Вакансии

Location: São Paulo or Rio de Janeiro, Brazil Why Join Exadel We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next. What powers it all? Our people are ambitious, collaborative, and constantly evolving. About the Client A leading global digital banking platform and one of the largest neobanks in Latin America, headquartered in Brazil. The company provides a mobile-first suite of financial services—including credit cards, savings accounts, and investments—designed to eliminate bureaucracy and high fees. By leveraging advanced data analytics and a customer-centric digital infrastructure, the organization delivers transparent and accessible financial solutions to millions of users across Brazil, Mexico, and Colombia. What You’ll Do Design, build, test, and maintain AI agent capabilities, including tools, skills, commands, and prompts Apply prompt-engineering techniques to improve agent accuracy, reliability, and usability Define structured output contracts, error-handling mechanisms, and evaluation methods for measuring agent behavior Develop extensions, plugins, and integrations for AI-powered development tools Build and maintain reusable application templates that establish consistent engineering standards across generated projects Develop developer-facing interfaces and internal tooling using React and TypeScript Improve the developer experience through actionable feedback, clear error messages, reliable defaults, and streamlined workflows Implement and maintain quality gates, including type checking, linting, automated testing, and build validation Apply containerization and runtime standards to support secure and consistent application development Collaborate with platform engineers to integrate AI capabilities with infrastructure, CI/CD pipelines, and deployment workflows Monitor platform usage, identify friction points, and continuously improve the experience based on observed behavior and user feedback Document technical decisions, agent behavior, platform capabilities, and development workflows Incorporate AI agents into daily engineering activities and identify opportunities to improve their effectiveness What You Bring A solid foundation in application architecture, software engineering, and modern development practices Hands-on experience designing and implementing AI agents, including tools, skills, commands, and prompt engineering Experience evaluating AI agent behavior systematically using defined criteria, test cases, and supporting evidence Experience with React and TypeScript, including modern frontend development patterns and build tooling Experience building reusable application templates, developer tools, internal platforms, or self-service engineering capabilities Knowledge of automated testing, type checking, linting, build validation, and software-quality practices Familiarity with containerization and application runtime environments Working knowledge of cloud infrastructure, CI/CD concepts, and application deployment workflows Strong technical English skills, including written documentation and remote collaboration Strong analytical and problem-solving abilities with excellent attention to detail Ability to work independently, navigate ambiguity, and take ownership of technical outcomes Interest in incorporating AI agents into everyday engineering workflows and continuously improving their performance Nice to have Experience developing plugins, extensions, or integrations for AI-powered development environments Experience using Python for supporting services, automation, or AI-related workflows Familiarity with enterprise application security, governance requirements, and engineering guardrails Experience designing structured agent interfaces, typed outputs, and robust error-handling mechanisms Understanding of cloud-native architectures, CI/CD pipelines, and production deployment practices Experience improving developer productivity through internal platforms, reusable templates, or self-service tooling Exposure to AI evaluation frameworks, observability, or agent performance monitoring English level Upper-Intermediate Work Type: Remote Eligible Locations: São Paulo or Rio de Janeiro, Brazil Legal & Hiring Information Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more Reasonable accommodations are available to enable individuals with disabilities to perform essential functions Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs Compensation details are shared with candidates at the early stage of the recruitment process. The offer is not binding until a signed contract is in place. Your Benefits at Exadel Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details. International projects In-office, hybrid, or remote flexibility Medical healthcare Recognition program Ongoing learning & reimbursement Well-being program Team events & local benefits Sports compensation Referral bonuses Top-tier equipment provision Exadel Culture We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Design and build production RAG systems and AI agents. Run open-source LLMs self-hosted, from model selection to serving and optimization.

* Giving all our riders an excellent customer experience by the channels that we are available on. * Making sure that you are on top of our product/processes to provide the right information to all our riders.

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.

-Разработка Web-интерфейса Агента AI PDLC. -Участие в принятии архитектурных решений.

-Разрабатывать и поддерживать backend-сервисы на Python (FastAPI, asyncio). -Развивать логику диалогового агента: сценарии и состояния звонка, извлечение данных из реплик, работу с LLM.

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.

You will take an agent surface from operational research through specification, prototype, evaluation, and enterprise deployment, working hands-on throughout. Agent definition.

Mirage is looking for a Software Engineer Agents to build and deploy reliable agentic systems for creative video workflows.

- Сильный опыт в ML, Deep Learning, NLP и LLM. - Практический опыт создания AI-продуктов, работающих в production и в большом масштабе.

Location: Remote - Canada What We’re Building Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023! If you want to see what we’ve been up to, please check out these blog posts and Honeycomb.io press releases . Who We Are We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live our values every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers. How We Work We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote Little more about the team: The team builds observability for AI in Honeycomb. We help customers see what their agents are doing, what those agents cost, and where errors happen. We also give them insight into individual conversations so they can debug them. We're bringing LLM and agent observability together, and we own both the data foundation and the product experiences built on top of it. You'll work in a small, cross-functional group of engineers with a dedicated product manager and designer, shipping features customers use in production. If you want to define how people understand and debug AI systems, this is the team for you. What you’ll do in the role: Deliver AI observability capabilities end to end, from ingestion to in-product visualizations. Contribute to the data model and infrastructure that let us observe agents and their ecosystems across the Honeycomb product. Build systems that analyze and surface AI-specific signals, such as cost, token usage, errors, and anomalies. Collaborate with product and design partners to make sure what we build is usable, intuitive, and unlocks meaningful user workflows. Share what you learn about exploring and understanding AI system behavior across conversations and workloads. Iterate through fast feedback loops and experimentation, and share both wins and failures. What you’ll bring to the role: 3+ years of software engineering experience. Experience shipping customer-facing features at a SaaS company, beyond internal tooling. Full-stack range, with proficiency in backend development (Go and/or Python) and frontend development (TypeScript and React). A track record of working with product managers and designers. Regular, hands-on use of AI tools in your day-to-day engineering work. Experience being on call. You'd join our rotation after about 90 days. A track record of navigating ambiguity in a fast-moving field where requirements shift and experimentation is a core part of the job. Bonus: Experience building LLM or agent-powered features in production. Bonus: Hands-on experience with observability tooling, such as OpenTelemetry. Base Salary based on level of experience $218,891 — $245,946 CAD What you'll get when you join the Hive: A stake in our success - generous equity with employee-friendly stock program It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience Time to recharge with unlimited PTO A distributed-first mindset and culture (really!) Home office, co-working, and internet stipend Full benefits coverage for employees, with additional coverage available for dependents Up to 16 weeks of paid parental leave, regardless of path to parenthood Annual development allowance And much more... Please note we cannot currently sponsor or support visa transfers at this time. Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work. Phishing and Recruitment Scam Warning: We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you: All communications will come from an @honeycomb.io email address We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses— never personal accounts like Gmail or Yahoo . Our recruiting process will never ask you to provide financial or sensitive personal information, including but not limited to: Social security or tax identification numbers Credit card numbers Bank account information Diversity & Accommodations: We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams. We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know. As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback. Privacy Notice: If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes. For more information regarding our privacy practices please see the Honeycomb Privacy Notice . If you do not want us to retain your information, or want us to update it, please contact privacy@honeycomb.io . Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.

Location: Remote - United States What We’re Building Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023! If you want to see what we’ve been up to, please check out these blog posts and Honeycomb.io press releases . Who We Are We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live our values every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers. How We Work We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote Little more about the team: The team builds observability for AI in Honeycomb. We help customers see what their agents are doing, what those agents cost, and where errors happen. We also give them insight into individual conversations so they can debug them. We're bringing LLM and agent observability together, and we own both the data foundation and the product experiences built on top of it. You'll work in a small, cross-functional group of engineers with a dedicated product manager and designer, shipping features customers use in production. If you want to define how people understand and debug AI systems, this is the team for you. What you’ll do in the role: Deliver AI observability capabilities end to end, from ingestion to in-product visualizations. Contribute to the data model and infrastructure that let us observe agents and their ecosystems across the Honeycomb product. Build systems that analyze and surface AI-specific signals, such as cost, token usage, errors, and anomalies. Collaborate with product and design partners to make sure what we build is usable, intuitive, and unlocks meaningful user workflows. Share what you learn about exploring and understanding AI system behavior across conversations and workloads. Iterate through fast feedback loops and experimentation, and share both wins and failures. What you’ll bring to the role: 3+ years of software engineering experience. Experience shipping customer-facing features at a SaaS company, beyond internal tooling. Full-stack range, with proficiency in backend development (Go and/or Python) and frontend development (TypeScript and React). A track record of working with product managers and designers. Regular, hands-on use of AI tools in your day-to-day engineering work. Experience being on call. You'd join our rotation after about 90 days. A track record of navigating ambiguity in a fast-moving field where requirements shift and experimentation is a core part of the job. Bonus: Experience building LLM or agent-powered features in production. Bonus: Hands-on experience with observability tooling, such as OpenTelemetry. Base Salary based on level of experience $160,000 — $180,000 USD What you'll get when you join the Hive: A stake in our success - generous equity with employee-friendly stock program It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience Time to recharge with unlimited PTO A distributed-first mindset and culture (really!) Home office, co-working, and internet stipend Full benefits coverage for employees, with additional coverage available for dependents Up to 16 weeks of paid parental leave, regardless of path to parenthood Annual development allowance And much more... Please note we cannot currently sponsor or support visa transfers at this time. Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work. Phishing and Recruitment Scam Warning: We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you: All communications will come from an @honeycomb.io email address We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses— never personal accounts like Gmail or Yahoo . Our recruiting process will never ask you to provide financial or sensitive personal information, including but not limited to: Social security or tax identification numbers Credit card numbers Bank account information Diversity & Accommodations: We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams. We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know. As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback. Privacy Notice: If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes. For more information regarding our privacy practices please see the Honeycomb Privacy Notice . If you do not want us to retain your information, or want us to update it, please contact privacy@honeycomb.io . Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.

Location: Remote - Canada What We’re Building Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023! If you want to see what we’ve been up to, please check out these blog posts and Honeycomb.io press releases . Who We Are We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live our values every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers. How We Work We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote Little more about the team: The team builds observability for AI in Honeycomb. We help customers see what their agents are doing, what those agents cost, and where errors happen. We also give them insight into individual conversations so they can debug them. We're bringing LLM and agent observability together, and we own both the data foundation and the product experiences built on top of it. You'll work in a small, cross-functional group of engineers with a dedicated product manager and designer, shipping features customers use in production. If you want to define how people understand and debug AI systems, this is the team for you. What you’ll do in the role: Own end-to-end development of AI observability capabilities, from ingestion to in-product visualizations. Architect and evolve the data model and infrastructure that let us observe agents and their ecosystems across the Honeycomb product. Build systems that analyze and surface AI-specific signals, such as cost, token usage, errors, and anomalies. Collaborate with product and design partners to make sure what we build is usable, intuitive, and unlocks meaningful user workflows. Teach best practices for exploring and understanding AI system behavior across conversations and workloads. Iterate through fast feedback loops and experimentation, and share both wins and failures. What you’ll bring to the role: Significant software engineering experience, with a record of shipping and owning features end to end. Experience shipping customer-facing features at a SaaS company, beyond internal tooling. Full-stack range, with proficiency in backend development (Go and/or Python) and frontend development (TypeScript and React). A track record of working closely with product managers and designers. Regular, hands-on use of AI tools in your day-to-day engineering work. Experience being on call. You'd join our rotation after about 90 days. A track record of navigating ambiguity in a fast-moving field where requirements shift and experimentation is a core part of the job. Bonus: Experience building LLM or agent-powered features in production. Bonus: Hands-on experience with observability tooling, such as OpenTelemetry. Base Salary based on level of experience $250,000 — $280,000 CAD What you'll get when you join the Hive: A stake in our success - generous equity with employee-friendly stock program It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience Time to recharge with unlimited PTO A distributed-first mindset and culture (really!) Home office, co-working, and internet stipend Full benefits coverage for employees, with additional coverage available for dependents Up to 16 weeks of paid parental leave, regardless of path to parenthood Annual development allowance And much more... Please note we cannot currently sponsor or support visa transfers at this time. Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work. Phishing and Recruitment Scam Warning: We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you: All communications will come from an @honeycomb.io email address We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses— never personal accounts like Gmail or Yahoo . Our recruiting process will never ask you to provide financial or sensitive personal information, including but not limited to: Social security or tax identification numbers Credit card numbers Bank account information Diversity & Accommodations: We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams. We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know. As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback. Privacy Notice: If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes. For more information regarding our privacy practices please see the Honeycomb Privacy Notice . If you do not want us to retain your information, or want us to update it, please contact privacy@honeycomb.io . Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.

Location: Remote - United States What We’re Building Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023! If you want to see what we’ve been up to, please check out these blog posts and Honeycomb.io press releases . Who We Are We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live our values every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers. How We Work We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote Little more about the team: The team builds observability for AI in Honeycomb. We help customers see what their agents are doing, what those agents cost, and where errors happen. We also give them insight into individual conversations so they can debug them. We're bringing LLM and agent observability together, and we own both the data foundation and the product experiences built on top of it. You'll work in a small, cross-functional group of engineers with a dedicated product manager and designer, shipping features customers use in production. If you want to define how people understand and debug AI systems, this is the team for you. What you’ll do in the role: Own end-to-end development of AI observability capabilities, from ingestion to in-product visualizations. Architect and evolve the data model and infrastructure that let us observe agents and their ecosystems across the Honeycomb product. Build systems that analyze and surface AI-specific signals, such as cost, token usage, errors, and anomalies. Collaborate with product and design partners to make sure what we build is usable, intuitive, and unlocks meaningful user workflows. Teach best practices for exploring and understanding AI system behavior across conversations and workloads. Iterate through fast feedback loops and experimentation, and share both wins and failures. What you’ll bring to the role: Significant software engineering experience, with a record of shipping and owning features end to end. Experience shipping customer-facing features at a SaaS company, beyond internal tooling. Full-stack range, with proficiency in backend development (Go and/or Python) and frontend development (TypeScript and React). A track record of working closely with product managers and designers. Regular, hands-on use of AI tools in your day-to-day engineering work. Experience being on call. You'd join our rotation after about 90 days. A track record of navigating ambiguity in a fast-moving field where requirements shift and experimentation is a core part of the job. Bonus: Experience building LLM or agent-powered features in production. Bonus: Hands-on experience with observability tooling, such as OpenTelemetry. Base Salary based on level of experience $183,340 — $206,000 USD What you'll get when you join the Hive: A stake in our success - generous equity with employee-friendly stock program It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience Time to recharge with unlimited PTO A distributed-first mindset and culture (really!) Home office, co-working, and internet stipend Full benefits coverage for employees, with additional coverage available for dependents Up to 16 weeks of paid parental leave, regardless of path to parenthood Annual development allowance And much more... Please note we cannot currently sponsor or support visa transfers at this time. Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work. Phishing and Recruitment Scam Warning: We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you: All communications will come from an @honeycomb.io email address We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses— never personal accounts like Gmail or Yahoo . Our recruiting process will never ask you to provide financial or sensitive personal information, including but not limited to: Social security or tax identification numbers Credit card numbers Bank account information Diversity & Accommodations: We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams. We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know. As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback. Privacy Notice: If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes. For more information regarding our privacy practices please see the Honeycomb Privacy Notice . If you do not want us to retain your information, or want us to update it, please contact privacy@honeycomb.io . Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.

{COMPANY} is looking for a Frontend Engineer Agents to build agent-facing web and mobile interfaces, backend APIs, and high-quality real-time product experiences.

Perplexity is looking for a Machine Learning Engineer to develop search, retrieval, LLM training, and multi-agent systems.

Ищем технического руководителя продукта и команды из трёх инженеров. Отвечаете за архитектуру, качество и стоимость агентов в продакшене, план работ и найм.

Опыт работы от 6 лет, включая Copilot Studio и Azure AI Foundry. Знание архитектуры AI-агентов, паттернов проектирования и промпт-инжиниринга.