AI-инженер (LLM, агенты, AI product) вакансии - удалённо

-AI Engineer должен находить участки, которые сегодня требуют человека, таблиц, браузера и десятков повторяющихся действий, и превращать их в автоматизированные процессы, сервисы или AI-агентов. -Python и SQL/PostgreSQL.

- 3+ years of experience in web apps or services. - Hands-on experience with n8n or Make.

Synthesia is looking for a Research Scientist Interactive Avatars to develop and evaluate multimodal diffusion models for natural real-time avatar interactions.

Location: San Francisco, CA; Seattle, WA Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ Docker is looking for a Senior Software Engineer to build AI-powered developer tools and the platform behind them on our AI Developer Tools team. You will work at the intersection of AI, developer experience, and platform engineering, building tools that make Docker's engineers more productive and the platform that lets teams across Docker prototype, deploy, and scale their own AI developer tools. As a Senior Engineer you will design, build, and operate: AI-Powered Developer Tools. AI agents and tools that accelerate developer productivity, surface observability insights, and automate operational reviews. You will help teams adopt an AI-native way of working and speed up adoption of tools such as Claude Code and Codex. Examples include AI-powered code review and refactoring assistants, automated test generators and local environment setup tools, deployment pipeline diagnostic agents, and agents that simplify on-call work during incidents. Self-Service AI Developer Tools Platform. Platform infrastructure that lets product and platform teams across Docker unblock themselves by prototyping, building, and deploying their own AI developer tools, using the patterns and standards the team sets. You will report to the Senior Manager, AI Developer Tools, and work closely with the team's Principal and Staff engineers, product engineering teams, and platform teams across Docker. WHAT WOULD MAKE SOMEONE SUCCESSFUL IN THIS ROLE You are a strong, hands-on engineer who enjoys building at the intersection of AI, developer experience, and platform engineering. You have built software on top of LLMs and AI agents and have a good sense of what works in practice. You care about the people using your tools, and you can tell a tool developers love from one they put up with. You take a feature from a vague request to production: you ask the right questions about requirements, design it sensibly, ship it iteratively, and operate it afterward. You are comfortable in a fast-moving AI landscape and balance quality with pragmatism. You make the engineers around you better through thoughtful code review and by sharing what you learn. RESPONSIBILITIES Building and Operating AI Developer Tools - Design, build, and operate production AI agents for developer productivity, including code review assistants, test generators, deployment diagnostics, and incident response automation - Integrate LLM providers, agent orchestration frameworks, and MCP servers into reliable tools, following the team's patterns and standards - Build systems that help Docker's engineers adopt AI-native development tools - Build integrations between AI developer tools and existing developer infrastructure such as CI/CD pipelines, observability platforms, and deployment systems - Instrument your tools so the team can measure adoption, effectiveness, and developer satisfaction Self-Service Platform - Build and improve platform capabilities, including deployment pipelines (ArgoCD/GitOps), observability integration (Grafana), security controls, and cost management, that help teams ship their own AI tools faster - Help reduce time-to-production for new products from weeks to days - Contribute to reliability, security, and performance standards for AI systems, including SLOs, monitoring, and incident response Design and Delivery - Take features and services from requirements to production. Ask about scale, users, and constraints before designing, and write down your assumptions - Write clear design documents for the work you own, and participate in design reviews for the team - Review code thoroughly and share what you learn with the rest of the team - Take part in the team's on-call rotation, and help improve alerts, runbooks, and tooling so the next incident is easier - Follow the AI-assisted engineering practices the team sets: use AI tools critically, validate their output, and stay accountable for what you ship Collaboration and Growth - Work with the Senior Manager and the team's Principal and Staff engineers to understand priorities and shape your work - Partner with Infrastructure, Security, and Data teams on integrations and shared standards - Help newer engineers get up to speed on the team's tools, patterns, and practices - Keep up with emerging AI/LLM technologies and agent frameworks, and bring useful findings back to the team QUALIFICATIONS REQUIRED - 6+ years of software engineering experience building and operating production systems - Hands-on experience building LLM-powered applications, AI agents, or AI-assisted developer tools - Working knowledge of LLM APIs (OpenAI, Anthropic, and others), prompt engineering, agent orchestration frameworks, and practical uses of AI in software development workflows - Experience building and operating scalable backend services, distributed systems, or developer-facing platforms - Experience with cloud-native infrastructure, including Kubernetes, CI/CD pipelines, and observability systems - Proficiency in Go (preferred), Rust, Java, or Python, with strong software engineering fundamentals - Experience building developer tools, platform systems, or internal tools that other engineers rely on - Good product judgment: you weigh developer experience and technical trade-offs, and you ask clarifying questions before committing to a design - Clear written and spoken communication suited to a remote, async-first company - Ownership mentality with a bias for action and iterative delivery in ambiguous, fast-moving environments - Comfortable working autonomously in a distributed, remote-first team - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience PREFERRED - Experience with MCP (Model Context Protocol) or similar AI agent integration standards - Background in developer productivity, DevOps, SRE, or platform engineering - Contributions to open source AI tools, developer tooling, or platform engineering projects - Experience with GitOps deployment patterns (ArgoCD) or Grafana-based observability - Familiarity with security and operational practices for production AI systems - Experience with infrastructure-as-code (Terraform, Pulumi) and major cloud platforms (AWS, GCP, Azure) WHAT TO EXPECT FIRST 30 DAYS - Learn Docker's current AI and developer tooling landscape, the team's services, and the architecture decisions made so far - Meet your teammates, including the Principal and Staff engineers, the Senior Manager, and key stakeholders in product engineering - Ship a useful production change in your first weeks, using the team's AI-assisted engineering workflow - Review existing AI tool prototypes and internal experiments to learn what is working and what is not - Shadow on-call and learn the operational profile of the team's services FIRST 90 DAYS - Own a feature or service from design to production with measurable impact, such as part of an AI code review agent, a deployment diagnostic agent, or an on-call assistant - Write the design document for work you own and take part in team design reviews - Contribute to the self-service platform's deployment pipeline, observability integration, or security controls - Take part in the on-call rotation FIRST YEAR OUTLOOK - Be a go-to engineer for one or more of the team's AI tools or platform components - Have shipped multiple production improvements that Docker engineers use every day, with adoption and effectiveness you can point to - Have helped teams outside AI Developer Tools build and run their own tools on the platform - Have taken on larger and more ambiguous work as your scope grows, and helped newer engineers do the same Docker considers visa sponsorship on a case-by-case basis based on business needs.   Compensation & Equity United States: $160,900 – $260,700 + equity ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: San Francisco, CA; Seattle, WA Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ Docker is looking for a Staff Software Engineer to set the technical direction for key parts of our AI Developer Tools team. You will work at the intersection of AI, developer experience, and platform engineering, building the AI-powered tools and the platform that let teams across Docker prototype, deploy, and scale their own AI developer tools. As a Staff Engineer you will own the technical design and delivery for two areas: AI-Powered Developer Tools. Design and build AI agents and tools that accelerate developer productivity, surface observability insights, and automate operational reviews. You will help teams adopt an AI-native way of working and speed up adoption of tools such as Claude Code and Codex. Examples include AI-powered code review and refactoring assistants, automated test generators and local environment setup tools, deployment pipeline diagnostic agents, and agents that simplify on-call work during incidents. Self-Service AI Developer Tools Platform. Design and build the platform infrastructure that lets product and platform teams across Docker unblock themselves by prototyping, building, and deploying their own AI developer tools. You will set the patterns and standards that let teams experiment, iterate quickly, and graduate successful prototypes into production-ready services. You will report to the Senior Manager, AI Developer Tools, and work closely with the team's Principal engineers, engineering leadership, product engineering teams, and platform teams across Docker. WHAT WOULD MAKE SOMEONE SUCCESSFUL IN THIS ROLE You are a hands-on technical leader who works well at the intersection of AI, developer experience, and platform engineering. You have shipped production systems built on LLMs and AI agents, and you can explain what worked and what did not. You think in platforms: you design something once so that several teams can move faster. You have clear opinions about what makes a developer tool good, and sound judgment about when to build, when to integrate, and when not to do either. You are comfortable in a fast-moving AI landscape and balance technical quality with shipping iteratively. Before you design, you ask about scale, users, and constraints rather than assuming them. You lead through influence and mentorship, and the engineers around you get better because you are on the team. RESPONSIBILITIES Technical Leadership and Architecture - Set technical direction and own the architecture for AI-powered developer tools and the self-service platform within the team's roadmap - Turn ambiguous problems into clear requirements, plans, and staged decisions. Ask about scale, users, and constraints before designing, and write down your assumptions - Establish patterns, standards, and best practices for LLM integration, agent development, and production AI systems that the team and partner teams adopt - Shape platform capabilities including deployment frameworks (ArgoCD/GitOps), observability integration (Grafana), security controls, and operational tooling for AI developer tools - Design reliable, scalable infrastructure for hosting AI agents and developer tools - Recommend AI technology choices, LLM provider strategies, and agent orchestration approaches, and make the trade-offs explicit - Work with the Senior Manager and the team's Principal engineers to align technical decisions with business goals Systems Design and Implementation - Design, build, and operate production AI agents for developer productivity, including code review assistants, test generators, deployment diagnostics, and incident response automation - Build self-service platform capabilities that reduce time-to-production for new AI tools from weeks to days - Build systems that speed up adoption of AI-native development tools (Claude Code, Codex) across Docker's engineering organization - Set and meet reliability, security, and performance standards for AI systems, including SLOs, monitoring, incident response, and cost management - Design integrations between AI developer tools and existing developer infrastructure such as CI/CD pipelines, observability platforms, and deployment systems - Take part in the team's on-call rotation and use what you learn to improve alerts, runbooks, and tooling Strategic Impact and Innovation - Evaluate emerging AI/LLM technologies, developer tooling trends, and agent frameworks, and recommend what Docker should adopt and what it should not build - Define how we measure AI tool effectiveness, including adoption, productivity gains, and developer satisfaction - Improve AI tool performance, cost efficiency, and developer experience through architectural improvements - Contribute to the technical approach for hardening proven internal tools so other teams across Docker can adopt them - Lead cross-team technical delivery, surface risks early, and work with Infrastructure, Security, and Data on shared standards Leadership and Mentorship - Mentor senior engineers on AI/LLM integration patterns, agent development, and platform engineering practices - Lead design reviews and raise the quality of design and code reviews across the team - Create reusable patterns, documentation, and architectural decision records (ADRs) that other engineers build on - Help the team turn good individual AI-assisted engineering practice into shared workflows and controls - This role may require participation in an on-call rotation to provide support outside of standard business hours, including evenings, weekends, and holidays, as needed. QUALIFICATIONS REQUIRED - 8+ years of software engineering experience, with demonstrated technical leadership on production systems at scale - Hands-on production experience building LLM-powered applications, AI agents, or AI-assisted developer tools - Strong understanding of LLM APIs (OpenAI, Anthropic, and others), prompt engineering, agent orchestration frameworks, and practical uses of AI in software development workflows - Track record of designing and building scalable distributed systems and developer-facing platforms - Production experience with cloud-native infrastructure, including Kubernetes, GitOps deployment patterns, observability systems, and CI/CD pipelines - Proficiency in Go (preferred), Rust, Java, or Python, with strong software engineering fundamentals - Experience designing developer tools, platform systems, or internal tools that other teams rely on - Track record of clarifying requirements and constraints with stakeholders before committing to a design - Track record of leading complex initiatives that crossed team boundaries, and of influencing without direct authority - Strong product and platform judgment: you weigh business outcomes, developer experience, and technical trade-offs - Clear written and spoken communication suited to a remote, async-first company - Track record of mentoring other experienced engineers - Ownership mentality with a bias for action and iterative delivery in ambiguous, fast-moving environments - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience PREFERRED - Experience with MCP (Model Context Protocol) or similar AI agent integration standards - Background in developer productivity, DevOps, SRE, or platform engineering - Contributions to open source AI tools, developer tooling, or platform engineering projects - Experience evolving an internal platform or tool into a widely adopted, production-grade service - Knowledge of security, compliance, and operational practices for production AI systems - Experience with infrastructure-as-code (Terraform, Pulumi) and major cloud platforms (AWS, GCP, Azure) WHAT TO EXPECT FIRST 30 DAYS - Build context on Docker's current AI and developer tooling landscape, including existing AI experiments, LLM provider relationships, and architecture decisions to date - Meet the Senior Manager, the team's Principal engineers, engineering leadership, and key stakeholders in product engineering to understand needs, pain points, and constraints - Review existing AI tool prototypes and internal experiments to learn what is working and what is not - Get hands-on with the team's services and ship a useful production change - Shadow on-call and learn the operational profile of the team's services - Work with the Senior Manager to agree on initial technical priorities FIRST 90 DAYS - Lead the technical framing and delivery plan for one significant problem, from requirements through to production - Document the architecture, technology choices, and integration patterns for that work, including ADRs - Ship a production AI developer tool that sets patterns the team can reuse (for example an AI-powered code review agent, a deployment diagnostic agent, or an on-call assistant) - Contribute to the technical foundations of the self-service platform: deployment pipeline, observability integration, security controls, and cost management - Lead design reviews for your area of the roadmap and begin mentoring other engineers - Take part in the on-call rotation FIRST YEAR OUTLOOK - Be the trusted technical lead for your area of AI Developer Tools, and a sought-after partner for teams across Docker - Deliver at least one material outcome that spans multiple teams or systems - Have multiple production AI tools demonstrating value across Docker's engineering organization - Help build a self-service platform that lets multiple teams build, deploy, and operate their own AI tools with little friction - Define and instrument how the team measures AI tool adoption, effectiveness, and developer productivity impact - Grow other senior engineers into broader ownership, and reduce the number of decisions that depend on a small set of people Docker considers sponsorship on a case-by-case basis based on business needs.   Compensation & Equity United States: $170,350 – $275,550 + equity ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

• Запуск и развитие канадской версии iGaming-платформы. • Управление AI-агентами и автоматизация процессов.

• Запуск и развитие канадской версии iGaming-платформы. • Управление AI-агентами и автоматизация процессов.

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 About the problem space AI has changed what's possible in go-to-market, support, and business operations. The constraint is no longer "can we build it" — it's "can we deploy it into a real workflow, prove it made things better, and keep it working." Most companies are stuck at the demo stage: a lot of clever prompting, very little that runs reliably on Tuesday morning without someone watching it. This role exists to get us past that, everywhere outside of engineering. Little more about the team: You'll sit on the Data team, which is where this work belongs. Our team already operates at the seam between the business and its systems — we partner daily with RevOps, Customer Success, Sales, and Product, and we own the data infrastructure these workflows depend on. AI-in-the-business is a data problem with a model attached, and you'll have the pipelines, the warehouse, and the domain relationships already in place. What you'll do You are a senior individual contributor. Your job is to take business workflows that are slow, manual, or inconsistent, and make them fast, automated, and measurably better — then do it again, and leave behind enough shared scaffolding that the third one is easier than the first. Ship automated workflows end to end Partner with department leaders to identify the highest-leverage workflows in their orgs, and go deep enough on how the work actually happens to know where a model helps and where it doesn't. Define success before you build: cycle time, quality, cost, risk. Instrument it. Report on it honestly, including when the answer is "this didn't work." Deliver working systems, not prototypes, with evaluation harnesses, human-in-the-loop review where the stakes call for it, and ongoing monitoring. Iterate on adoption the way a product manager would: user research, documentation, and a real plan for getting people to use the thing. Build the shared substrate as you go Establish patterns for model access, orchestration and agents, prompt and tool management, evaluation, logging, and cost control — derived from what real workflows needed, not designed in advance. Build on the Data team's existing infrastructure rather than standing up parallel systems. Co-own shared components with your counterpart in Engineering; identify dependencies early and bring them into partner roadmaps collaboratively. Make the company fluent Create templates, playbooks, and golden paths: prompt patterns, agent patterns, safety checklists, evaluation patterns. Run office hours, demos, and community-of-practice sessions that make adoption feel accessible rather than intimidating. Develop enablement material for distinct audiences — GTM, operations, leadership — from fundamentals through advanced workflows. Help people build judgment about AI: when to use it, when not to, and how to tell whether it worked. Keep it safe and governable Partner with Security, IT, and Legal on access control, data handling, vendor risk, and policy — so that employees have a clear, fast, safe path to experiment. Work with the Data team to apply our data classification standards to AI use cases: what data can be used for retrieval and context, and what audit trails are required when sensitive data flows through LLM pipelines. What you'll bring Deep experience shipping systems into real business workflows — you've owned something end to end, in production, that non-technical people depended on daily. Hands-on fluency with modern AI stacks: LLMs, retrieval, tool use and agents, evaluation, guardrails — plus the pragmatism to keep things shippable. The ability to learn someone else's job well enough to improve it. This role lives or dies on understanding how support, sales, or finance actually work. A track record of leading cross-functional initiatives without formal authority, bringing clarity, momentum, and crisp decision-making. Comfort navigating security, privacy, and compliance tradeoffs in real organizations: data classification, retention, access controls, vendor risk. Strong teaching instincts — you explain complex things simply, write clear docs, and meet people where they are. Demonstrated ability to stay current as the landscape shifts, and to change your mind in public when the evidence does. Nice to have SQL fluency and comfort in a modern data stack (dbt, a cloud warehouse, BI tooling). Experience with workflow automation or enterprise systems: case management, ticketing, CRM, knowledge bases. Familiarity with observability practices for AI systems: monitoring, quality signals, evaluation pipelines, cost and latency analysis. Change management experience across a distributed, multi-function company. Interest in external evangelism — writing, speaking, podcasts, peer groups. Base Salary based on level of experience $310,000 — $360,000 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 About the problem space AI has changed what's possible in go-to-market, support, and business operations. The constraint is no longer "can we build it" — it's "can we deploy it into a real workflow, prove it made things better, and keep it working." Most companies are stuck at the demo stage: a lot of clever prompting, very little that runs reliably on Tuesday morning without someone watching it. This role exists to get us past that, everywhere outside of engineering. Little more about the team: You'll sit on the Data team, which is where this work belongs. Our team already operates at the seam between the business and its systems — we partner daily with RevOps, Customer Success, Sales, and Product, and we own the data infrastructure these workflows depend on. AI-in-the-business is a data problem with a model attached, and you'll have the pipelines, the warehouse, and the domain relationships already in place. What you'll do You are a senior individual contributor. Your job is to take business workflows that are slow, manual, or inconsistent, and make them fast, automated, and measurably better — then do it again, and leave behind enough shared scaffolding that the third one is easier than the first. Ship automated workflows end to end Partner with department leaders to identify the highest-leverage workflows in their orgs, and go deep enough on how the work actually happens to know where a model helps and where it doesn't. Define success before you build: cycle time, quality, cost, risk. Instrument it. Report on it honestly, including when the answer is "this didn't work." Deliver working systems, not prototypes, with evaluation harnesses, human-in-the-loop review where the stakes call for it, and ongoing monitoring. Iterate on adoption the way a product manager would: user research, documentation, and a real plan for getting people to use the thing. Build the shared substrate as you go Establish patterns for model access, orchestration and agents, prompt and tool management, evaluation, logging, and cost control — derived from what real workflows needed, not designed in advance. Build on the Data team's existing infrastructure rather than standing up parallel systems. Co-own shared components with your counterpart in Engineering; identify dependencies early and bring them into partner roadmaps collaboratively. Make the company fluent Create templates, playbooks, and golden paths: prompt patterns, agent patterns, safety checklists, evaluation patterns. Run office hours, demos, and community-of-practice sessions that make adoption feel accessible rather than intimidating. Develop enablement material for distinct audiences — GTM, operations, leadership — from fundamentals through advanced workflows. Help people build judgment about AI: when to use it, when not to, and how to tell whether it worked. Keep it safe and governable Partner with Security, IT, and Legal on access control, data handling, vendor risk, and policy — so that employees have a clear, fast, safe path to experiment. Work with the Data team to apply our data classification standards to AI use cases: what data can be used for retrieval and context, and what audit trails are required when sensitive data flows through LLM pipelines. What you'll bring Deep experience shipping systems into real business workflows — you've owned something end to end, in production, that non-technical people depended on daily. Hands-on fluency with modern AI stacks: LLMs, retrieval, tool use and agents, evaluation, guardrails — plus the pragmatism to keep things shippable. The ability to learn someone else's job well enough to improve it. This role lives or dies on understanding how support, sales, or finance actually work. A track record of leading cross-functional initiatives without formal authority, bringing clarity, momentum, and crisp decision-making. Comfort navigating security, privacy, and compliance tradeoffs in real organizations: data classification, retention, access controls, vendor risk. Strong teaching instincts — you explain complex things simply, write clear docs, and meet people where they are. Demonstrated ability to stay current as the landscape shifts, and to change your mind in public when the evidence does. Nice to have SQL fluency and comfort in a modern data stack (dbt, a cloud warehouse, BI tooling). Experience with workflow automation or enterprise systems: case management, ticketing, CRM, knowledge bases. Familiarity with observability practices for AI systems: monitoring, quality signals, evaluation pipelines, cost and latency analysis. Change management experience across a distributed, multi-function company. Interest in external evangelism — writing, speaking, podcasts, peer groups. Base Salary based on level of experience $225,000 — $265,000 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.

Areta is looking for an AI Engineering Intern Investment Banking to build and maintain internal tools, workflows, automations, and system integrations for deal execution and operations.

Location: Berlin Office; Norway; Latvia; Netherlands; Hungary; Portugal; Poland; Serbia; Germany; Austria; Lithuania; Ireland; United Kingdom; Spain Workplace: Remote The AI orchestration of your wildest imagination. n8n is the open workflow orchestration platform built for the new era of AI. We give technical teams the freedom of code with the speed of no-code, so they can automate faster, smarter, and without limits. Backed by a fiercely inventive community and 500+ builder-approved integrations, we’re changing the way people bring systems together and scale ideas for impact. Since our founding in 2019, we’ve grown into a diverse team of over 260 - working across Europe and the US, connected by a shared builder spirit and with our centre of gravity in Berlin. Along the way, we’ve: - Cultivated a community of more than 650,000 active developers and builders - Earned 190K+ GitHub stars, making us one of the world’s Top 40 most popular projects - Backed by top investors, from Sequoia’s first German seed to our SAP's recent strategic investment - bringing us to a $5.2bn valuation That’s the company we’ve built. Now we’d love to see what you can build. If you’re applying, try n8n out - whether you’re technical or not - and share a screenshot of your first workflow with us. The easiest place to start is here: app.n8n.cloud/register http://app.n8n.cloud/register. We’re in a defining moment of an incredible journey. Come and build with us. 🎯 YOUR MAIN GOAL WILL BE TO TURN N8N’S INTERNAL AI AND AUTOMATION CAPABILITIES INTO SOMETHING EVERY FUNCTION CAN CONFIDENTLY USE, BUILD WITH, AND LEARN FROM. To make that happen, you’ll create the programs, experiences, and foundations that help teams across n8n build their AI and automation fluency: DRIVE HANDS-ON ENABLEMENT - Run weekly, role-specific workshops, prioritizing less-technical functions such as Legal and Customer Support. - Lead hands-on sessions where you build live alongside teams, helping them turn real workflows and challenges into working automations. - Run Build Along Office Hours and Bounty Hunts that give teams regular opportunities to learn, experiment, and solve problems together. - Help teams identify useful automation opportunities, understand the process they are changing, and decide when to reuse an existing solution, build themselves, or involve the Automation team. OWN DOGFOODING & EXPERIMENTATION - Own our monthly Dogfooding Day end-to-end, from planning and coordination through execution and follow-up. - Design and run hackathons and other experimentation initiatives that encourage teams to explore new ways of working with AI and automation. - Turn learnings and outputs from these initiatives into reusable assets that help other teams move faster. SCALE AI FLUENCY & COMMUNITY - Own periodic AI fluency survey cycles alongside the People team and help calibrate what fluency means across different functions. - Build visibility around internal wins and reusable solutions so teams can learn from what others have already created. - Identify and support champions across functions, informally leading the emerging Guild and helping automation knowledge spread across the company. ENABLE SAFE, REUSABLE AUTOMATION - Act as product owner for our internal “safe playground,” partnering with IT, Security, Data, and Solutions Engineering on access, credentials, environments, and requirements. - Turn outputs from workshops and office hours into reusable templates and resources that teams can easily discover and adopt. - Actively help teams reuse existing solutions rather than reinventing them, making automation more accessible and scalable across n8n. - Check whether the things built are still in use four weeks later; provide evidence that teams reuse existing assets and can make routine changes without handing everything back to the Automation team. REQUIREMENTS MUST-HAVES - 🛠️ Practitioner-level n8n fluency: You’ve built real, meaningful automations in n8n and are comfortable building live alongside others. - 🎓 Technical enablement experience: You’ve run structured, recurring enablement programs such as workshops, office hours, or build-alongs. - 🤝 Non-technical audience expertise: You have a strong track record of helping non-technical teams understand, adopt, and confidently use technical tools. - 🏗️ Cross-functional ownership: You’re comfortable partnering with IT, Security, and Data teams to define and own requirements around access, credentials, and environments without needing to implement the infrastructure yourself. - 🌍 CET overlap: You’re based in a time zone that gives you strong overlap with Central European working hours, within a couple of hours of Berlin. - 💬 English fluency: You have fluent or near-native English and can communicate clearly and confidently with audiences ranging from individual contributors to senior stakeholders. NICE-TO-HAVES - 🌱 Champion programs: You’ve helped build or run an internal ambassador, champion, or community program. - 📊 Fluency measurement: You have experience running capability, fluency, or adoption surveys and turning the results into actionable programs. - 🔐 Access & governance: You’re familiar with access or governance models and have worked with stakeholders responsible for secure environments and tooling. Why join us? At n8n, you’ll have the opportunity to build a brand-new enablement function from the ground up and shape how AI and automation become part of everyday work across the company. You’ll have a direct line to the Head of AI & Automation, high visibility across functions, and genuine autonomy to design an enablement model rather than inherit one. As n8n scales, you’ll become a key connector between the people building our internal automation capabilities and the teams putting them to work. You’ll help create a culture where teams don’t just learn about automation — they confidently build, experiment, share what works, and help others do the same. You’ll join a fast-growing, remote-first company that values autonomy, experimentation, and builder culture, with the opportunity to influence how we scale AI fluency across the organization. Sound like a challenge you’re excited to take on? Apply now — and help us build the future of automation. n8n is an equal opportunity employer and does not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, gender identity, age, marital status, veteran status, or disability status. We can sponsor visas to Germany; for any other country, you need to have existing right to work. Our company language is English. You care about diversity and inclusion? We do too! Check out our Diversity, Inclusion and Belonging initiatives at n8n https://www.notion.so/Diversity-inclusion-and-belonging-n8n-c1bec2fff536422d868b1a438d990e35?pvs=21 (https://www.notion.so/n8n/Diversity-inclusion-and-belonging-n8n-c1bec2fff536422d868b1a438d990e35). Location disclaimer: If you see multiple job postings for the same role, it is most likely because we're hiring remotely for this role and posting in different locations to make sure every potential candidate can see the role. Please apply to the location you're the most likely to work from in the future. BENEFITS - Competitive compensation 💸 – We offer fair and attractive pay. - Ownership 💪 – Our core value is to “empower others,” and we mean it—you’ll get a slice of n8n with equity. - Work/life balance 🏖️ – We work hard but ensure you have time to recharge: - Europe: 30 days of vacation, plus public holidays wherever you are. - US: 20 vacation days, 8 sick days, plus public holidays wherever you are. - Health & wellness 🩺 – - Europe: We provide benefits according to local country norms.* - US: Multiple low-premium, low-deductible medical plans with coverage for individuals and families—plus a no-cost premium HDHP option with a pre-seeded HSA—along with dental and vision coverage. - Future planning 💰 – - Europe: We provide pension contributions according to local country norms.* - US: 401(k) retirement plan with a 4% employer match. - Financial security 🛡️ – - Europe: We provide benefits according to local country norms.* - US: Company-paid short-term and long-term disability insurance, plus life insurance to support you and your loved ones. - Career growth 📈 – We hire rising stars who grow with us! You’ll get €1K (or equivalent) per year to spend on courses, books, events, or coaching to level up your skills. - A passionate team 🤩 – We love our product, and we prove it with regular hackathons where we see who can build the coolest thing with it! - Remote-first 🌏 – Our team works remotely across Europe, with regular off-sites for team bonding. Some roles, like sales in the US, are hybrid—please check the job description. - Giving back 🤝 – We're big fans of open source, and you'll get $100 per month to support projects you care about. - Transparency 🙏 – We all know what everyone’s working on, how the company is doing—the whole shebang. *Country and/or State specific details provided in your employment agreement.

Location: Korea Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! ABOUT NORTH North is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications. WHY THIS ROLE? This role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors such as finance, healthcare, and telecommunications. We’re looking for senior software engineers with Applied AI experience who can own the design, build, and deployment of agentic workflows powered by Large Language Models (LLMs), from early prototypes to production-grade AI agents, to deliver concrete business value in enterprise workflows. You’ll work closely with customers on real-world business problems, often building first-of-their-kind agent workflows that integrate LLMs with tools, APIs, and data sources. While our pace is startup-fast, the bar is enterprise-high: agents must be reliable, observable, safe, and auditable from day one. WHAT YOU’LL DO Customer-Facing Technical Impact - Work closely with enterprise customers to translate high-value, ambiguous business problems into well-framed agentic problems with clear success criteria and evaluation methodologies. - Provide technical leadership across the full development and evaluation lifecycle, including post-deployment iteration, for agentic workflows. - Travel up to 20–40% to work on-site with customers and partners Agent Design, Build and Production launches - Lead the design, build, and delivery of LLM-powered agents that reason, plan, and act across tools and data sources with enterprise-grade reliability and performance. - Balance rapid iteration with enterprise requirements, evolving prototypes into stable, reusable solutions. - Define and apply evaluation and quality standards to measure success, failures, and regressions; Debug real-world agent behavior and systematically improve prompts, workflows, tools, and guardrails. - Build and ship features for North, our AI workspace platform, working across the full product lifecycle from conceptualisation through production - Take ownership of scoping and shaping use cases end-to-end, flexing into whatever technical area the problem demands (including frontend) to drive the most effective solution Team Mentorship & Organizational Impact - Mentor engineers across distributed teams. - Drive clarity in ambiguous situations, build alignment, and raise engineering quality across the organization. - Contribute to shared frameworks and patterns that enable consistent delivery across customers. REQUIRED SKILLS & EXPERIENCE Technical Foundations - Demonstrated ability to build, ship, and operate production-grade software systems. - Substantial hands-on experience designing, building, evaluating, and fine-tuning LLM-based agents in real-world applications. - Deep familiarity with modern LLM ecosystems, including models (e.g., GPT, Claude, Gemini), vector databases, RAG architectures, agent/orchestration frameworks, prompt engineering, tool use, multi-step agent workflows (e.g., ReAct), and robust failure handling. - Strong proficiency in Python and/or JavaScript/TypeScript. Experience and Leadership - Experience working directly with customers or stakeholders to design and deliver LLM-powered agentic solutions aligned with real business needs. - Proven technical leadership at the team level, including guiding architecture, implementation, and delivery of complex AI systems. ADDITIONAL REQUIREMENTS - Strong written and verbal communication skills. - Fluency in English and Korean language. IT’S A BONUS IF YOU HAVE: - Experience setting architectural standards for AI and agentic systems across distributed teams - Experience flexing into unfamiliar technical areas, such as frontend, when the problem calls for it - Exposure to regulated or sensitive industry environments (finance, healthcare, telecoms) - Experience with enterprise security, compliance, or auditability requirements for AI systems FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

The Senior AI Professional will help design, develop, and optimize production-grade agentic AI solutions. Design, develop, and optimize production-grade agentic AI solutions.

Location: Remote; Seattle, WA; New York, NY; San Francisco, CA Workplace: Remote We are building AI to simulate the world through merging art and science. We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world. World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached. Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you. *Titles posted to our careers page are updated regularly to best advertise the role and expected seniority, but internally we have a flat titling system with two types of titles: one for individual contributors and one for people managers. ABOUT THE ROLE *Open to hiring remote across the US — we also have offices in New York, San Francisco, and Seattle. We are looking for a Prototype Researcher to join Runway Labs — our research and exploration team pushing the frontier of AI video and General World Models. You’ll imagine, design, and build experimental experiences that make emerging AI capabilities tangible and communicate a compelling vision for where the technology is heading. This role combines creative thinking, hands-on prototyping, and storytelling. You should be able to develop an original idea, build a working prototype, and shape it into a clear, memorable demonstration. Your work will help people understand new AI systems through experiences they can see, use, and engage with. Working closely with researchers, engineers, and designers, you’ll explore new interfaces and interaction paradigms for AI-generated video, world models, and agentic systems. The focus is on research explorations that express our vision, reveal new possibilities, and strengthen Runway’s position as a full-stack research organization. We’re looking for a motivated self-starter with strong creative judgment, technical fluency, and a portfolio that shows both what you can build and how well you can communicate an idea. WHAT YOU’LL DO - Develop original concepts that explore the possibilities of emerging AI systems, from interactive video and world models to agentic experiences. - Design and build working prototypes that turn research capabilities into engaging, understandable experiences. - Shape each project’s story: what it explores, why it matters, and what it suggests about the future. - Package explorations into polished demos, films, and interactive experiences that communicate our research and vision. - Collaborate with researchers and engineers to understand new capabilities and identify compelling ways to demonstrate them. - Move quickly through experimentation, using prototypes to test ideas and refine both the experience and its narrative. WHAT YOU’LL NEED - A portfolio of original projects that demonstrates creative thinking, design craft, technical execution, and strong storytelling. - The ability to take an idea from an early concept to a working prototype and a compelling presentation. - Hands-on experience building interactive experiences with code, with the judgment to choose the right tools for each experiment. - Strong visual and interaction design skills, with an eye for detail and an instinct for making complex ideas accessible. - Genuine curiosity about AI video, world models, agentic systems, and emerging generative media. - Comfort working in ambiguous research environments, defining your own direction, and learning new tools as the work evolves. - The ability to explain the purpose and potential of your work clearly, through writing, visuals, demos, or film. Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide. There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates. WORKING AT RUNWAY Great things come from great teams. https://www.youtube.com/watch?v=kwmj4ato2kw&ab_channel=Runway We’d love to hear from you. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply. More about Runway - Universal World Simulator https://runwayml.com/world-simulator.html - GWM-1 https://runwayml.com/research/introducing-runway-gwm-1 - Gen-4.5 https://runwayml.com/research/introducing-runway-gen-4.5 - General World Models https://runwayml.com/research/introducing-general-world-models - Robotics SDK https://runwayml.com/research/introducing-runway-gwm-1#robotics-section - Conversational Real-time Agents https://runwayml.com/research/introducing-runway-gwm-1#avatars-section - Runway Studios https://runwayml.com/studios We're excited to be recognized as a best place to work: Crain's https://www.crainsnewyork.com/awards/best-places-work-2023 | InHerSight https://www.inhersight.com/companies/best/city/new-york-city-ny | BuiltIn NYC https://builtin.com/awards/new-york-city/2024/best-places-to-work | INC https://www.inc.com/best-workplaces/2024

Location: Remote - Singapore Workplace: Remote ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE ROLE: We're looking for a Deployed Engineer to join our Professional Services team, working directly with enterprise customers to build reliable, production agents. You'll translate vague enterprise workflows into concrete software specs and guide engineering teams through the resulting solution, or build it for them. You might spend a week designing a customer's agent architecture, a few weeks co-building their evaluation pipeline, or a quarter embedded inside their team shipping alongside their engineers. You are someone who's built real AI systems for production and can defend the technical tradeoffs within them. KEY RESPONSIBILITIES: - Advising: Agent architecture design, evaluation strategy review, and best-practice production guidance. - Building: Co-build with the customer's engineering team across the full Agent Development Lifecycle (ADLC) in outcome-scoped engagements. - Embedding: Serve as a deployed engineer inside the customer's team for extended engagements, operating as a de facto member of their org to ship agent systems directly. - Agent Engineering: ADLC end-to-end, architecture design, orchestration patterns, evals, custom conversational UIs, and production deployment. - Applied AI: Post-training, supervised fine-tuning, harness engineering, trace mining, model selection and evaluation methodology. REQUIREMENTS: - 4+ years of software engineering experience with deep expertise in Python. TypeScript/JavaScript a plus. - 2+ years of hands-on experience building and shipping production agent systems. - Strong client-facing communication skills, with the ability to confidently articulate architectural decisions to technical stakeholders (engineers, architects, CTOs). - Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management (short and long-term memory). - Deep familiarity designing and implementing evaluation methodologies for non-deterministic AI systems. - Comfortable operating across the full spectrum from advisory to embedded delivery. - Willing to travel up to 20% of the time. NICE TO HAVE: - Exposure to dataset curation and post-training techniques (SFT, DPO, RLHF) on open-weight models using tools like Axolotl, Unsloth, Hugging Face transformers, or TRL. - Experience with trace mining to drive continuous improvement loops COMPENSATION: $185,000-$260,000 base salary + equity Location: - Singapore - Remote with up to 25% travel Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: Atlanta, GA; Austin, TX; Dallas, TX; Las Vegas, NV; Nashville, TN; Seattle, WA; Boston, MA; Detroit, MI; San Diego, CA; Denver, CO Workplace: Remote ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE ROLE We're looking for a Deployed Engineer to join our Professional Services team, working directly with enterprise customers to build reliable, production agents. You'll translate vague enterprise workflows into concrete software specs and guide engineering teams through the resulting solution, or build it for them. You might spend a week designing a customer's agent architecture, a few weeks co-building their evaluation pipeline, or a quarter embedded inside their team shipping alongside their engineers. You are someone who's built real AI systems for production and can defend the technical tradeoffs within them. KEY RESPONSIBILITIES - Advising: Agent architecture design, evaluation strategy review, and best-practice production guidance. - Building: Co-build with the customer's engineering team across the full Agent Development Lifecycle (ADLC) in outcome-scoped engagements. - Embedding: Serve as a deployed engineer inside the customer's team for extended engagements, operating as a de facto member of their org to ship agent systems directly. - Agent Engineering: ADLC end-to-end, architecture design, orchestration patterns, evals, custom conversational UIs, and production deployment. - Applied AI: Post-training, supervised fine-tuning, harness engineering, trace mining, model selection and evaluation methodology. REQUIREMENTS - 4+ years of software engineering experience with deep expertise in Python. TypeScript/JavaScript a plus. - 2+ years of hands-on experience building and shipping production agent systems. - Strong client-facing communication skills, with the ability to confidently articulate architectural decisions to technical stakeholders (engineers, architects, CTOs). - Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management (short and long-term memory). - Deep familiarity designing and implementing evaluation methodologies for non-deterministic AI systems. - Comfortable operating across the full spectrum from advisory to embedded delivery. - Willing to travel up to 20% of the time. NICE TO HAVE - Exposure to dataset curation and post-training techniques (SFT, DPO, RLHF) on open-weight models using tools like Axolotl, Unsloth, Hugging Face transformers, or TRL. - Experience with trace mining to drive continuous improvement loops LOCATION Remote COMPENSATION $150,000-$270,000 base + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: Washington DC Workplace: Remote ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. Today, LangChain, LangGraph, LangSmith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. ABOUT THE TEAM The LangChain Deployed Engineering - Federal team works directly with U.S. Government customers — including the Department of Defense (DoD), Civilian Agencies, and the Intelligence Community (IC) — who are building and operating AI agents in mission-critical environments. This is a hands-on, highly technical team that partners closely with government engineers, technical program managers, and system integrators across the full lifecycle — from pre-award technical shaping and evaluations to post-deployment advisory work in secure environments. The focus is on achieving the technical win, architecting secure and compliant agent systems, and enabling agencies to operate AI agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, security, and go-to-market. You will shape how LangChain is adopted across classified and unclassified environments, ensuring alignment with federal compliance requirements while feeding mission-driven insights back into the platform. ABOUT THE ROLE As a Deployed Engineer, you’ll work on some of the hardest problems in applied AI — not demos or experimental research, but production systems supporting real-world missions. You’ll help defense, civilian, and intelligence customers design, deploy, and operate AI agents in secure, regulated, and high-stakes environments. The feedback loop is fast, the mission impact is tangible, and your work directly influences how AI agents are deployed across the federal landscape. You will operate in environments that demand security, reliability, compliance (FedRAMP, IL levels, etc.), and operational rigor. WHAT YOU’LL DO - Co-architect and co-build production AI agents with federal engineering teams and system integrators - Own the technical win in federal pre-sales engagements by designing secure POCs, supporting RFI/RFP technical responses, and guiding technical evaluations - Design architectures that meet federal security and compliance requirements (FedRAMP, DoD IL2–IL6, NIST, etc.) - Help agencies deploy and operate agent-based applications such as mission support copilots, intelligence analysis agents, research automation systems, and multi-step operational workflows - Advise customers post-award on architecture, scalability, observability, evaluation, and long-term roadmap decisions - Deliver technical demos, workshops, and enablement sessions tailored to government developer and operator audiences - Partner with security teams to navigate ATO processes and accreditation pathways - Surface field feedback from federal use cases and contribute reusable patterns, secure deployment guides, and example code that scale across agencies - Occasionally contribute code upstream when it meaningfully improves federal customer outcomes WHAT YOU’LL BRING - Must have zctive or prior U.S. security clearance (Secret, TS/SCI) - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, product engineering), ideally supporting federal or regulated customers - Experience working with DoD, Civilian Agencies, Intelligence Community, or federal system integrators - Strong Python and JavaScript fundamentals, with deep systems thinking - Experience designing agent-based or LLM-powered systems beyond simple API calls, including multi-step workflows, orchestration, guardrails, and failure handling - Familiarity with secure cloud environments (AWS GovCloud, Azure Government, etc.) - Comfort operating in regulated environments with security, compliance, and documentation requirements - Experience supporting technical evaluations, architecture reviews, and competitive down-select processes - Ability to clearly explain technical tradeoffs to government stakeholders and build trust across engineering and program leadership - Ownership mindset — you take responsibility for mission outcomes, not just recommendations - Bias toward action and comfort operating in ambiguity - Excitement about running AI agents in real-world, production federal environments — not just building demos NICE TO HAVE - Experience deploying AI systems in classified or air-gapped environments - Familiarity with FedRAMP authorization processes or DoD Impact Levels (IL2–IL6) - Experience with LLM evaluation, observability, red-teaming, or guardrails in high-assurance settings - Hands-on experience with AWS, Azure, containers, Kubernetes, and secure networking architectures - Experience working alongside federal system integrators (Booz Allen, SAIC, Leidos, etc.) - Production experience with LangChain, LangGraph, or similar agent frameworks COMPENSATION & BENEFITS We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. Annual OTE range: $185,000–$300,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Задачи: — Дизайн и построение LLM пайплайнов, AI агентов и RAG-систем с функциями вызова инструментов и структурированным выводом (JSON schema) — Разработка production-grade Python сервисов с использованием Django, Celery, Redis — Валидация продуктовых гипотез на основе реальных данных и аналитики — Измерение и оптимизация качества, производительности и стоимости LLM — Тесное сотрудничество с продакт-менеджерами и инженерами для превращения идей в масштабируемые решения Требования: — Опыт создания production LLM приложений — Практические знания RAG, embeddings, векторного поиска, prompt engineering и оценки LLM — Опыт работы с LangGraph, LangChain или аналогичными фреймворками — Сильный опыт Python backend (Django, PostgreSQL, асинхронное программирование) — Навыки работы с SQL и Pandas, ориентированность на данные — Владение английским языком на уровне B2-C1, русским на уровне C1 — Локация: любой город, кроме России и Беларуси Будет плюсом: — Опыт работы с векторными базами данных (Qdrant, pgvector и др.) — Опыт дообучения, классификации текста или работы с embedding моделями — Опыт с Kubernetes, gRPC или Go Условия: — Удалённая работа — Гибкий график — Профессиональное развитие Компания Mad Devs занимается решением сложных задач и созданием инновационных решений в области AI, проекты охватывают Европу, США и Юго-Восточную Азию. Вакансия направлена на революцию в юридической индустрии с помощью AI.