastructure for fraud prevention and payment risk decisioning. The platform combines real-time, near-real-time, and offline/batch-computed risk features with business rules, machine learning model outputs, and experimentation. You will make these capabilities reliable, scalable, and observable, enabling teams to develop, validate, and launch risk strategies faster and more safely. This is a hands-on backend and platform role with technical ownership from architecture through production. You will collaborate with product, risk policy, data science, and engineering teams to turn risk strategies into reusable platform capabilities. Your scope includes feature ingestion and integration, user acceptance testing (UAT), experimentation, and engineering infrastructure supporting the full machine learning (ML) lifecycle—from development and validation workflows through deployment, serving, and production monitoring—in partnership with data scientists who own model research and training. What you’ll do Lead backend architecture and development for the Fraud and Payment Risk Platform, including decisioning services, APIs, and shared infrastructure for evolving business needs. Design for scalability, performance, and reliability , balancing latency, throughput, availability, data consistency, and cost. Build capabilities for feature ingestion, integration, and serving , supporting real-time, near-real-time, and offline/batch-computed features with attention to freshness, correctness, and availability. Develop infrastructure for rules and experimentation , enabling teams to configure and version risk strategies, perform user acceptance testing (UAT), evaluate changes, and safely roll them out. Own engineering infrastructure across the ML lifecycle , supporting development and validation workflows, deployment, inference, versioning, safe rollouts, rollback, and integration of model outputs into risk decisions. Own monitoring and alerting across the platform , covering service health, feature freshness and quality, rule and experiment execution, and model inference. Partner with risk policy and data science teams to monitor model behavior and decision outcomes. Improve platform extensibility and usability , so teams can add features, rules, models, and experiments without duplicating infrastructure or tightly coupling systems. Drive complex initiatives from design through production , including technical design proposals, hands-on implementation, performance testing, migration planning, and cross-team coordination. Raise the engineering bar through design and code reviews, mentorship, and improvements to testing, documentation, deployment safety, and operations. Our backend stack includes Java, Spring Boot, Python, and AWS . Qualifications Minimum qualifications 6+ years of professional software engineering experience, including substantial experience building and operating backend systems in production. 5+ years of hands-on Java experience, including building services with Spring Boot. Experience leading the architecture and delivery of complex distributed systems or shared backend platforms. Strong understanding of API design, service integration, data modeling, caching, and distributed-system failure modes. Experience diagnosing performance bottlenecks and improving scalability and reliability through measurement, testing, and production troubleshooting. Experience with cloud infrastructure, containerized deployments, and relational and NoSQL data stores. Experience establishing observability, monitoring, and alerting for production systems. Ability to lead technical decisions across teams, communicate architectural trade-offs clearly, and mentor other engineers. Preferred qualifications Experience building risk platforms, decision engines, or fraud/payment risk systems is a plus, though risk-domain experience is not required Experience with feature platforms, configurable rules engines, experimentation infrastructure, or production model-serving systems. Experience building shared platforms that other engineering or risk teams adopt and operate independently. Familiarity with AWS services such as EKS, Aurora, ElastiCache, and DynamoDB. Experience with infrastructure as code and CI/CD automation using tools such as Terraform, CDK, and GitHub Actions. Familiarity with tools such as Datadog for observability and Snowflake for analytics. Compensation Flex takes a market-based approach to pay, and compensation may vary depending on your primary work location. Work locations are categorized into one of three tiers based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be commensurate with their experience, qualifications, and Flex’s internal leveling guidelines and benchmarks. Tier 1 (NYC/Bay Area, Los Angeles, Seattle) $200,000 — $250,000 USD Tier 2 (Austin, Washington D.C. Philadelphia, San Diego, Chicago, Atlanta) $180,000 — $225,000 USD Tier 3 (Salt Lake City, all other USA cities) $170,000 — $212,500 USD Life at Flex Building a successful company takes a diverse team of intelligent, curious, determined, empathetic, and self-aware people. Our headquarters is in New York City, with employees across the US, Australia, Canada, and South America. We’re growing quickly and deliberately, with a focus on building an inclusive culture. We value the perspectives our people bring and take pride in being an equal opportunity workplace. Offices Roles posted in New York, San Francisco, and Salt Lake City are hybrid positions with on-site expectations of 2-3 days per week in our local offices. For candidates outside of these areas, you may be eligible for our relocation assistance program. Benefits View our benefits and more at getflex.com/careers .

Location: Remote - Ireland Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as Twilio’s next Staff SRE, Platform Engineering About the job Twilio is looking for a Staff Site Reliability Engineer to join our Platform Engineering organization. SRE owns production health and resiliency at Twilio — we are accountable for whether our services stay available, performant, and recoverable for the customers who build their businesses on us. SREs here are software engineers who focus on reliability: you will architect systems with reliability designed in from the outset, define the SLIs and SLOs that determine whether we are meeting customer expectations, and build the automation that keeps our infrastructure efficiently ahead of capacity and performance demand. At the Staff SRE you work without day-to-day guidance, applying deep subject-matter knowledge and industry-leading practice to improve the products, processes, and services that Twilio runs on. You will own the reliability posture of significant parts of our production estate. Your impact will be felt across multiple teams rather than within one. This is a hands-on engineering role. You will write and deploy code that improves service reliability, orchestrate complex changes across systems, lead the response when production is degraded, and raise the quality bar for the engineers around you. Responsibilities In this role, you’ll: Own the reliability posture of production services in your area — availability, latency, capacity, efficiency, performance, and the monitoring and alerting that makes them visible Define, instrument, and operate against SLIs and SLOs, and use error budgets to drive engineering priorities Identify trends and problem areas that threaten stability, and provide a path forward to mitigate risk before it reaches customers Drive down repair items and prevent classes of incidents rather than resolving them one at a time Improve detection, response, and recovery — reducing time to acknowledge, engage, mitigate, and restore, with fewer people pulled in Design for failure: strengthen failure domains, validate recovery paths, and make production changes safer to ship and safer to roll back Participate in on-call for the services you support, and lead the response when production is degraded Write post-mortems that identify true root causes, and drive the follow-up work to completion Oversee efforts to identify, diagnose, report, and document production problems across all reliability dimensions Write, configure, and deploy code that measurably improves service reliability — maintainable, reviewed, documented, and well tested Orchestrate complex changes across systems and services, documenting design changes, technical decisions, migration plans, and upgrades Lead debugging, troubleshooting, and analysis of service architecture and design Use code review to drive up the quality of your coworkers' code Reduce the operational overhead required to run infrastructure and services Drive projects from conception to completion for efforts spanning the concerns of your team Coordinate across programs, collaborating with others to estimate and communicate delivery timelines Break projects into milestones and tasks, track progress, and communicate updates to stakeholders Identify and communicate changes that may impact stability Qualifications Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table! *Required: 8+ years of related engineering experience, with a substantial portion focused on reliability, infrastructure, or platform engineering Demonstrated accountability for production systems — you have carried a pager for services that mattered and owned the outcome when they failed Strong software engineering fundamentals: you build and ship production code, not only configure tooling Experience defining and operating against SLIs and SLOs, and using error budgets to inform engineering priorities Depth in production operations: incident command, post-mortem analysis, capacity planning, and observability A record of preventing recurrence — reducing incident classes and operational toil, not just closing tickets Experience driving changes that span multiple teams, and the communication skills to build alignment without formal authority A track record of improving the engineers around you through code review, design feedback, and mentorship Experience with large-scale distributed systems in a cloud environment Desired: Familiarity with infrastructure-as-code, container orchestration, and GitOps-style delivery Experience with multi-region architecture, failure-domain design, or regional expansion work Background in chaos engineering, game days, or other proactive resilience validation Location This role will be remote, and based in Ireland. Travel We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings. What We Offer Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location. Twilio thinks big. Do you? We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call Twilio Magic . Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts. So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for, please consider other open positions. . Stay alert to recruitment fraud We care about your safety. Scammers sometimes impersonate Twilio recruiters through fake job postings, emails, websites, or messages. Please ensure you are engaging with an official @ twilio.com email address. We will never ask for payment, gift cards, cryptocurrency, or banking information during the recruiting process. We do not make job offers without a formal interview process or conduct interviews exclusively through text-based messaging apps. . Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

Location: United States About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . The Role Turing builds large-scale datasets and reinforcement learning (RL) environments that power post-training for the world's leading AI labs and enterprises. The STEM Horizontal team produces the high-signal coding and STEM data frontier labs train on. We're looking for a Research Engineering Manager to lead the research engineering behind its next layer: synthetic data that measurably improves models, and new benchmarks that measure what today's evals miss. You'll lead a team of research engineers, work side by side with research scientists, and stay close enough to the code to review an eval harness line by line or prototype a generator yourself when the team needs it. You'll also build the team : hiring research engineers is a core part of this role, not a side task. Ideally you've been on the other side, at a frontier lab, and know what makes a lab trust a dataset or a benchmark result. Synthetic data that earns its place. Generation, verification, and filtering pipelines where every sample is checked, and where we can show which properties of the data drive downstream gains, not just how much of it we made. Benchmarks that stay meaningful. New evaluations for capabilities current benchmarks miss, built with calibrated difficulty, contamination controls, and statistics strong enough that a lab can make a decision on the result. Quality failures here are quiet. A subtle bug in a verifier doesn't crash anything; it ships thousands of wrong labels into someone's training run and costs weeks. If you want to build the team and the systems that catch that early, this is the seat. What You'll Do 1. Build and Lead the Team Build the team: define the profiles you need, run hiring, and grow research engineers selected for research taste as much as engineering rigor. Run the team's operating rhythm: project selection, planning, experiment reviews, design docs, and clear ownership. Coach engineers on experimental design, code quality, and presenting results; give direct, regular feedback and run fair performance cycles. Define the standards the team works to: eval methodology, data quality bars, and reproducibility — every dataset and result can be regenerated from a commit, a config, and a seed. 2. Partner with Research Scientists Turn hypotheses into experiment plans together: what we're testing, the baseline, the ablations, and the result that would change our minds. Set the agenda with research scientists. You're expected to bring your own hypotheses, not only implement theirs. Take research prototypes to production scale without losing the scientific intent. 3. Build Synthetic Data Systems at Scale Own synthetic data pipelines that generate, verify, filter, deduplicate, and version data, combining programmatic generators, LLM-based generation, automated verifiers, and targeted expert review. Judge data by its effect on models : ablations and fine-tuning or RL experiments that show which attributes (difficulty, diversity, correctness, coverage) drive gains. Build quality systems that hold up at volume: gold sets, LLM-judge calibration against expert labels, sampling audits, and agreement metrics. 4. Create New Benchmarks and Evaluations Find where frontier models fail and where existing benchmarks have saturated, and design evaluations that measure what's missing . Own benchmark methodology end to end: task taxonomy, difficulty calibration, graders and verifiers, contamination controls, held-out splits, and confidence intervals. Ship eval harnesses , including agentic and sandboxed-execution evals, that are deterministic, reproducible, and trusted by internal teams and partner labs. Make the call on whether a result holds up: partner labs and internal teams act on your sign-off. Publish benchmarks, datasets, and findings with our research scientists at venues such as NeurIPS, ICML, and ICLR. 5. Stay Hands-On and Work with Frontier Labs Write code every week on the hardest, highest-leverage parts: core verifier logic, eval statistics, the pipeline component everything else depends on. Expect a third or more of your time on direct technical work. Be the person the team brings its hardest debugging and methodology questions to: why a judge disagrees with experts, why an eval number moved, whether a gain is real or noise. Act as a technical counterpart to researchers at frontier AI labs: scope requests, set acceptance criteria, and explain results and trade-offs plainly. Partner with Strategic Project Leads, delivery, and engineering teams so research advances land in client work and in the platforms the team builds. Sample Projects Identify a capability gap, design and ship a benchmark for it, and see it adopted by partner labs. Stand up a synthetic data pipeline for long-horizon coding tasks with execution-based verifiers, and run the ablations that show which task properties drive RL gains. Calibrate an LLM-judge grading system against expert labels, map where it fails, and decide where humans stay in the loop. Design the experiment that tells a partner lab whether a two-point gain on their eval is real. Decide which of three competing synthetic data approaches the team should bet on, and design the experiments that settle it. Tech Stack Research: Python · PyTorch or JAX · SFT · DPO · PPO / GRPO · RL with verifiable rewards Evals & data: LLM-as-judge · programmatic verifiers · sandboxed execution · gold sets · contamination checks Platform: Python services (Django / FastAPI) · PostgreSQL · Docker · Terraform · AWS or GCP What We're Looking For Experience: 8+ years of hands-on ML or research engineering, at least 5 in industry, including 3+ years directly managing research engineers, ML engineers, or researchers (hiring and performance management included). Synthetic data at scale: you've owned synthetic or curated data pipelines in production whose output drove training decisions , and can show how you measured their quality and downstream impact. Evaluation rigor: you've designed and shipped LLM evals or benchmarks that others used to make model decisions, and understand contamination, saturation, judge bias, inter-annotator agreement, variance, and confidence intervals. Experimental judgment: you plan ablations up front, choose baselines honestly, and can tell a real effect from noise. Technical depth: strong Python; production experience with PyTorch or JAX; working knowledge of the post-training stack (SFT, DPO, PPO/GRPO, RL with verifiable rewards). Technical direction: a track record of setting direction for a team, not only executing a roadmap handed to you. Scale: distributed data processing and large evaluation or training jobs (e.g., Ray, Spark, Kubernetes) on AWS or GCP. Communication: clear written communication for scientists and non-specialists alike; comfortable presenting results to researchers at partner labs. AI-forward: daily use of LLM coding tools (Claude Code, Cursor, Copilot) as part of how you ship, with the judgment to review their output critically. This is a must-have. Education: PhD or Master's degree in AI, machine learning, computer science, statistics, or a closely related field; PhD preferred. Exceptional equivalent research experience will also be considered. We weigh industry outcomes most heavily. Strongly Preferred Frontier AI lab experience: post-training data, evals, or reward modeling at a frontier lab (e.g., OpenAI, Anthropic, Google DeepMind, Meta, xAI) or a top industry research group. Built or contributed to a public benchmark or dataset the community uses. Nice to Have First-author papers at NeurIPS, ICML, ICLR, ACL, EMNLP, or similar. RL environment and verifier design for agentic tasks: coding agents, tool use, computer use, long-horizon workflows. Data valuation or attribution: measuring what each slice of data contributes to a model. Depth in a STEM domain such as math, physics, chemistry, or biology (not required). Experience managing tech leads or managers, or running several concurrent programs. Directing large expert networks through specs, rubrics, and fast feedback loops. A note from our CTO, Ece Kamar Some of the most important questions in AI can't be answered from inside a single lab: how to evaluate frontier models, how data and RL truly drive capability, and what happens when AI meets the real world. At Turing, we work directly with frontier labs, the academic community, and enterprises deploying AI at scale. That creates a feedback loop where deployment shapes our research and our research shapes the field, and we publish our findings, datasets, and benchmarks openly. Join our talented team at Turing to push the frontier of AI with rigorous science that matters. Why Turing Work directly with leading AI labs and enterprises at the frontier of post-training, evaluation, and synthetic data. Build the datasets and benchmarks that improve and measure the capabilities of advanced AI systems. Shape how frontier labs measure progress on coding and STEM reasoning. Operate with high autonomy, rapid iteration, and meaningful commercial impact. Collaborate with exceptional colleagues from organizations including Google, Meta, Amazon, and other leading technology companies. Contribute to research that may be shared through technical publications and leading conferences such as ICLR, ICML, and NeurIPS. Compensation $260,000 to $350,000 + Equity Don't meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive, and authentic workplace and celebrate authenticity, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here. Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Location: New York, NY (HQ) Workplace: Hybrid ABOUT RAMP Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. ABOUT THE ROLE Buying software and services is still slow and fragmented at most companies. Employees don't know how to request what they need, approvals stall across finance, legal, and security, purchase orders live in a separate system from the bills that pay them, and finance teams spend month-end matching it all together by hand. Ramp's Procurement team builds the system that connects every step of that process, from the first purchase request through sourcing, approvals, purchase orders, receiving, and matching bills and contracts back to what was ordered. Procurement sits upstream of payments and works closely with Bill Pay, Accounting, and ERP integrations, so the systems we build shape how money leaves a business long before a payment goes out. We're looking for a senior backend engineer to own a core part of that system. You'll take responsibility for a product area such as the purchase order lifecycle, PO and bill matching, PO coding and accruals, or supplier and ERP integrations, set its technical direction within the team, and keep it healthy as customers and complexity grow. You'll work closely with product, design, and data partners to turn enterprise purchasing workflows into software that is flexible, auditable, and simple to use. WHAT YOU'LL DO - Own the design and evolution of a core Procurement system, such as purchase orders, receiving, or PO, bill, and contract matching, from technical design through launch, monitoring, and iteration - Build flexible request, intake, and approval workflows that handle the policies, approval chains, and audit requirements of complex organizations - Design data models that keep purchase orders, receipts, bills, and accounting data accurate and traceable from request to payment - Build and improve integrations with ERPs and supplier systems that stay consistent through retries, partial failures, and edits on either side - Help build AI-assisted features, such as automated PO coding and intelligent matching, that reduce manual work for finance and procurement teams - Drive technical direction for your area, connecting long-term system health to the team's roadmap - Work cross-functionally with product, design, and data, and with partner teams across Bill Pay, Accounting, to ship features across the full procurement lifecycle - Raise the engineering bar through design reviews, code reviews, and mentorship WHAT YOU'LL NEED - Experience designing, building, and operating production backend systems, including APIs, data models, and asynchronous workflows - A track record of owning a system or product area end to end: spotting problems before they are assigned, proposing the fix & working with relevant stakeholders, and shaping the area's technical direction over time - Strong system design judgment, especially around data correctness, auditability, and keeping complex workflows understandable - Product sense: you care about the customer problem, can work through ambiguous enterprise requirements, and push back when the spec is wrong - Clear communication and a collaborative approach to technical decisions across product, design, and engineering NICE TO HAVES - Experience with procurement, purchasing, accounts payable, or other B2B finance workflows - Experience building integrations with ERPs or other systems of record, such as NetSuite, QuickBooks, or Sage Intacct - Experience integrating with punchout catalogs, cXML, and other supplier facing integrations - Experience building configurable workflow or approval engines for enterprise customers - Experience applying LLMs or other automation to structured business workflows BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL) - Flexible PTO - Centralized home-office equipment ordering - Health and wellness stipend - Budget for intra-office travel - Weekly coffee stipend UNITED STATES - 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents - One Medical annual membership - 401(k), including employer match on contributions made while employed by Ramp - Fertility HRA (up to $10,000 per year) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay - Pet insurance - In-office perks: lunch, snacks, drinks, and more - Relocation expense coverage to NYC or SF (if needed) CANADA - Group medical, dental, and vision coverage through Sun Life - Life, AD&D, and disability coverage - Fertility drug coverage (up to $4,000 lifetime) - Group Retirement Plan with employer match (RRSP + DPSP) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay - Employee Assistance Program and virtual care through Lumino Health UNITED KINGDOM - Private medical insurance through Freedom Elite - Virtual GP and at-home care via eMed x Livi - Workplace pension through Penfold, with salary sacrifice option - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.   OTHER NOTICES Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.   Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.   Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice

Location: United States; Brazil; United Arab Emirates; Ireland; Peru; Sweden; Colombia; Argentina; Romania; Cyprus; Switzerland; Portugal; Lithuania; South Africa; Czech Republic; Canada; Hungary; Mexico; Chile; Poland; Spain; United Kingdom; Bulgaria Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Bitnomial is building the next generation US-based global derivatives exchange, starting with digital assets and progressively expanding to encompass a full spectrum of commodities worldwide. Bitnomial operates a US CFTC regulated exchange (DCM), clearinghouse (DCO), and brokerage (FCM). It offers a range of crypto-settled derivatives, including futures, options, and a suite of live perpetual futures, used by brokers, hedge funds, institutions, and trading firms around the world. Bitnomial's exchange, clearinghouse, and brokerage systems are written largely in Haskell. In this role you will build the services and data models that record every order, fill, and settlement at a CFTC-regulated exchange and clearinghouse, with the database as a first-class part of the design. You will build features across these systems and design the schema, queries, and migrations behind them.   THE OPPORTUNITY - Improve build and release pipelines in GitHub Actions: caching, parallelism, pinned toolchains, and required tests and scans before production - Manage AWS infrastructure as code with Terraform, and run services as containers on Nomad - Build deployment tooling with health checks and automated rollback, and make deploys safe around market sessions - Add metrics and alerts to the services you build, so you can see whether a deploy worked - Monitor systems, respond to alerts, and support daily operations such as settlement cycles - Fix the cause of production issues and write down what you learned - Build, test, and ship well-reviewed features and fixes in our services across the exchange, clearinghouse, and brokerage. Most of the code is Haskell - Understand the order, trade, clearing, and settlement flows end to end   WHAT YOU BRING - Hands-on experience with CI/CD pipelines, such as GitHub Actions or GitLab CI - Production experience with AWS and Docker, and infrastructure as code with Terraform - Strong Linux and scripting skills (Bash, Python, or similar) - 3+ years of professional software engineering experience with a functional or strongly typed programming language such as Haskell, Rust, or C++ - Solid computer science fundamentals, including distributed systems: failure modes, retries and idempotency, consistency, and how to observe them across services - Willingness to take part in on-call and operational shifts - Care and rigor with code that moves money - Good judgment with AI tools. You use them to work faster, and you read, test, and understand what they produce before you ship it - A habit of asking why before changing something - Sound judgment under pressure, with a calm and methodical approach when production is live - Collaboration across engineering, operations, risk, and compliance, with a habit of documenting   NICE TO HAVES - Financial knowledge or experience in trading, markets, or financial services - Bachelor's degree in computer science or a related field, or equivalent experience - Experience with Nomad or Kubernetes - Experience with Nix, Ansible, Vault, or Prometheus, Grafana, and Loki - Haskell experience Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on X https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice