Location: San Francisco, CA
Workplace: OnSite
ABOUT US
At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale.
We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry.
More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale.
ABOUT THE ROLE
We’re looking for a Solutions Marketing Manager to shape how LangChain brings its full platform to priority industries, enterprise buyers, and high-value use cases.
This role sits at the intersection of product and GTM. You’ll translate customer problems into clear solution narratives, repeatable sales plays, campaign themes, and customer-facing assets that help teams understand where LangChain fits in their AI strategy.
You’ll develop industry solutions, use case solutions, and enterprise solution stories for segments such as financial services, healthcare, life sciences, and other priority markets. You’ll work closely with sales, solutions, product, demand generation, field marketing, education, and customer teams to understand what matters in the field, turn those insights into messaging and collateral, and help create programs that support pipeline and revenue generation.
The role covers the full LangChain platform, including Observability & Evaluation, Deployment, Sandboxes, LLM Gateway, Fleet, Engine, and OSS. The goal is to explain how these products work together to help companies build, deploy, monitor, and improve agents in production.
You’ll define the problems we solve for specific audiences, package those into repeatable narratives, and help GTM teams take them to market.
WHAT YOU’LL DO
DEVELOP INDUSTRY AND USE CASE SOLUTIONS
- Build solution narratives for priority industries and enterprise use cases. Initial focus areas include financial services, healthcare, and life sciences, with room to expand based on GTM priorities.
- Translate customer problems into clear solution stories. You’ll connect LangChain’s platform capabilities to the business, operational, governance, and technical needs of specific audiences.
- Define repeatable use case messaging. You’ll identify where agents can create value across functions and industries, then turn those patterns into solution briefs, use case pages, campaign assets, sales decks, webinar narratives, and customer-facing content.
- Build a point of view on enterprise AI adoption. You’ll help explain how companies move from prototypes and isolated experiments to production deployments with the controls, visibility, and evaluation practices they need.
- Stay close to the market. You’ll synthesize customer conversations, sales feedback, competitive activity, industry trends, and product signals into sharper messaging and GTM recommendations.
SUPPORT ENTERPRISE GTM MOTIONS
- Partner with sales, solutions, field marketing, demand generation, and customer-facing teams on targeted enterprise campaigns and account motions.
- Build sales enablement for industry and enterprise conversations. This may include talk tracks, discovery questions, objection handling, use case maps, executive-ready decks, demo narratives, and competitive context.
- Turn field learnings into reusable sales plays. You’ll work with account teams to understand what resonates with buyers and turn those insights into repeatable messaging, collateral, and campaign programs.
- Create materials for complex buying committees. You’ll help LangChain speak clearly to technical buyers, AI leaders, IT and security stakeholders, business leaders, and functional teams.
- Support pipeline and revenue programs. You’ll help connect solution narratives to campaigns, events, webinars, ABM motions, field programs, and sales follow-up.
WHAT YOU’LL BRING
- You have 3–6+ years of experience in solutions marketing, enterprise marketing, product marketing, developer marketing, industry marketing, or a related GTM role.
- You’ve built messaging, collateral, or campaigns around technical products, AI/ML products, developer tools, B2B SaaS, infrastructure, automation, productivity tools, or platform products.
- You can turn customer problems into clear solution narratives. You know how to move from “what the product does” to “why this matters for this audience, industry, or use case.”
- You understand enterprise buying motions. You know how to create assets for complex buying committees, regulated industries, sales-led motions, and executive conversations.
- You’re comfortable with technical products. You don’t need to be an engineer, but you should be able to learn technical concepts quickly, ask good questions, and translate details into customer-facing messaging.
- You like working with sales and customer-facing teams. You’re interested in what happens in the field and know how to turn that feedback into stronger messaging and enablement.
- You’re comfortable working across many audiences, including developers, technical buyers, operators, admins, AI leaders, business stakeholders, and nontechnical end users.
- You can balance strategic thinking with execution. You can define a messaging POV, then build the deck, brief, landing page copy, or sales asset that brings it to life.
- You’re comfortable with ambiguity and iteration. The market for production-ready AI agents is still being defined, and you’re excited to ship, learn, and improve.
- You have genuine curiosity about agents, enterprise AI adoption, and how they will change how teams work.
NICE TO HAVE
- Experience building industry or solutions marketing programs for financial services, healthcare, life sciences, public sector, or other regulated industries.
- Experience supporting enterprise sales teams through enablement, account-based campaigns, customer-facing storytelling, competitive support, or executive-facing collateral.
- Familiarity with the LLM, agent, or AI application development ecosystem.
- Experience with PLG motions, onboarding, activation, lifecycle marketing, or self-serve adoption.
WHY JOIN
- You’ll help build the solutions marketing motion at LangChain. There is room to shape how we define priority industries, package use cases, support enterprise campaigns, and enable the field.
- You’ll work on a category that is moving from experimentation to enterprise adoption. Companies are trying to understand where agents can create real value and how to deploy them with control.
- You’ll join a small, fast-moving team. You’ll get real scope, close access to product and GTM leaders, and the ability to ship meaningful work quickly.
Compensation: 140,000 - 195,000K
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: San Francisco, CA; New York, NY
Workplace: OnSite
ABOUT US
At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale.
We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry.
More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale.
ABOUT THE TEAM
The Security team ensures that while AI moves at breakneck speed, everyone driving the racecar is wearing a seatbelt. We secure LangChain's core platform and protect AI agents from emerging threats. We work across the stack so developers can confidently ship from prototype to production without compromising on safety or privacy.
ABOUT THE ROLE
You'll be the hands-on detection and response engineer responsible for how we see, stop, and learn from threats across LangChain's production platform, cloud infrastructure, and the services that host and execute agentic workloads. You'll partner closely with Product Security to turn threat models, vulnerabilities, and incidents into telemetry, detections, and durable defenses. Your primary focus is engineering: building detection, investigation, and response systems that scale the Security team's impact beyond what manual operations allow. We are looking for engineers who think like builders, not just operators — strong software skills are a must.
This role participates in an incident on-call rotation, but its core focus is engineering systems that reduce risk, speed up investigations, and make incidents less frequent and less costly.
Location/City: San Francisco or NYC
WHAT YOU'LL DO
- Own the detection lifecycle: Translate threat models, incidents, and attacker behavior into telemetry requirements and detections-as-code. Validate coverage, measure signal quality, tune false positives, and continuously test whether defenses work.
- Build security monitoring and telemetry: Design the telemetry pipeline end-to-end across cloud (GCP/AWS), Kubernetes, and the LangSmith/LangGraph control plane. Instrument services, define the signals that matter, and make security data reliable and useful.
- Engineer investigations and threat hunting: Build tools and workflows for proactive hunting, evidence collection, incident scoping, and containment. Turn investigation findings into new detections and lasting improvements.
- Use agents to scale the team: Build reliable internal AI agents and automation that triage alerts, enrich findings, gather evidence, scope incidents, and accelerate routine security work. Design human-in-the-loop controls and evaluations so automation is safe, observable, and trustworthy.
- Lead incident response and participate in on-call: Triage, scope, contain, and remediate security incidents, then drive postmortems that produce durable engineering changes.
- Partner with Product Security: Turn product threat models and vulnerability findings into production monitoring, and feed real-world detection and incident learnings back into secure design.
WHAT YOU'LL BRING
- 5+ years in security engineering, with meaningful experience in detection engineering, security operations, or incident response — and the software skills to build your way out of repetitive work.
- Strong software engineering in Python or Go (TypeScript a plus). You design maintainable systems and write production code, not just one-off scripts.
- Cloud and Kubernetes detection depth: Experience with GCP or AWS logging, Kubernetes audit and runtime telemetry, workload identity, and turning raw signals into actionable detections.
- Detection and adversary expertise: The ability to model realistic attacker behavior, hunt across complex systems, test detection coverage, and distinguish meaningful signal from noise.
- Hands-on incident response: You've participated in on-call, led incidents, and written postmortems that changed how a team operates.
- Experience building reliable automation or developer-facing systems: You can design APIs and workflows, instrument what you build, evaluate quality, and operate it in production.
- A pragmatic product mindset: You can identify users and requirements, prioritize the highest-leverage problems, define success, and ship iteratively.
NICE TO HAVE
- Experience building or operating AI agents for security workflows such as alert triage, investigation, evidence collection, or human-in-the-loop response.
- Proficiency using AI tooling to accelerate security investigations and engineering work.
- Understanding of AI threats, adversarial testing, and the security boundaries of LLM and agent workloads.
- Exposure to SOC 2 or ISO 27001 monitoring and evidence automation.
- Experience with infrastructure as code such as Terraform or Helm.
- Experience securing both SaaS and self-hosted or air-gapped deployments.
Annual salary range: $185,000- $250,000 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.
Location: New York, New York, United States
About Turing
Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at
www.turing.com
.
Role: AI Engagement Lead (Enterprise AI)
Location: New York, NY
Experience Level: 10+ years
Compensation: $225,000 to $255,000 base salary + bonus + equity
Work Model: Hybrid, three days per week in office
Why Join Enterprise AI?
Enterprise AI is a distinct business unit within Turing, operating with the speed, focus, and ownership of a rapidly scaling startup. When it comes to applied AI in the workplace, you’ll define the frontier by building beyond it.
As an AI Engagement Lead, you’ll own GenAI engagements for Fortune 500 clients end to end, from POC to full-scale implementation, while leading a team of Turing Forward Deployed Engineers. The Turing GenAI delivery organization has implemented multi-agent LLM systems, RAG systems, and open source LLM deployments for major enterprises.
This is a hybrid delivery and go-to-market role. Roughly 80% of your time goes to delivering for the client, and 20% to growing the account by extending projects and finding new opportunities across the client’s organization.
As an AI Engagement Lead, You Will
Lead from the Technical Front
Provide hands-on direction on solution architecture and system design, stay deep enough to review and step into your FDEs’ work, and keep the team aligned on a technical roadmap that ships on time.
Own the Client Relationship
Be the primary point of contact for client communication, feedback, and escalations. Build trust with stakeholders, manage expectations proactively, and bring new LLM research into the conversation to show what’s possible.
Grow the Account
Look beyond the current project. Identify the next phase, the future path for the team, and adjacent opportunities in the client’s organization, and select the use cases that unlock new revenue for the client and for Turing.
Lead the Team and the Delivery
Lead and develop a team of Forward Deployed Engineers, own delivery quality, scope, and timelines across one or two projects, and make decisions with gross margin, ROI, and long-term impact in mind.
Our AI Engagement Leads Typically Have
Deep technical leadership:
10+ years of professional experience, including at least 4 years driving machine learning and AI projects and experience leading engineering teams as an engineering manager or technical lead.
Hands-on GenAI expertise:
Strong command of agentic designs and frameworks such as LangChain and LangGraph, and cloud services on Azure, GCP, or AWS.
Client-ready communication:
Excellent communication and stakeholder management, with a track record of owning client relationships.
Founder’s mindset:
The drive to own end-to-end GenAI deliveries and grow accounts, plus familiarity with Agile methodologies and tools like JIRA and Confluence.
Values
We are client first:
We put our clients at the center of everything we do, because their success is the ultimate measure of our value.
We work at Start-Up Speed:
We move fast, stay agile and favor action because momentum is the foundation of perfection
We are AI forward:
We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.
Advantages of joining Turing
Work at the frontier of AI
, helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks.
Contribute to leading-edge AI research
and showcase your work at top conferences such as ICLR, ICML, and NeurIPS.
Bring frontier AI innovation to the enterprise
, applying lessons learned from leading AI labs to solve real-world business challenges.
Collaborate with and learn from exceptional colleagues
with deep AI experience from Google, Meta, Amazon, and other leading technology companies.
Move at the pace of AI innovation
, with the speed, ownership, and impact of a startup.
Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
For applicants from the European Union, please review
Turing's GDPR notice here
.
Location: San Francisco, CA
Workplace: OnSite
ABOUT US
At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale.
We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry.
More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale.
ABOUT THE ROLE
Cloud providers and Systems Integrators help LangChain reach customers that our direct sales and customer engineering teams can't reach on their own. This role is the technical foundation behind that ecosystem.
You'll build the reference architectures, integration patterns, and enablement programs that make partner motions work technically: co-sell with cloud hyperscalers, and independent delivery capability at systems integrators and global systems integrators (GSIs). You build with and for a partner, whose technical team then takes what you built to dozens of their own clients.
About the role
AWS, Google Cloud, and Microsoft Azure help LangChain reach customers that our direct sales and customer engineering teams can't reach on their own. This role is the technical foundation behind those cloud alliances.
You'll build the reference architectures, integration patterns, and co-sell assets that make our cloud motions work technically. That covers marketplace listings and private offers, joint solutions with cloud field teams, and technical wins on named accounts. You build with and for each cloud provider, and their partner and field teams then take what you built to many of their own customers. When a cloud deal involves a services partner, you make sure that partner can deliver on LangChain.
Key responsibilities
Cloud partner engineering (AWS, GCP, Azure)
- Own the technical relationship with partner and field teams at AWS, Google Cloud, and Microsoft Azure
- Build reference architectures and integration patterns for running LangChain, LangGraph, DeepAgents and LangSmith on each cloud, including integrations with each provider's native AI and data services (for example Amazon Bedrock, Gemini Enterprise, AzureAI)
- Support the technical side of co-sell: joint solution briefs, deployment guides, and validated architectures that cloud sellers can bring to their customers
- Partner with cloud account teams on solutioning for named accounts, from discovery through technical win
- Keep our marketplace listings, deployment options, and co-sell technical assets current as the product evolves
- Enable cloud field and partner teams through workshops, demos, and technical briefings so they can position LangChain without pulling in our engineers for every deal
- Build and maintain joint technical plans with each cloud provider, turning shared account and industry priorities into a concrete set of reference assets
Marketplace motions with services partners
- Support systems integrators and resellers when they're part of a cloud deal, such as marketplace private offers transacted through a channel partner or joint deployments on a customer's cloud
- Give those partners the technical assets they need to scope and deliver LangChain on AWS, GCP, or Azure, using existing reference architectures and implementation guides rather than a standalone enablement program
Partner technical evangelism and feedback
- Serve as a technical escalation point for complex deployments sourced through cloud partners
- Represent LangChain at cloud provider events, summits, and joint webinars
- Gather feedback from cloud partners and the field, and route it back to product and engineering
What we're looking for
7+ years of experience in a technical, partner-facing or customer-facing role such as Partner Engineer, Partner Solutions Architect, Solutions Architect, or Sales Engineer. Experience at or alongside a hyperscaler is a strong plus. We also like former founders and technical leaders, so if you have an unusual background but the right skill set, you're welcome to apply.
Cloud and partner experience
- Track record of working with AWS, Google Cloud, or Microsoft Azure partner and field teams to drive co-sell, from joint solution design through technical win
- Familiarity with cloud marketplace mechanics such as listings, private offers, and channel partner offers, and with hyperscaler co-sell programs
- Experience enabling a partner's field or technical teams so they can position and deploy a product without depending on you for every deal
- Comfortable working across engineering, partnerships, and sales at the same time
- Strong presentation and technical communication skills, able to translate between technical and business stakeholders, including C-suite executives
Agent engineering and development
- Hands-on experience building with LLM frameworks such as langchain, langgraph, or similar, including RAG patterns and agent architecture
- Experience designing evaluation frameworks and iterating on prompts and agent behavior based on results
- Strong Python skills
Cloud architecture and integration
- Deep working knowledge of at least one of AWS, GCP, or Azure, and familiarity with the other two. Strong background in GCP or Azure preferred.
- Hands-on experience with cloud AI platforms and managed model services
- Experience designing integrations, sample repositories, or reference architectures that other teams can pick up and reuse
- Familiarity with vector stores, tool integration, and API design in agentic systems
Key attributes
- You build credibility with a cloud provider's technical and field teams and act as their trusted advisor on LangChain
- Building and evangelizing are both part of the job. You're equally comfortable writing an integration and presenting it at a cloud summit
- You build assets that scale. A reference architecture should work across every cloud account team, not only the one in front of you
- You're comfortable with variety. AWS, GCP, and Azure each have their own programs, sellers, and ways of working, and switching between them doesn't throw you off
LOCATION:
San Francisco
COMPENSATION:
$185K to $225K
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: Remote - US
Workplace: Remote
ABOUT US
At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale.
We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry.
More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale.
ABOUT THE ROLE:
This position can be based remotely in
We’re looking to bring on an experienced frontend engineer to develop and enhance new features on LangSmith, our enterprise platform product for LLM application observability, testing, and debugging.
WHAT YOU WILL DO
- Develop new user-facing features using React & Typescript
- Build reusable components and front-end libraries for future use
- Translate designs and wireframes into high-quality code
- Optimize components for maximum performance across a vast array of web-capable devices and browsers
- Collaborate with fullstack and backend developers and UX/UI designers, to enhance usability
WHAT YOU WILL BRING
- Extensive front-end engineering experience with strong proficiency in React, JavaScript and TypeScript
- Hands-on experience with front-end development tools like Babel, Vite, Webpack, NPM, and Yarn
- Familiarity with REST APIs and experience working closely with fullstack and backend engineers
- Knowledge of modern authorization mechanisms, such as JWTs
- A passion for user experience, design and building clean, engaging, and intuitive interfaces
- Strong written and oral communication skills, with the ability to explain technical concepts clearly and concisely to both technical and non-technical stakeholders
- The DNA to thrive in a start-up, fast-paced environment. You view unstructured environments as an opportunity to make the most impactful work and to help define what's next.
- An ownership mind-set. You are self-driven and look for opportunities to make an impact.
- Strong computer science fundamentals, ideally with a degree in computer science or related field.
Compensation
Annual salary range: $180,000-$240,000 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:
— Проектировать и разрабатывать Python-сервисы и REST API платформы;
— Строить и поддерживать конвейеры обработки данных;
— Разрабатывать интеграции с внутренними источниками данных;
— Реализовывать поисковые и AI-ориентированные рабочие процессы на платформе;
— Создавать инструменты для измерения и поддержания качества системы;
— Отвечать за развертывание и эксплуатацию сервисов при запуске;
— Участвовать в планировании дорожной карты и архитектурных решениях.
Требования:
— Владение Python;
— Опыт создания backend-сервисов и проектирования REST API (FastAPI / Django REST / Flask);
— Опыт работы с реляционными базами данных (PostgreSQL / MySQL);
— Опыт работы с очередями и фоновыми задачами (Celery / RabbitMQ / Kafka);
— Знание Redis (кэширование, очереди, pub/sub);
— Интеграции с API третьих сторон: REST, OAuth, webhooks;
— Опыт работы с Docker, S3-совместимым хранилищем;
— Культура тестирования (pytest), workflow PR/code review, понимание CI/CD и наблюдаемости;
— Будет плюсом: системы RAG, embeddings, векторные базы данных (pgvector);
— Работа с LLM API (Anthropic, OpenAI): prompting, tool calling;
— Фреймворки агентов (LangChain, LlamaIndex, LangGraph);
— Фреймворки оценки LLM (RAGAS, deepeval);
— Инструменты быстрого прототипирования AI (Streamlit, Gradio);
— Современные инструменты Python (ruff, uv, pyproject.toml, pyright).
Условия:
— Конкурентная компенсация;
— 100% компенсация отпусков и больничных;
— 12 дополнительных оплачиваемых выходных в году;
— Бюджет на личное образование, языковые курсы и спорт;
— Участие в конференциях отрасли;
— Отсутствие бюрократии и поддерживающая, прозрачная культура.
Location: San Francisco, CA; Boston, MA; New York, NY
Workplace: OnSite
ABOUT US
At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale.
We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry.
More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale.
About The Role:
We’re looking to add a frontend engineer to develop and enhance new features on LangSmith, working on our enterprise platform product for LLM application observability, testing, and debugging.
*This role can be based in our San Francisco, New York, or Boston office. Employees within commuting distance work from the office five days per week. Candidates who live outside commuting distance (e.g. >1hr each way), may be eligible for hybrid arrangements depending on location and role requirements.
What You Will Do:
- Develop new user-facing features using React & Typescript
- Build reusable components and front-end libraries for future use
- Translate designs and wireframes into high-quality code
- Optimize components for maximum performance across a vast array of web-capable devices and browsers
- Collaborate with fullstack and backend developers and UX/UI designers, to enhance usability
What You Will Bring:
- 2+ years of Front-end engineering experience with strong proficiency in React, JavaScript and TypeScript
- Hands-on experience with front-end development tools like Babel, Vite, Webpack, NPM, and Yarn
- Familiarity with REST APIs and experience working closely with fullstack and backend engineers
- Knowledge of modern authorization mechanisms, such as JWTs
- A passion for user experience, design and building clean, engaging, and intuitive interfaces
- Strong written and oral communication skills, with the ability to explain technical concepts clearly and concisely to both technical and non-technical stakeholders
- The DNA to thrive in a start-up, fast-paced environment. Views unstructured environments as an opportunity to figure out the most impactful work and help define the future success of the company
- An ownership mind-set. You are self-driven and look for opportunities to make an impact.
- Strong computer science fundamentals, ideally with a degree in computer science or related field
Compensation
- Annual salary range: $160,000-$195,000 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.
Location: New York, NY
Workplace: Remote
ABOUT US
At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale.
We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry.
More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale.
ABOUT THE ROLE
We are looking for a Regional Director of Sales to lead revenue growth across a defined region within the Americas. This is a critical frontline leadership role for someone who has managed high-performing enterprise Account Executives, understands complex technical sales cycles, and is excited to help build the go-to-market motion for one of the most important categories in software.
As Regional Director, Sales, you will own regional revenue execution, pipeline development, forecast accuracy, and team performance. You will lead a team of quota-carrying Account Executives selling to technical, product, and business stakeholders at high-growth startups and large enterprises.
This role is ideal for a hands-on sales leader who combines strong operating discipline with curiosity about AI, developer platforms, and emerging infrastructure markets. You should be comfortable staying close to deals, coaching sellers through complex cycles, and helping customers understand both immediate use cases and long-term strategic value.
WHAT YOU’LL DO
- Own regional revenue targets, pipeline generation, forecast accuracy, and overall sales execution.
- Lead, coach, and develop a team of enterprise Account Executives.
- Build a culture of accountability, customer obsession, strong qualification, and consistent execution.
- Partner closely with Sales Engineering, Customer Success, Product, Marketing, and Sales leadership to improve win rates and customer outcomes.
- Drive disciplined execution across territory planning, account strategy, opportunity qualification, mutual action plans, forecasting, and expansion motions.
- Stay deeply engaged in strategic opportunities, including executive alignment, deal strategy, negotiation, and closing.
- Coach the team on selling to technical and executive audiences, including engineering leaders, AI teams, platform teams, product leaders, and business stakeholders.
- Inspect pipeline rigorously, identify risks early, and ensure clear next steps across priority opportunities.
- Develop a clear view of market demand, buyer personas, competitive dynamics, and customer pain points across your region.
- Help refine LangChain’s enterprise sales motion as we scale from early GTM into a more repeatable, predictable sales organization.
- Recruit, onboard, and retain high-performing sales talent as the region grows.
WHAT WE’RE LOOKING FOR
- 7+ years of enterprise software sales experience, including 2+ years leading quota-carrying sales teams.
- Proven track record managing teams that sell complex technical products to enterprise customers.
- Experience hiring, coaching, and developing high-performing Account Executives.
- Strong command of enterprise sales fundamentals: qualification, discovery, value selling, mutual action plans, forecasting, negotiation, and executive engagement.
- Experience selling to technical buyers such as engineering, infrastructure, data, AI/ML, developer platform, or product teams.
- Ability to operate in a fast-moving, early-stage or high-growth environment where playbooks are still being built.
- Strong cross-functional instincts and a collaborative approach to working with Product, Engineering, Marketing, Sales Engineering, and Customer Success.
- Excellent communication skills, with the ability to simplify complex technical concepts for different audiences.
- High ownership, low ego, and a willingness to be hands-on with customers, deals, and team development.
NICE TO HAVE
- Experience selling developer tools, infrastructure software, observability, data platforms, ML/AI tooling, or open-source commercial products.
- Familiarity with LLMs, AI agents, RAG, observability, evaluations, or modern AI application development.
- Experience helping scale a regional sales function at a company moving from founder-led or early GTM to a more repeatable enterprise sales motion.
- Experience with MEDDIC, MEDDPICC, Command of the Message, or similar enterprise sales methodologies.
- Prior success selling into both digital-native and large enterprise accounts.
- Experience working in a highly technical, product-led, or open-source-influenced sales environment.
WHY JOIN US
AI is changing how software is built, deployed, and operated. LangChain is at the center of that shift. This is an opportunity to help build the sales organization for a category-defining company, work with highly technical and ambitious customers, and shape how enterprises adopt production-grade AI systems.
You’ll join a team that values ownership, clarity, curiosity, and pace — and you’ll have the opportunity to make a meaningful impact on the company’s growth trajectory.
Compensation: $350,000 - $400,000 OTE + Equity
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: Canada
What The Role Is
As a
Senior Engineer
at Babylist, you take on hard problems and own them end-to-end. Millions of families depend on what we build. Agents write most of the code now. So the hard part is yours: what to build, how it should work and whether what shipped was right. You're still in the code for the genuinely hard problems. Agents handle the volume. You spend your time on the parts that need a person.
We're building well beyond the registry now: the financial side of raising a kid, maternal health made simpler and more human, the education new parents are looking for and the community around them. The hard problems run across all of it, plus the platform underneath and the AI we already ship to families. You'll start on a team, but you won't be boxed into it. The roadmap is open, your scope grows as you do and you have a say in what you take on next. Senior here means owning whole problems; Staff is the next step up, setting direction across a domain.
What You'll Own
A Senior Engineer here owns problems, not just features. You're handed an outcome, you decide what to build, ship it and own whether it worked. You act on incomplete information and change course fast when the evidence says you were wrong.
What you do depends on what the team needs:
Frame the problem with your PM as a peer, run the experiment and bring customer evidence into what gets built.
Harden a critical path, kill a class of incidents or design the abstraction your team builds on.
Be the reviewer people want on the risky changes.
Manage up with crisp choices: raise the risks early and protect the right tradeoffs.
Share what you're learning about AI openly, so the whole team gets sharper.
A few problems people at this level are working on right now:
Deciding what the registry recommends to each family, from the ranking to the model behind it, and proving in a live experiment that it actually helps.
Building the evals system that catches our AI support agent making things up before a customer does.
Making a child's info one source of truth instead of five disconnected flows, so parents set it up once and new products like Early Investor build on it.
Who You Are
You've been shipping production systems for years, and you've got the judgment to show for it. You can pick up an ambiguous problem and start moving before anyone hands you the full picture.
The strongest Senior engineers here are generalists, and usually the most prolific builders on their team. You go wherever the problem leads: a backend service one week, a stubborn frontend bug the next, the data pipeline after that. When it's hard you dig in, and you learn unfamiliar parts of the stack fast. Range is the Senior signature.
Compensation
We post real numbers. For a Canada-based Senior Engineer, the starting base salary range is $255,900 to $318,600 CAD, plus a target annual bonus of 15 percent of base. That's total target cash of roughly $294,285 to $366,390 CAD. On top of that you get meaningful equity and an RRSP match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope.
How We Build
AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome. The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers.
The Stack
Core app:
Rails, Packwerk, React, TypeScript, Sidekiq
Mobile:
iOS (Swift), Android (Kotlin)
Data, search & events:
MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma
Machine learning:
deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow
AI & dev tooling:
Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim
Infra & ops:
AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly
Key integrations:
Shopify (payments), Iterable (CRM)
Why Babylist
An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done.
Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide.
How We Work
Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis.
How We Hire
Three rounds, usually two to three weeks, start to finish.
Recruiter conversation (30 minutes).
Trade context: what you want next, what we're building and straight answers on comp, team and remote.
Technical screen (1 hour).
One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles.
Final round (4 hours).
Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours.
If your timeline is tight, tell us and we'll move faster.
Benefits
Company-paid medical and fully covered dental and vision
A RRSP match
Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program
Winter Wonder Week, a paid company-wide week off at the end of the year
A remote-work stipend
Mental-health and wellness support
A Few Things To Know
We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws.
We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking.
If you have a family member or close relationship with a Babylist employee, let your recruiter know.
Official outreach only ever comes from an @babylist.com address.
Location: Canada
What The Role Is
As a
Staff Engineer
at Babylist, you own some of our hardest domains and decide where they go. Millions of families depend on what we build. Agents write most of the code now. So the hard part is yours: what to build, how it should work and whether what shipped was right. You're still in the code for the genuinely hard problems. Agents handle the volume. You spend your time on the parts that need a person. We're building well beyond the registry now: the financial side of raising a kid, maternal health made simpler and more human, the education new parents are looking for and the community around them. The hard problems run across all of it, plus the platform underneath and the AI we already ship to families.
You'll own a big piece of the product, but you won't be boxed into it. The roadmap is open. You have a say in which bets we make, and you pick what you take on next.
What You'll Own
A Staff Engineer here sets direction. You own a domain: a product surface, a platform area or a capability that cuts across several teams. You set where it's going over the next year or two, sequence the bets that get there and make the technical and product calls along the way. You're still in the code. We don't have architects who've stopped building. If you stepped away, multiple teams would feel it. Your influence shows up in the systems and the work other teams choose to build on. You don't need direct reports to have that reach. It comes from what you build.
In practice, you:
Take a fuzzy business problem from the first sketch through to production, and stay on the hook for whether it actually helped customers.
Build the platform or tooling other teams adopt by choice, and own it as it scales.
Make the architecture calls that span teams and the ones that are expensive to reverse.
Set the standard for how your domain builds with AI. Decide what good looks like, build the patterns and evals that get agents there and catch the output that's confidently wrong before it ships.
Partner with product, design and data as a peer, shaping what's worth building from the start.
Coach Senior engineers through the hard calls, the ambiguous ones as much as the technical ones.
A few problems people at this level are working on right now:
Resolving one customer across registry, shop and health, plus the friends and family buying for them, so personalization works everywhere without each team rebuilding it.
Designing the knowledge system our coding agents reliably load, and working out how much context actually helps before it starts to hurt.
Building Early Investor, our new family finance product, from scratch, on a deadline that can't move.
Who You Are
You've shipped production systems for enough years to have earned strong opinions, and you hold them loosely. You can pick up an ambiguous problem and start moving before anyone hands you the full picture. You've already changed how a team builds with AI, and the new way stuck. Most Staff engineers lean one of two ways, and both do well here. Some point their depth at the systems everyone runs on: the platforms, the reliability and security bar, the harnesses that make AI produce good code. Others point it at the customer: framing the problem with PMs as peers, owning a journey end to end, deciding what to build and learning whether it worked. You don't have to be both. You do have to be excellent at one and fluent in the other.
A few things that tend to be true of people who thrive here:
You measure yourself by impact: a customer outcome, or a system a dozen teams come to depend on.
You're curious: you spot problems before they're filed and push your own ideas until they ship.
Compensation
We post real numbers. For a Canada-based Staff Engineer, the starting base salary range is $299,300 to $372,600 CAD, plus a target annual bonus of 20 percent of base. That's total target cash of roughly $359,160 to $447,120 CAD. On top of that you get meaningful equity and an RRSP match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope.
How We Build
AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome.
The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers.
The Stack
Core app:
Rails, Packwerk, React, TypeScript, Sidekiq
Mobile:
iOS (Swift), Android (Kotlin)
Data, search & events:
MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma
Machine learning:
deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow
AI & dev tooling:
Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim
Infra & ops:
AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly
Key integrations:
Shopify (payments), Iterable (CRM)
Why Babylist
An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done.
Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide.
How We Work
Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis.
How We Hire
Three rounds, usually two to three weeks start to finish.
Recruiter conversation (30 minutes).
Trade context: what you want next, what we're building and straight answers on comp, team and remote.
Technical screen (1 hour).
One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles.
Final round (4 hours).
Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours.
If your timeline is tight, tell us and we'll move faster.
Benefits
Company-paid medical and fully covered dental and vision
A RRSP match
Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program
Winter Wonder Week, a paid company-wide week off at the end of the year
A remote-work stipend
Mental-health and wellness support
A Few Things To Know
We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws.
We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking.
If you have a family member or close relationship with a Babylist employee, let your recruiter know.
Official outreach only ever comes from an @babylist.com address
Задачи:
— разработка backend-сервисы и API на Python
— создание AI-агентов и AI-пайплайны с использованием LangChain, LangGraph или аналогичных инструментов
— работа с LLM: промптами, structured output, tool calling, контекстом и памятью
— участие в создании RAG-систем: загрузке документов, поиске информации и формировании ответов на основе источников
— интеграция решения с базами данных, внутренними API и внешними сервисами
— работа с очередями задач, кэшированием, логированием и мониторингом
— участие в проектировании веб-приложений: продумывать взаимодействие backend, frontend, баз данных, фоновых задач и внешних сервисов
— интеграция backend с пользовательскими интерфейсами и при необходимости внесение базовых изменений во frontend
— написание тестов, исправление ошибок и улучшение качества существующего кода
— участие в обсуждении архитектурных и технических решений
— быстрое создание прототипов, проверка гипотез и доработка решений по обратной связи пользователей.
Требования:
— коммерческий опыт разработки на python (fastapi, django или flask) и уверенное проектирование rest api
— sql и реляционные бд (postgresql), git, docker; понимание клиент-серверной архитектуры и http-стека (авторизация, аутентификация, обработка ошибок)
— базовая архитектура приложений: модульность, разделение ответственности, слои приложения, поддерживаемость кода и взаимодействие сервисов
— синхронная и асинхронная обработка, фоновые задачи, очереди сообщений и брокеры (например, celery с rabbitmq/kafka)
— практический опыт в ai/llm: разработка агентов и чат-ботов, использование langchain/langgraph, управление контекстом llm, оценка качества и защита данных
— rag-системы, векторные базы данных, работа с полуструктурированными данными (pdf, таблицы) через pandas/numpy
— кэширование, логирование и мониторинг (redis, elk/prometheus); базовое знакомство с ci/cd и развёртыванием
— websocket и потоковая передача ответов от llm; базовое понимание frontend (html/css/js, react/vue/next.js) для интеграции интерфейса с api
— использование современных ai-инструментов для ускорения написания кода, тестирования и подготовки документации
Условия:
— офисный формат работы: г. Москва
— ежегодный пересмотр зарплаты и годовая премия
— более 400 образовательных программ в СберУниверситете для развития
— спортзал и зоны отдыха
— расширенный ДМС, льготное страхование для семьи
— гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ
— подписка Прайм с возможностью совместного использования на трёх близких
— вознаграждение за рекомендацию друзей в команду Сбера.
Location: Dubai, United Arab Emirates
Job Description
We are seeking experienced
AI Engineers / Agentic AI Developers
to design, develop, and deploy enterprise-grade AI solutions with a focus on
Agentic AI
,
Large Language Models (LLMs)
, and
Retrieval-Augmented Generation (RAG)
. The successful candidate will be responsible for building intelligent AI agents and workflows capable of reasoning, planning, task execution, and orchestration while ensuring all solutions are deployed in an
on-premises environment
using local AI models and tools.
Key Responsibilities
Gather, analyze, and translate business requirements into scalable AI and Agentic AI solutions.
Design, develop, test, deploy, and maintain AI-powered applications and autonomous AI agents.
Build Agentic AI workflows capable of reasoning, planning, task execution, and orchestration.
Develop and integrate Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multi-agent architectures.
Integrate AI solutions with enterprise applications, APIs, databases, cloud services, and on-premises systems.
Optimize AI models, prompts, workflows, and application performance.
Ensure AI solutions comply with enterprise security, governance, privacy, and Responsible AI standards.
Prepare technical documentation, deployment guides, operational manuals, and knowledge transfer materials.
Provide technical support, troubleshooting, performance tuning, and continuous improvements.
Design and implement AI solutions using
on-premises infrastructure, local models, and enterprise-approved AI tools
.
Requirements
Bachelor's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field.
5+ years
of software development experience, including
2+ years
working with AI/Generative AI technologies.
Strong experience with
Python
and AI application development.
Hands-on experience with
Large Language Models (LLMs)
and prompt engineering.
Experience designing and implementing
Retrieval-Augmented Generation (RAG)
solutions.
Experience building
Agentic AI
or multi-agent systems.
Experience integrating AI applications with
REST APIs
, databases, and enterprise applications.
Familiarity with AI orchestration frameworks such as
LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen
, or similar.
Experience working with vector databases such as
Milvus, ChromaDB, FAISS, Pinecone
, or equivalent.
Knowledge of model deployment using
Ollama, vLLM, Hugging Face Transformers, NVIDIA NIM
, or similar on-premises inference platforms.
Experience deploying and managing AI solutions in
on-premises environments
.
Understanding of AI security, governance, privacy, and Responsible AI principles.
Experience with Docker, Kubernetes, Git, and CI/CD pipelines is preferred.
Strong analytical, problem-solving, communication, and documentation skills.
Preferred Skills
Experience with open-source LLMs such as
Llama, Mistral, Qwen, Gemma, or DeepSeek
.
Experience with GPU infrastructure and AI model optimization.
Knowledge of MLOps practices and AI monitoring.
Experience integrating AI solutions with enterprise platforms such as SAP, ServiceNow, Microsoft 365, or other enterprise systems.
Experience working in highly secure or regulated enterprise environments.
This JD is aligned with your requirement that
all AI use cases must run on-premises using local models and on-premises tools
, making it suitable for enterprise or government projects.
Location: Chicago, IL
Workplace: Hybrid
ABOUT US
At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale.
We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry.
More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale.
ABOUT THE TEAM
The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on.
This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite.
Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform.
ABOUT THE ROLE
The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world.
This will be a hybrid in office role in Chicago, IL.
WHAT YOU’LL DO
- Co-architect and co-build production AI agents with customer engineering teams
- Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations
- Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows
- Advise customers post-sale on architecture, best practices, and roadmap-level decisions
- Run technical demos, trainings, and workshops for developer audiences
- Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers
- Occasionally contribute code upstream when it meaningfully improves customer outcomes
- Travel to customers up to 25% of the time
WHAT YOU’LL BRING
- 6+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up
- Strong Python, JavaScript and systems fundamentals
- Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling
- Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations
- Can explain technical tradeoffs clearly and build trust with developer audiences
- Take responsibility for outcomes, not just recommendations
- Have a bias toward action and enjoy figuring things out as you go
- Are excited about operating AI agents in production, not just building demos
NICE TO HAVE’S
- You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks
- Worked with LLM evaluation, observability, or guardrails
- Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts
- Have shipped and operated production software and are comfortable owning systems under real-world constraints
COMPENSATION:
Annual OTE range: $200,000–$300,000 USD. Final compensation will depend on experience, skills, and location.
Looking for a hands-on implementation role focused on custom delivery, bespoke integrations, and scoped consulting projects? Please check out the Deployed Engineer (Professional Services) roles.
COMPENSATION PHILOSOPHY:
We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks.
We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.
BENEFITS
Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
Location: Denver, CO
Workplace: Remote
ABOUT US
At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale.
We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry.
More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale.
About LangChain
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 role:
We’re looking for an experienced Account Executive to join our growing GTM team and drive the next wave of growth at LangChain. In this role, you’ll own the full sales cycle helping technical teams at cutting-edge enterprise companies discover, evaluate, and adopt LangChain’s products.
This is a high-impact, high-visibility role where you’ll collaborate closely with engineering, product, and customer success teams to shape how GenAI is adopted across different domains. If you're a relationship-driven seller who thrives in fast-paced, unstructured environments and wants to be part of building the go-to-market motion from the ground up, we’d love to hear from you.
WHAT YOU’LL DO:
- Own and manage the full sales cycle, from lead stage to close with a strong bias for follow-up and follow-through
- Act as a trusted advisor to prospects and customers, learning their needs and demonstrating how our products can solve real problems
- Drive proof-of-concept efforts, working with sales engineers and product experts to demonstrate tangible value
- Stay on top of product updates and industry trends to educate customers and shape the conversation around GenAI adoption
- Build long-term customer relationships and support post-sale success in partnership with our deployment and support teams
- Negotiate pricing and deal terms and work with legal to redline contracts
- Bring customer insights back to product and engineering teams to inform the future roadmap and improve the user experience
- Help define and iterate on our sales playbook - your input will help shape our go to market strategies
How to be successful in this role:
- 5+ years of experience selling complex software to enterprise customers
- A relationship builder that garners trust quickly and approaches sales with empathy and curiosity
- Excellent communication and storytelling skills
- Technical acumen with the ability to establish credibility with technical decision makers.
- You thrive in fast-paced start-up environments and are energized by impact - you want to help evolve the playbook, not just follow one
- Driven and solutions-oriented; you know how to navigate roadblocks and keep deals moving forward
- Passionate about generative AI and excited to help customers navigate a rapidly evolving industry
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 salary: $350K OTE 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:
- разработка и поддержка Python-скриптов и микросервисов для интеграции AI-инструментов в банковские процессы
- исследование и пилотирование AI-платформ (OpenClaw, Claude Code, LangChain и аналоги) для автоматизации задач разработки и бизнес-процессов
- участие в проектировании бэкенд-компонентов для взаимодействия с LLM (совместно с командой)
- проведение экспериментов: тестирование гипотез, сравнение моделей и инструментов
- документирование результатов исследований и подготовка рекомендаций
- участие в Code Review
- работа в Agile-команде: участие в стендапах, спринтах и ретроспективах.
Требования:
- базовое знание Python (ООП, структуры данных, модули)
- понимание Git (коммиты, ветки, PR)
- основы SOLID и паттернов проектирования
- знакомство с FastAPI (учебные проекты) и pytest
- понимание SQL (простые запросы) и принципов БД
- общее представление о CI/CD (Jenkins) и сетевых протоколах
- понимание принципов работы LLM (на уровне концепций), опыт использования AI‑CLI (Claude Code, Codex и др. — достаточно пробовал)
Location: San Francisco, CA
Workplace: OnSite
ABOUT US
At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale.
We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry.
More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale.
ABOUT THE ROLE:
LangChain has strong technical credibility, a large developer community, and a lot worth saying. What we need now is someone to make sure we're saying it — consistently, strategically, and in ways that land.
We're looking for a Head of Narratives to own how LangChain shows up in the world across communications, brand, social, and design. This is a role for someone who thinks like a media company operator: always-on publishing, sharp editorial judgment, a clear point of view on the themes that matter, and a relentless focus on getting great narratives in front of the right people at the right time.
You'll lead an existing team of rockstars across brand, social, and design — each with deep expertise. Your job is to give the team a shared narrative direction, keep the output sharp and consistent, and make sure LangChain is building an audience that wants to hear from us.
This is a player-coach role. You'll set the direction but you'll also be in the work — shaping editorial, giving creative feedback, and reviewing and writing. The right person is opinionated about what good looks like and hands-on enough to help get there.
WHAT YOU'LL DO:
Communications
- Define the themes and narratives LangChain is hitting. Spearhead the direction on what LangChain should be known for and translate that into a rolling communications strategy the whole team is working from. This is the backbone of everything else.
- Own press and media relations. Kickstart our comms efforts, building and managing relationships with key journalists and outlets, drive proactive press coverage, and act as the point of contact for inbound media inquiries.
- Shape executive visibility and thought leadership. Identify the moments, platforms, and formats where LangChain's leaders should have a voice, and help them show up with a clear, consistent point of view.
- Lead announcement strategy. Plan and execute communications around major launches, funding, partnerships, and company milestones, working cross-functionally to make sure the story lands with the right audiences at the right time.
- Set and uphold the communications standard. Define LangChain's voice in the outside world and the quality bar for anything that goes out under its name.
Brand
- Shape brand direction in close partnership with the brand lead. The brand lead focuses on brand voice, visual identity, and standards. You'll work closely together to align on where the brand is headed, what it stands for, and how it shows up — with narrative and brand informing each other rather than operating separately.
- Stay close to major brand moments. Bring a point of view on concept and messaging for out-of-home, awareness campaigns, and other brand initiatives. Work with the brand lead to make sure what we're saying and how we're showing up are pulling in the same direction.
- Make sure brand and narrative feel like one thing. The brand should feel like a natural extension of the editorial point of view, and vice versa.
Social & Rich Media
- Partner with the social lead on strategy, themes, and goals. The social lead focuses on growing LangChain's social channels and ways to amplify our content and messaging. Work together to ensure social is amplifying the themes and narratives the broader team is driving.
- Shape LangChain's rich media approach together. Work with the social lead to develop a shared point of view on how video, audio, and other formats fit into the content mix — where they build audience, where they deepen credibility, and how to build the right execution muscle over time.
- Track what's working, what's not, and use it to sharpen direction. Stay close to performance across content, comms, brand, and social to have a better sense on where to focus, what narratives are resonating, and where to double down.
Brand Design
- Lead the creative direction for brand design in close partnership with our brand designer. Own the visual vision for how LangChain looks and feels — and work day-to-day with our brand designer to translate that into execution across campaigns, content, comms, social, and brand moments.
- Be a strong creative partner. Have a real point of view on what looks right, what earns trust with a technical audience, and where the work needs to go further. Give clear direction and help the designer do their best work.
- Keep visual identity consistent across every channel. A media company looks like itself everywhere it shows up. Make sure LangChain does too.
Team Leadership
- Lead by being in it. Develop your team by being close to the work — giving useful feedback, shaping output, and raising the bar through example.
- Build the operating rhythm. Establish the rituals and shared workflows — editorial planning, cross-functional reviews, publishing cadences — that help brand, social, comms, and design operate as a unit.
- Connect narrative to the rest of the business. Translate what marketing, sales, product, and leadership need into a narrative strategy your team can execute — and keep everyone aligned as priorities shift.
WHAT WE'RE LOOKING FOR:
- Ability to work like a media company operator. You think in publishing cadences, audience development, and narrative arcs — not just campaigns. You know what it takes to build an always-on narrative engine and keep it running at a high standard.
- Player-coach. You've led creative, comms, or content teams and know how to develop people — but you stay close to the work and make it better by being in it.
- Strong narrative instincts. You have a clear point of view on what makes a brand story work and can translate that into real direction across comms, brand, social, and design.
- Analytically grounded. You track what's working, form a view on why, and use that to make better decisions about where to focus. You connect creative work to business outcomes.
- Developer audience instincts. You understand what earns trust with technical audiences and can orient a creative team around that bar.
- Collaborative and clear. You work well with strong practitioners who own their domains — building alignment without stepping on what they own.
Nice to Have
- Experience leading narrative, brand, or comms teams at a developer-focused company
- Background in technical or developer marketing
- Familiarity with the AI/ML ecosystem and the tools developers use to build
- Track record running brand campaigns, including out-of-home or awareness programs
Salary Range: $200K-$240K
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:
— развитие и оптимизация существующих ИИ-агентов
— проектирование архитектуры новых компонентов
— разработка многошаговых агентных сценариев с использованием LangChain и LangGraph
— проектирование логики взаимодействия агентов с LLM, базами данных, внутренними API и корпоративными сервисами
— разработка backend-сервисов ИИ-агентов на Python
— реализация RAG-сценариев, поиск по корпоративным данным и работу с векторными базами данных
— улучшение качества ответов агентов, устойчивость сценариев и корректность использования инструментов
— оптимизация производительности, задержки и стоимости LLM-запросов
— разработка механизмов хранения состояния, истории диалогов и контекста пользователя
— анализ ошибок агентов и устранение причины некорректного поведения
— участие в тестировании, мониторинге и подготовке решений к промышленной эксплуатации
— взаимодействие с разработчиками, аналитиками и представителями бизнеса при проработке новых сценариев.
Требования:
— оконченное высшее образование
— подтвержденный опыт коммерческой разработки на python от 5 лет
— уверенное владение FastAPI или аналогичным Python-фреймворком
— практический опыт разработки приложений на базе LLM
— опыт работы с LangChain и LangGraph
— понимание принципов построения ИИ-агентов: структура запросов, состояние, инструменты, маршрутизация, планирование и выполнение многошаговых сценариев
— опыт проектирования архитектуры сервисов и самостоятельной декомпозиции задач
— опыт работы с PostgreSQL
— опыт работы с векторными базами данных или расширениями для векторного поиска
— понимание принципов RAG, embeddings, semantic search
— опыт интеграции с внешними и внутренними API
— понимание асинхронного программирования в Python
— умение писать поддерживаемый код, покрывать критическую логику тестами
— способность самостоятельно исследовать проблему, предлагать решение и доводить его до работающего результата
— навыки работы с генеративными AI-моделями; опыт создания AI-агентов и использования их в работе будет преимуществом
— опыт использования GigaChat, Kandinsky и аналогов в продуктах, навыки создания и использования AI-агентов
— инструментальное владение AI для анализа, генерации и автоматизации.
Условия:
— комфортный современный офис рядом с м. Кутузовская (для офиса Кутузовский 32)
— ежегодный пересмотр зарплаты и годовая премия
— корпоративный спортзал и зоны отдыха
— более 400 образовательных программ СберУниверситета для профессионального и карьерного роста
— подписка Прайм с возможностью совместного использования на трёх близких
— расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа.
ОфисmiddleМосква
ОфисSan Francisco, CA; New York, NY
leadNew York, New York, United States; For applicants from the European Union, please review
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