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Location: Remote Poland At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. About the Engineering team The Engineering team builds systems that power Affirm’s mission. We take pride in our craft, building reliable, performant, and scalable solutions that touch every part of the business. Whether we’re enabling new ways to pay, ensuring our platforms can scale to the most demanding levels in the industry, or developing seamless servicing experiences, our focus is on solving complex problems through exceptional engineering. About the team Affirm’s Communications team builds and modernizes the highly available platform that delivers billions of customer messages reliably and on time across the customer journey. As a senior backend engineer, you will shape multi-region, multi-tenant infrastructure, APIs, and vendor integrations that help product teams communicate with customers at scale. What you’ll do You will own and deliver quarterly technical goals for the Communications area, collaborating with teammates to solve ambiguous, open-ended problems across messaging infrastructure. You will design and evolve reliable backend services for high-volume communications across multi-region, multi-tenant environments, including orchestration, delivery, preferences, templates, and observability. You will collaborate with product management, design, analytics, security, and engineering partners throughout the product lifecycle, articulating technical constraints and balancing customer impact, risks, and trade-offs. You will design, implement, and operate resilient integrations with external messaging vendors, balancing reliability, latency, cost, and compliance. You will proactively identify and solve project, process, technology, or business issues that affect scalability, developer experience, and operational resilience. You will support the operations and availability of your team’s services by defining service-level objectives and metrics, improving alerting and incident response, and participating in on-call efforts. You will foster quality and ownership by improving design, testing, code review, rollout, and operational standards, and advocating for them through writing and tech talks. You will help develop talent on your team by providing feedback, mentorship, and technical direction, and leading by example. On-Call Rotation - There would be an on-call rotation for this role as a requirement. What we look for You have 5+ years of experience in software development or engineering, with a deep understanding of system design and architecture. Proficiency in modern programming languages such as Python, Kotlin, or similar. You have a track record of developing highly available distributed systems using technologies like AWS, MySQL, DynamoDB, and Kubernetes. You have experience designing multi-region, multi-tenant platforms with strong isolation, scalability, failure recovery, and data-consistency guarantees. You have experience integrating with third-party communications or messaging vendors and designing abstractions that account for different capabilities, rate limits, and failure modes. You have experience defining a technical plan for the delivery of a significant feature or system component with an elegant, simple and extensible design. You write high quality code that is easily understood and used by others. You are proficient at making significant changes in a large code base, and have developed a suite of tools and practices that enable you and your team to do so safely. You are proficient with AI-assisted development tools and apply sound judgment to validate their outputs. Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders. You have strong verbal and written communication skills that support effective collaboration with our global engineering team. Total rewards We believe the people building honest financial products at Affirm should share in its success. That's why our total rewards are designed to support your health, growth, financial well-being, and future. In service of our mission, we reward employees through a combination of base pay, equity (from parent company), and comprehensive benefits. Base Pay Grade - N 308,000 zł  -  428,000 zł Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company). Base pay ranges and placement within those ranges are determined based on several factors, including role, experience, and job-related skills. In addition to base pay, all employees in this role are eligible to receive equity from the parent company each year. This means as Affirm’s parent company grows, employees have the opportunity to share in that growth financially. Equity Grade - 4 (awarded in US Dollars) Affirm Holdings, Inc. Equity Grade example Equity grade: 4 New hire equity: $32,000-$48,000 Annual Refresh: $10,000 Reward equity: $0-$150,000 Affirm also provides flexible spending wallets to all employees for technology and wellbeing related needs, which are reimbursable up to 1390 zł per month. In addition to your compensation, our comprehensive benefits are designed to support you and the people who matter most. Benefits include: Competitive paid time off, paid public holidays, and additional paid Away Days to rest and recharge. Comprehensive private healthcare through Lux Med's Platinum package. A MultiSport card to support your health and well-being. Learning and development programs to help you grow professionally. Family healthcare support through Maven and parental leave support through Parentaly. Mental well-being support through Lyra, including up to 12 confidential counseling or coaching sessions each year for you and your household members. Financial well-being support through Northstar, with unlimited access to Certified. Financial Advisors and planning tools at no cost to you. Employee Resource Groups (ERGs) that foster connection and inclusion. Eligibility for creative tax benefits, subject to applicable law, role, and company policy. Location - Remote Poland The majority of our roles can be located anywhere in Poland. **This job description is not a contractual document, and is not intended to have binding force.** #LI-Remote Remote-first with flexibility built in Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience. Benefits designed for you Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights: Health coverage at no cost: We cover 100% of premiums for employees and their dependents. Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you. Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to. Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount. We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help. For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

Location: Remote Spain At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. About the Engineering team The Engineering team builds systems that power Affirm’s mission. We take pride in our craft, building reliable, performant, and scalable solutions that touch every part of the business. Whether we’re enabling new ways to pay, ensuring our platforms can scale to the most demanding levels in the industry, or developing seamless servicing experiences, our focus is on solving complex problems through exceptional engineering. About the team Affirm’s Communications team builds and modernizes the highly available platform that delivers billions of customer messages reliably and on time across the customer journey. As a senior backend engineer, you will shape multi-region, multi-tenant infrastructure, APIs, and vendor integrations that help product teams communicate with customers at scale. What you’ll do You will own and deliver quarterly technical goals for the Communications area, collaborating with teammates to solve ambiguous, open-ended problems across messaging infrastructure. You will design and evolve reliable backend services for high-volume communications across multi-region, multi-tenant environments, including orchestration, delivery, preferences, templates, and observability. You will collaborate with product management, design, analytics, security, and engineering partners throughout the product lifecycle, articulating technical constraints and balancing customer impact, risks, and trade-offs. You will design, implement, and operate resilient integrations with external messaging vendors, balancing reliability, latency, cost, and compliance. You will proactively identify and solve project, process, technology, or business issues that affect scalability, developer experience, and operational resilience. You will support the operations and availability of your team’s services by defining service-level objectives and metrics, improving alerting and incident response, and participating in on-call efforts. You will foster quality and ownership by improving design, testing, code review, rollout, and operational standards, and advocating for them through writing and tech talks. You will help develop talent on your team by providing feedback, mentorship, and technical direction, and leading by example. On-Call Rotation - There would be an on-call rotation for this role as a requirement. What we look for You have 5+ years of experience in software development or engineering, with a deep understanding of system design and architecture. Proficiency in modern programming languages such as Python, Kotlin, or similar. You have a track record of developing highly available distributed systems using technologies like AWS, MySQL, DynamoDB, and Kubernetes. You have experience designing multi-region, multi-tenant platforms with strong isolation, scalability, failure recovery, and data-consistency guarantees. You have experience integrating with third-party communications or messaging vendors and designing abstractions that account for different capabilities, rate limits, and failure modes. You have experience defining a technical plan for the delivery of a significant feature or system component with an elegant, simple and extensible design. You write high quality code that is easily understood and used by others. You are proficient at making significant changes in a large code base, and have developed a suite of tools and practices that enable you and your team to do so safely. You are proficient with AI-assisted development tools and apply sound judgment to validate their outputs. Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders. You have strong verbal and written communication skills that support effective collaboration with our global engineering team. Compensation & Benefits Pay Grade - N Equity Grade - 4 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company). ESP base pay range per year: €86,000 - €122,000 Additional benefits include: • Flexible Spending Wallets for tech, food and lifestyle • Away Days - wellness days to take off work and recharge • Learning & Development programs • Parental benefits • Employee Resource & Community Groups Location - Remote Spain We are able to offer visa sponsorship for this role, but do require that someone is based in Spain for the role. #LI-Remote Remote-first with flexibility built in Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience. Benefits designed for you Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights: Health coverage at no cost: We cover 100% of premiums for employees and their dependents. Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you. Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to. Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount. We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help. For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

Location: Europe or US About the SQL Console Team The SQL Console team operates with a great degree of autonomy inside ClickHouse, building the rich web interfaces, interactive query environments, data visualization dashboards, and dynamic AI agents that developers use daily to interact with ClickHouse Cloud. We solve extreme UI performance and scalability challenges that only a handful of tech companies in the world ever reach. We are builder-first, heavily leverage modern AI coding tools like Cursor and Claude, and give engineers end-to-end product ownership. What You Will Do - Build highly interactive React web applications, developer tools, and IDE extensions handling real-time, high-throughput data streaming. - Optimize frontend rendering performance, state management, and DOM virtualization for large-scale datasets and complex visualizations. - Write high-performance Node.js / Express services when API, data streaming, or backend optimizations are required. - Act with a founder mindset: take ambiguous product problems, architect clean solutions, and ship maintainable code with high autonomy. - Leverage modern AI development tools (Cursor, Claude, Codex) as force multipliers to ship features rapidly. What We Are Looking For - React Architecture Depth: Deep expertise in building complex, state-heavy web applications in React (Zustand, Redux, TanStack Query, or Context API). - Rendering & Data Viz Performance: Proven ability to handle high-volume data rendering using DOM virtualization (react-window), Canvas/D3.js, or memoization techniques. - Full Stack Comfort (Node.js): Strong hands-on experience writing asynchronous Node.js / Express microservices and streaming APIs. - Founder / Builder Mindset: Previous experience as a startup founder, side-project creator, or early engineer who thrives in fast-paced environments without rigid specifications. Nice to Haves - Experience building VS Code extensions, web-based IDEs, query editors (Monaco), or developer tools. - Hands-on experience with ClickHouse or columnar real-time databases. PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: New York City, NY; New York City, NY | Seattle, WA; Remote-Friendly, United States; San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is looking for Software Engineers to join the Memory & Search team. We own how Claude remembers you and how it finds what it needs, across Claude.ai, Cowork and Claude Code. That spans the user-facing experience (what Claude remembers, how people see and edit it, how search surfaces the right conversation) and the shared infrastructure underneath it, the memory service, indexing, retrieval and vector search. Memory is one of the biggest levers on whether Claude feels like it knows you. We recently moved memory from a periodically synthesized summary to a dynamic, editable, on-demand system, and then unified it so the same memory follows you across products. Search went from a top user complaint to something people rely on to find past work. The platform is now in place, and the next phase is finding the product form factors that make memory the most compelling and sticky part of using Claude. That is why we are hiring product engineers. The team is strong on infrastructure, and we want people who have shipped user-facing products at scale, have a sharp sense for what makes a product feel good, and have built agentic systems where the model, the tools and the user interface have to work together. You will run short, demo-driven experiments on top of the memory and search stack, decide what to keep based on real usage, and help the whole team think like a product team. If you have founded a company, been an early engineer at a startup, or taken a product from zero to one, you will recognize the way we want to work. This is a trust-sensitive surface. Memory touches privacy, consent and enterprise controls, so you will work closely with product, design, privacy, legal and safeguards, and you will be expected to treat those constraints as part of good product design rather than obstacles to it. Key responsibilities Design, build and ship memory and search experiences in Claude.ai, Cowork and Claude Code, owning them end to end from the backend service through the model's tools to the user interface Run product experiments on the memory and search stack: form a hypothesis, build a demo, put it in front of real users, measure, and make a clear persevere-or-pivot call Shape how Claude uses memory and retrieval inside its agentic loop, including what the model stores, when it searches, how results are ranked and presented, and how the user stays in control Define and track the metrics that tell us whether memory is actually making Claude more useful, and build the evaluations that keep quality honest as the system evolves Improve search relevance and recall across conversations and memories, working across embeddings, hybrid retrieval and ranking as well as the interface that presents results Partner with product, design, privacy, legal and safeguards to ship features that respect user consent and enterprise requirements such as customer-managed encryption keys and data retention policies Raise the bar on product quality for the team through design reviews, code reviews and the standards you set for latency, polish and reliability Share the on-call for the systems you own Minimum qualifications Experience building and operating user-facing products used by a large number of people, including the backend services behind them Experience building agentic systems or LLM-powered products, including tool use, retrieval and prompt or context design Strong programming skills in Python and TypeScript, with experience across backend services and web front ends A track record of taking a product or feature from an idea to launch, and iterating on it based on usage data and user feedback Experience defining product metrics and running experiments to make decisions Strong product judgment: you notice when something feels off and you fix it, and you can explain why a design choice matters to users Strong written and verbal communication, with experience working closely with product managers, designers and non-engineering partners Interest in AI safety and Anthropic's mission Preferred qualifications Experience as a founder, early-stage engineer, or someone who has taken a product from zero to one Experience building search or retrieval systems: embeddings, vector search, hybrid lexical and semantic retrieval, or ranking Experience building evaluations for LLM or ML systems, or measuring the quality of retrieval and ranking Experience on consumer products with strong retention, or on personalization systems Experience shipping features that handle sensitive data or meet enterprise requirements such as customer-managed encryption keys, data residency or HIPAA Experience with latency-sensitive, performance-critical product work Experience mentoring engineers or setting technical direction for a team The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

About the Position Design and develop state-of-the-art algorithms, automation, and services in support of a cloud-based service that helps our customer resolve identities across their fleet of databases.

Location: San Francisco; Seattle; New York City ABOUT THE ROLE The Enterprise Agent Evals & Efficiency team makes Perplexity's agents better at completing real work across enterprise connectors, tools, and data. Our goal is to help agents choose the right tools, use the right context, and complete complex workflows reliably, with less time and compute. This team owns the improvement loop: define what successful work looks like, build evaluations that measure it, understand where agents fail, and ship changes that improve outcomes. This is a hands-on engineering role with end-to-end ownership, from building realistic enterprise evaluation environments to shipping improvements across the agent harness, tools, and skills. You'll create complex scenarios spanning connected systems, data, and permissions, use them to identify where agents struggle, and improve the tools agents call, the skills they follow, the context they receive, and the models they use. Working with AI Research, Connectors, and Platform teams, you'll turn experimental results into measurable gains in task success, latency, and cost per successful task. The goal is not just to measure agents, but to make more enterprise work reliable and practical to automate. KEY RESPONSIBILITIES - Build realistic enterprise evaluation environments spanning connected applications, representative datasets, user roles, and permissions, with complex, multi-step workflows and reproducible system state. - Own evaluation infrastructure, task suites, and automated graders that measure how well agents complete enterprise work, calibrated against human judgment and grounded in end-to-end outcomes. - Analyze agent trajectories and production failures, identify root causes, and ship improvements across the agent harness, tools, and skills that measurably improve task success and reliability. - Develop reusable skills and improve tool descriptions, schemas, and result handling so agents can select the right tools, execute workflows correctly, and recover from errors with fewer unnecessary calls. - Build and evaluate model-selection and routing strategies that match each task to the right model and effort level, balancing quality, latency, reliability, and cost. - Improve agent efficiency through context management, skill loading, caching, and execution strategies that reduce wasted tokens and cost per successful task without compromising quality or safety. - Build regression gates and launch-readiness signals for model, connector, tool, skill, and harness changes, and validate that evaluation gains translate into better production outcomes. QUALIFICATIONS - 5+ years of software engineering or machine learning engineering experience, with a track record of owning complex production systems from design through deployment and operation. - Strong system design skills, including building reliable, scalable infrastructure for experimentation, evaluation, or data-intensive applications. - Strong proficiency in a backend language such as Python, Go, or Rust, and the ability to work effectively across a multi-language production stack. - Hands-on experience building, evaluating, or improving LLM-based applications or agents, including tool use and multi-step workflows. - Deep expertise in at least one of the following: - Evaluation infrastructure, benchmark design, and automated grading. - Agent harnesses, tool interfaces, and reusable skills for complex workflows. - Realistic test environments or simulations spanning multiple systems, datasets, permissions, and stateful workflows. - Model selection, routing, and inference efficiency, including context management and caching. - Strong experimental and statistical judgment, including choosing representative tasks, defining meaningful success criteria, diagnosing failures, and distinguishing real improvements from noise. - Sound technical judgment in balancing task quality, latency, reliability, and cost, with a track record of translating evaluation findings into shipped improvements. - A track record of leading ambiguous, cross-team initiatives from architecture through production adoption, setting technical direction, and raising engineering quality through mentorship. If you’re excited about this role, we encourage you to apply even if you don’t meet every qualification. We value demonstrated impact, deep ownership, and the initiative to turn ambiguity into results.

Location: San Francisco; Seattle; New York City ABOUT THE ROLE The Enterprise Agent Evals & Efficiency team makes Perplexity's agents better at completing real work across enterprise connectors, tools, and data. Our goal is to help agents choose the right tools, use the right context, and complete complex workflows reliably, with less time and compute. This team owns the improvement loop: define what successful work looks like, build evaluations that measure it, understand where agents fail, and ship changes that improve outcomes. This is a hands-on engineering role with end-to-end ownership, from building realistic enterprise evaluation environments to shipping improvements across the agent harness, tools, and skills. You'll create complex scenarios spanning connected systems, data, and permissions, use them to identify where agents struggle, and improve the tools agents call, the skills they follow, the context they receive, and the models they use. Working with AI Research, Connectors, and Platform teams, you'll turn experimental results into measurable gains in task success, latency, and cost per successful task. The goal is not just to measure agents, but to make more enterprise work reliable and practical to automate. KEY RESPONSIBILITIES - Build realistic enterprise evaluation environments spanning connected applications, representative datasets, user roles, and permissions, with complex, multi-step workflows and reproducible system state. - Own evaluation infrastructure, task suites, and automated graders that measure how well agents complete enterprise work, calibrated against human judgment and grounded in end-to-end outcomes. - Analyze agent trajectories and production failures, identify root causes, and ship improvements across the agent harness, tools, and skills that measurably improve task success and reliability. - Develop reusable skills and improve tool descriptions, schemas, and result handling so agents can select the right tools, execute workflows correctly, and recover from errors with fewer unnecessary calls. - Build and evaluate model-selection and routing strategies that match each task to the right model and effort level, balancing quality, latency, reliability, and cost. - Improve agent efficiency through context management, skill loading, caching, and execution strategies that reduce wasted tokens and cost per successful task without compromising quality or safety. - Build regression gates and launch-readiness signals for model, connector, tool, skill, and harness changes, and validate that evaluation gains translate into better production outcomes. QUALIFICATIONS - 5+ years of software engineering or machine learning engineering experience, with a track record of owning complex production systems from design through deployment and operation. - Strong system design skills, including building reliable, scalable infrastructure for experimentation, evaluation, or data-intensive applications. - Strong proficiency in a backend language such as Python, Go, or Rust, and the ability to work effectively across a multi-language production stack. - Hands-on experience building, evaluating, or improving LLM-based applications or agents, including tool use and multi-step workflows. - Deep expertise in at least one of the following: - Evaluation infrastructure, benchmark design, and automated grading. - Agent harnesses, tool interfaces, and reusable skills for complex workflows. - Realistic test environments or simulations spanning multiple systems, datasets, permissions, and stateful workflows. - Model selection, routing, and inference efficiency, including context management and caching. - Strong experimental and statistical judgment, including choosing representative tasks, defining meaningful success criteria, diagnosing failures, and distinguishing real improvements from noise. - Sound technical judgment in balancing task quality, latency, reliability, and cost, with a track record of translating evaluation findings into shipped improvements. - A track record of leading ambiguous, cross-team initiatives from architecture through production adoption, setting technical direction, and raising engineering quality through mentorship. If you’re excited about this role, we encourage you to apply even if you don’t meet every qualification. We value demonstrated impact, deep ownership, and the initiative to turn ambiguity into results.

Lambda is looking for a Senior Software Engineer to build Kubernetes control-plane services, automate cluster lifecycle management, and support AI infrastructure.

Own system architectural vision and design for critical areas of our business. Transform high-level system vision into estimated project plans for initiatives central to Squarespace’s strategy.

Own substantial connectivity work: Lead multiple medium-to-large features or service components from problem definition through design, implementation, validation, release readiness, and operational handoff.

What you will do Collaborate with UX designers, Product Management, and engineering teams to deliver robust security features alongside an optimal user experience. Work cross functionally with product squads and go-to-market teams to ensure smooth release of new features and products.

Location: Almaty, Kazakhstan Workplace: OnSite Almaty, Kazakhstan · Trust & Safety Engineering Why this role exists Our ML and analytics teams already work on fraud detection and risk analysis. This role owns the backend that turns their signals into reliable protections across accounts, credits, payments, and generation. You'll integrate risk checks into product flows, build enforcement services and operator tools, and make sure controls work correctly in production. We're looking for an engineer we can trust to take a backend problem from an unclear starting point to a working solution. What you'll actually do - Risk integrations: connect existing ML scores and risk signals to account creation, credit usage, payments, and generation flows, with clear timeouts and fallback behavior. - Enforcement services: implement configurable rules, rate limits, account restrictions, and credit or payment controls with consistent behavior across services. - Operator tooling: build APIs and workflows for reviewing cases, inspecting decision history, and safely applying or reversing restrictions. - Production reliability: handle retries, duplicate events, concurrent requests, and safe rollouts; add monitoring and audit trails so failures can be traced and fixed. - Work in other teams’ codebases to add signals or interventions without hurting their stability or architecture. - Ownership: clarify the control with ML, analytics, and operations → scope the smallest useful implementation → ship → verify production behavior and review impact with the team. Our release cycle is days, not quarters, so your first shipped protection happens fast. Must-haves 1. You've taken a difficult problem from an unclear starting point to a working system used in production, and can explain your own decisions, contribution, and results. 2. You can build reliable backend services: APIs, data models, queues, transactions, idempotency, and concurrency. You can integrate external services and debug failures across the request and event lifecycle. 3. You choose the next steps, remove blockers, and ask for help when needed. You cut scope to test an idea, adapt from evidence, and keep working through difficult problems. 4. You work with ML, analytics, and operations to turn risk requirements into clear backend behavior. You use operator feedback and customer cases to improve controls and learn unfamiliar systems quickly. 5. You take feedback, change your mind when the evidence changes, and do the work the team needs. You share knowledge and responsibility so others can operate and extend what you build. Who this is not for - You prefer problems where requirements stay stable after launch. - You prefer work centered on training models or producing analysis rather than building and operating backend services. Nice to have - Fraud prevention, payments risk, or platform abuse experience. - Integrating risk-scoring services or building rules engines and rate limiters. - Case management, appeals, and risk operations tooling. - Familiarity with Stripe. - Experience building real-time scoring, graph-based account linkage systems. - Python/Go experience. Interview process 1. Recruiter screen: role expectations, logistics, and fit. 2. Technical interview: a difficult system you shipped, what you personally decided and built, and how your work made the team more capable without leaving it dependent on you. 3. Additional technical interview, if needed: a deeper discussion of technical skills and open questions. 4. Product fit interview: take an existing risk signal and an operator need, scope a backend protection, and work through failure cases and effects on legitimate customers. 5. Offer. What we offer Competitive base in USD, equity, relocation support, and ownership of protections that preserve both company revenue and customer trust.

Location: Almaty, Kazakhstan Workplace: OnSite Almaty, Kazakhstan · Trust & Safety Engineering Why this role exists An agent needs more than a model response to complete useful work. It needs tools, durable execution, permissions, context, and a way to recover when something fails. You'll build the backend that lets Higgsfield agents carry creative tasks from a user's request to a finished result. We're looking for an engineer we can trust with a problem: work out what is worth building, build it, and carry it through to users. What you'll actually do - Agent execution: build orchestration for multi-step tasks, tool calls, streaming updates, and cancellation. - Durable workflows: implement checkpoints, resumability, retries, and recovery without duplicating actions. - Tools and integrations: connect agents to generation, editing, and external services through clear, validated interfaces. - Execution boundaries: enforce user permissions, tenant isolation, resource limits, and approval requirements for consequential actions. - Evaluation and observability: trace failures, build regression cases, and improve task completion, latency, and cost. - Ownership: understand a real user task → define success and build evaluation cases → scope the simplest useful workflow → ship → measure completion, reliability, and dollar impact → improve from failed runs. Our release cycle is days, not quarters, so your first shipped agent capability happens fast. Must-haves 1. You've taken a difficult problem from an unclear starting point to a working system used in production, and can explain your own decisions, contribution, and results. 2. You can build reliable agent execution: state machines, concurrency, queues, recovery, model APIs, secure tool calls, and repeatable evaluations. You learn unfamiliar tools quickly and understand what you ship. 3. You choose the next steps, remove blockers, and ask for help when needed. You cut scope to test an idea, adapt from evidence, and keep working through difficult problems. 4. You investigate real user tasks and failed agent runs, use feedback to choose what to automate, and stop workflows that do not help users finish their work. 5. You take feedback, change your mind when the evidence changes, and do the work the team needs. You share knowledge and responsibility so others can operate and extend what you build. Who this is not for - You prefer deterministic application behavior without investigating model uncertainty. - You prefer prototyping without owning evaluation, recovery, and production reliability. Nice to have - Production agents, workflow engines, or developer tools. - High-throughput systems with heavy traffic, large data volumes, or many long-running jobs. - Agent context management, memory, subagents, or parallel tool calls. - Sandboxed execution and scoped authorization. - Multimodal workflows involving images, video, or audio. Interview process 1. Recruiter screen: role expectations, logistics, and fit. 2. Technical interview: a difficult system you shipped, what you personally decided and built, and how your work made the team more capable without leaving it dependent on you. 3. Additional technical interview, if needed: a deeper discussion of technical skills and open questions. 4. Product fit interview: scope a useful tool-using workflow, evaluate failures, and explain when user feedback would lead you to change or stop it. 5. Offer. What we offer Competitive base in USD, equity, relocation support, and ownership of systems that turn AI capabilities into completed creative work.

Location: Almaty, Kazakhstan Workplace: OnSite Almaty, Kazakhstan · Trust & Safety Engineering Why this role exists Higgsfield builds tools for AI creators: creative workflows, collaborative projects in Cinema Studio, and a community for sharing work. We need a backend engineer who combines deep database and architecture expertise with the initiative to own product outcomes, from the first idea to production. What you'll actually do - Build AI creation workflows, Cinema Studio collaboration, and community features: sharing, discovery, contests, profiles, and follows. - Own features and bugs through release and follow-up. Define API contracts and coordinate frontend work to deliver the complete feature. - Deliver responsive UX: live progress, timely updates, and clear failure recovery, even when it takes more engineering effort. - Remove database and service bottlenecks under high traffic; improve correctness, latency, and reliability. - Define success metrics, build dashboards and alerts, and track adoption and system health after launch. Must-haves 1. Deep database expertise: data modeling, indexes, query plans, partitioning, transactions, and locking. You diagnose production bottlenecks and understand the trade-offs behind your fixes. 2. Strong architecture judgment: service boundaries, APIs, asynchronous workflows, caching, and failure handling. Hands-on Kubernetes and CI/CD experience, from design and testing to deployment and debugging. 3. A track record of shipping and operating backend systems across multiple projects, including high-traffic workloads. You can explain your decisions and measurable results. 4. API security: authentication, object-level authorization, and tenant isolation. You prevent IDOR in reads and writes, including resource IDs in request bodies, and test access across users and workspaces. 5. You've built or studied social networks and collaborative tools, and can explain design trade-offs in feeds, follow graphs, notifications, sharing permissions, real-time sync, and concurrent edits. 6. High agency and ownership: you find worthwhile problems, propose improvements, remove blockers, and follow through without waiting for assignments. 7. Low ego: you welcome direct feedback, admit mistakes, change your mind with evidence, and help wherever the team needs you. 8. Ambition and optimism: hard goals and rapid growth energize you. You challenge assumptions constructively and commit to making ambitious ideas work. 9. Energy for an intense pace, shifting priorities, and urgent launches or production issues that can require work outside regular hours. Our tech stack - Languages and frameworks: Python (FastAPI), Go (Gin), and TypeScript (React/Next.js on the frontend). - Data: PostgreSQL and Redis; analytical databases such as BigQuery or ClickHouse. - Messaging: Kafka, Amazon SQS, and RabbitMQ; event-driven services and asynchronous workers. - AWS: S3, DynamoDB, ECR, and Secrets Manager. - Infrastructure: Docker, Kubernetes on Amazon EKS, Helm, Argo CD, and GitHub Actions. - Observability: Prometheus, Grafana, OpenTelemetry, and Sentry. Interview process 1. Recruiter screen: role expectations, logistics, and fit. 2. Technical interview: a difficult system you shipped, what you personally decided and built, and how your work made the team more capable without leaving it dependent on you. 3. Additional technical interview, if needed: a deeper discussion of technical skills and open questions. 4. Product fit interview: turn a user problem into a small first release, decide what to leave out, and explain how feedback would change the solution. 5. Offer. What we offer Competitive base in USD, equity, relocation support, and ownership of product experiences that directly shape how people create with AI.

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— Поддержка и развитие AI-сервиса на Python и LangChain. — Интеграция LLM-моделей, разработка AI-агентов и RAG-систем.

Location: Remote Workplace: remote 🌎 About Us TeamSnap is made up of innovators, technologists, builders, and problem-solvers shaping the future of youth sports. We’ve been setting the standard in youth sports technology since we were founded in 2009.  We hire for big ideas and tiny egos — which is part of how we landed on Outside Magazine's Best Places to Work, Built In's 100 Best Remote-First Places to Work and, for several years running, Sports Business Journal’s Best Places to Work in Sports.   TeamSnap is seeking a Staff Software Engineer (Android) to lead advertising on our next-generation Android app. You'll set the technical direction for how ads come to life in the app: designing a scalable, privacy-conscious ad platform and building ad experiences that feel native to how families use TeamSnap. Along the way, you'll help shape the architecture of a modern Kotlin and Jetpack Compose app used by millions. We’re looking for critical thinkers who are excited to jump in and make an impact! We're looking for people with big ideas and tiny egos. No matter what your “job” is, you’re welcome to suggest better ways of doing anything. Our team values collaboration in a remote culture, so we regularly participate in pair sessions and virtual team swarms to stay connected and improve the team and company. What You'll Do: Architect and evolve TeamSnap's Android ad platform as a reusable, well-tested layer the whole app can build on Deliver display, native and video ad experiences across the app that fit naturally with the product Build privacy and consent into the ad stack from day one, in partnership with Legal/Privacy Make sure our app loads fast, renders smoothly, and is a delight to use Partner with Brands & Advertising, Product, Design and Data to define the roadmap, measure revenue and engagement impact, and iterate Shape the broader architecture of our Kotlin and Jetpack Compose app, including modularization and build health Lead cross-team technical initiatives through design docs, RFCs and hands-on work; mentor engineers and set Android standards with our iOS team What You'll Bring: Extensive experience building and shipping Kotlin Android apps at scale, including technical leadership at Staff level or equivalent Deep hands-on experience with Google Ad Manager on Android: native custom formats, key-value targeting, ad lifecycle and refresh, and debugging fill and delivery problems Experience with ad verification and measurement: DoubleVerify, IAS, or Open Measurement (OM SDK) and viewability Strong experience with modern Android: Jetpack Compose, Coroutines/Flow, Hilt, and multi-module architecture A track record of designing systems from scratch and leading them through launch across teams Nice to Have: Experience shipping video ads, such as the Google IMA SDK with ExoPlayer/Media3 or similar Ads in live streams (SSAI, ad breaks in live content), or experience with Amazon IVS Experience with apps for families or youth, and COPPA considerations BLE hardware integrations, or subscriptions (Play Billing, RevenueCat, Superwall) 🖥 Location TeamSnap is a fully remote company, so you'll need to be comfortable working with people in other time zones. We're always expanding, but we can't currently hire in Alabama, Alaska, Delaware, District of Columbia, Hawaii, Iowa, Louisiana, Mississippi, Nebraska, New Mexico, Rhode Island, South Dakota, West Virginia, or Utah. We can only hire permanent US residents at this time. 🚀 Opportunities to Grow We work hard on a culture built on trust, accountability, and inclusion — one where you can take on more, make a lasting impact, and have some fun doing it. 🎩 Total Rewards Remote-first since 2009 Flexible PTO and parental leave 100% premium coverage of medical, dental, and vision for you and your family 401(k) to invest in your future $1,500 annual learning and development reimbursement Travel to all-company meetings and team events Generous home office allowance TeamSnap swag when you start, plus a $50 store credit on every work anniversary Monthly health and wellness reimbursement, and more TeamSnap Total Rewards 🏆  Award-winning Culture At TeamSnap, you're not a culture fit – you're a culture add. Read our Culture Playbook to see how we play, what we ask of each other, and what drives us. 🧡 Inclusion and Diversity Creativity and innovation don't come from cookie-cutter teams. We hold ourselves accountable for building a culture where everyone is valued. Need any accommodations during the interview process? Just ask. We are an Equal Employment Opportunity Employer. AI Notice We may use AI tools to support parts of the hiring process, such as reviewing applications and resumes or assessing responses. These tools assist our recruitment team; they don't replace human judgment, and final hiring decisions are made by people. Contact us if you'd like more information about how your data is processed.