MLOps Engineer (Python)

Why Integrations Engineering at Langfuse

Your work puts Langfuse into developers’ hands.

Our SDKs are downloaded 26M+ times per month, and for many developers the first thing they touch is an integration — a few lines of code that connect their favorite framework to Langfuse. When that experience is seamless, they’re wow’ed. When it’s not, we might have lost them. You’ll own that critical first impression across 40+ framework integrations.

You’ll live at the frontier of LLM application development.

The AI framework ecosystem moves fast — new agent frameworks, orchestration libraries, and model providers emerge every week. You’ll be among the first to instrument them, giving you unmatched exposure to how cutting-edge AI applications are built. The developers you serve are some of the most ambitious software engineers in the world, and working closely with them will make you an expert on LLM engineering yourself.

Everything you build is open source and immediately visible.

All Langfuse integrations are MIT-licensed. When you ship a new integration or improve an existing one, thousands of developers benefit the same day — and they’ll tell you about it in GitHub issues, on Twitter, and in our community channels.

What You’ll Do

• Build and maintain framework integrations. Langfuse integrates with 40+ frameworks and model providers: OpenAI SDK, Vercel AI SDK, LangChain, LlamaIndex, Pydantic AI, OpenAI Agents, CrewAI, Amazon Bedrock AgentCore, LiveKit, and many more. You’ll own these integrations end-to-end — from initial implementation to ongoing maintenance as frameworks evolve. When a new framework gains traction, you’ll be among the first to instrument it.

• Design new integration patterns for emerging frameworks. When a framework or a new agent orchestrator appears, you’ll evaluate it, design the right instrumentation approach (callback handler, decorator, OTEL auto-instrumentation, or a combination), build the integration, write the docs, and ship it. You’ll develop strong opinions on what makes a great integration experience.

• Contribute to the core SDKs. While integrations are your primary focus, your work will surface needs in our Python and TypeScript SDKs. You’ll contribute improvements to the core SDK when your integration work demands it — whether that’s a new hook point, better context propagation, or performance optimizations.

• Write documentation and integration guides. At Langfuse, docs are part of our core product. When you ship a new integration, the guide ships with it. You’ll own the integration docs, quickstart tutorials, cookbooks, and migration paths that help developers get started in minutes.

• Be a voice in the developer community. You’ll engage with framework communities, respond to integration-related GitHub issues, write blog posts about new integrations, and be present in our Slack/Discord channels. You’ll build relationships with framework maintainers and represent Langfuse in the broader AI developer ecosystem.

What We’re Looking For

• Passionate about the LLM ecosystem. You’ve built real applications with frameworks like LangChain, Pydantic AI, Vercel AI SDK, LlamaIndex, or similar — or you have a deep willingness to go deep and get your hands dirty with every major framework in the space. You’re excited about this ecosystem, not just familiar with it.

• Strong in Python and/or TypeScript. You write clean, reliable code. You don’t need to be a systems-level performance expert, but you care about code quality and understand that integrations run inside other people’s production systems.

• Product-minded engineer. You think about the developer who’s going to use your integration at 11pm trying to ship a feature. You obsess over the getting-started experience: how many lines of code does it take? Is the error message helpful? Does the docs example actually work?

• Self-directed and motivated. You know how to develop conviction about what to build and how to ship it. You don’t wait for detailed specs — you investigate the framework, talk to users, and propose the right approach.

• Excited about open source and developer community. You genuinely enjoy talking to developers about their integration challenges, writing clear documentation, and contributing to open source projects.

• Thrives in a small, accountable team. Your output is visible and matters. You’re comfortable owning outcomes, not just tasks.

CS or quantitative degree preferred, but not required. We care far more about what you’ve built and your hunger to learn.

Bonus Points

• Experience with OpenTelemetry internals or observability instrumentation

• Contributions to popular open source projects, SDKs, or developer tools

• Experience building developer tooling, CLIs, or client libraries

• Former founder or early startup experience

• Active presence in AI/ML developer communities (blog posts, talks, open source)

No candidate checks all boxes. If you feel you are a good fit for this role, please go ahead and apply.

Projects You Could Own

• Build and ship a Langfuse integration for an emerging agent framework (e.g., OpenClaw, new OTEL-based instrumentation)

• Design the integration pattern for a new category of AI tools (e.g., voice agents via LiveKit/Pipecat)

• Create comprehensive quickstart cookbooks that get developers from zero to traced in under 5 minutes

• Work with the OpenTelemetry community to improve GenAI semantic conventions

• Maintain and upgrade our most popular integrations (OpenAI, LangChain, Vercel AI SDK) as those frameworks ship breaking changes

Perks

• Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries.

• Healthcare - Employer contributions towards your healthcare.

• Equity in the company - Every new team member who joins our company receives stock options.

• Time off - Flexible time off in the US, generous entitlement in other countries.

• A USD$500 Home office setup if you’re a remote employee.

• Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites.

Culture - We All Shape It

As part of a rapidly scaling start-up, you will be instrumental in shaping our culture.

Are you interested in finding out more about our culture? Learn more about our values here. Check out our blog posts or follow us on LinkedIn to find out more about what’s happening at ClickHouse.

Equal Opportunity & Privacy

ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Please see here for our Privacy Statement.

Andersen is hiring an MLOps / Cloud Engineer (AWS) for a project developing an ML-powered image analysis platform to automate defect detection and improve industrial quality control.

Our customer is an international company providing specialized industrial materials and technology solutions to businesses across multiple sectors. Combining technical expertise with research and development capabilities, the organization helps customers improve manufacturing processes, enhance product quality, and increase operational efficiency. Its activities focus on delivering innovative solutions, supporting sustainable industrial practices, and adapting to evolving technological and market requirements.

The project is focused on developing and enhancing an image analysis platform for quality control in electroplating and surface finishing processes. It leverages Machine Learning and Computer Vision to automate defect detection, image segmentation, feature measurement, and comparison with expert reference values, enabling accurate, consistent, and objective quality assessments.

• Design and set up AWS architecture for the ML pipeline: image ingestion, inference, storage of images, metadata and results.
• Build CI/CD pipelines in GitLab for application and model components.
• Implement Infrastructure as Code with Terraform.
• Set up development, pre-production and production deployment targets.
• Automate provisioning and controlled teardown of test and pre-production environments.
• Containerize services and integrate S3 and RDS.
• Set up pipeline monitoring, logging and operational traceability.
• Document infrastructure and deployment for knowledge transfer.

• Experience in DevOps / Cloud for 5+ years, with AWS as the primary cloud platform.
• Hands-on experience deploying ML models or Python services on AWS, including SageMaker, inference endpoints, and Step Functions.
• Experience with MLOps tooling, including MLflow or similar solutions.
• Hands-on experience using Terraform in real-world projects.
• Experience building and managing CI/CD pipelines using GitLab CI (GitHub Actions is also acceptable).
• Experience with Docker and container deployment on AWS, including ECS, EKS, or Lambda.
• Experience working with S3 and RDS in delivered environments.
• Experience setting up and managing multi-environment infrastructure, including dev, pre-prod, and prod.
• Level of English – from Intermediate+ and above.

• Experience building infrastructure from scratch for new products.
• Experience working with hybrid on-premise and cloud environments.
• Knowledge of security and compliance practices, including ISO 27001 or similar standards.
• Experience working with GPU instances and managing cloud costs.

• Experience in teamwork with leaders in FinTech, Healthcare, Retail, Telecom, and others. Andersen cooperates with such businesses as Samsung, Siemens, Johnson & Johnson, BNP Paribas, Ryanair, Mercedes, TUI, Verivox, Allianz, T-Systems, etc..
• The opportunity to change the project and/or develop expertise in an interesting business domain.
• Job conditions – you can work both fully remotely and from the office or can choose a hybrid variant.
• Guarantee of professional, financial, and career growth! The company has introduced systems of mentoring and adaptation for each new employee.
• The opportunity to earn up to an additional 1,000 EUR per month, depending on the level of expertise, which will be included in the annual bonus, by participating in the company's activities.
• Access to the corporate training portal, where the entire knowledge base of the company is collected and which is constantly updated.
• Bright corporate life (parties / pizza days / PlayStation / fruits / coffee / snacks / movies).
• Certification compensation (AWS, PMP, etc).
• Referral program.
• Private health insurance and sports compensation, depending on the type of employment.

Join us!

• Building reliable, low-latency, high-throughput ML inference services
• Supporting online, async, and batch predictions
• Optimizing system performance, cost efficiency, and resilience
• Enabling safe deployment, rollouts, and lifecycle management
• Streamlining model integration and ops for practitioners
• Advancing cross-environment platform capabilities with portable abstractions
  
  
  

• Architect, build, and operate scalable, low-latency distributed ML inference services and prediction systems across online, async, and batch workloads.
• Manage production model deployments, model versioning, feature access, shadow/canary testing, and rollbacks.
• Optimize compute utilization (CPU, GPU, memory) and lead capacity planning to minimize operational costs.
• Operate multi-cloud and on-premise Kubernetes workloads with automated scaling, CI/CD, and IaC practices.
• Implement end-to-end telemetry (metrics, logs, traces, alerts), maintain SLIs/SLOs, and participate in on-call response to drive service resilience.
• Partner with ML Scientists and Engineers to productionize models, improve developer experience, and mentor junior team members.
  
  
  

• Experience deploying and operating ML models in production across backend, infrastructure, or SRE domains.
• Proficiency in Java, Scala, JVM languages, or Python with strong backend engineering skills.
• Proven background designing distributed systems (microservices, RPC, queues, streaming, caching, batch).
• Solid grasp of concurrency, resource management, and server-side profiling.
• Hands-on experience managing containerized Kubernetes workloads in production.
• Experience with cloud/hybrid infrastructure, core platform capabilities, IaC, and CI/CD.
• Observability experience using SLIs, SLOs, metrics, logs, dashboards, and alerts.
• Understanding of ML serving (real-time/batch inference, versioning, feature retrieval, monitoring).
• Familiarity with on-call, incident response, postmortems, and runbooks.
• Pragmatic, customer-focused mindset for designing reusable platform capabilities and communicating technical trade-offs.
• Strong cross-team collaboration and English communication skills.
  
  
  

• Experience with ML serving platforms, runtimes (Triton, ONNX Runtime, TF Serving, TorchServe), or gateways.
• Background in JVM tuning, low-latency systems, GPU scheduling, or SRE/platform engineering.
  
  
  

• Annual paid time off and generous paid leave scheme including: parent, grandparent, bereavement, and care leave
• Hybrid working including flexible working arrangements, and up to 20 days per year working from abroad (home country)
• Industry leading product discounts - up to 1400 per year - for yourself, including automatic Genius Level 3 status and Booking.com wallet credit
  
  
  

• Let’s go places together: How we Hire
• This role does not come with relocation assistance.