A career driven by you. At LeasingMarkt.de, we bring customers and dealers together to make car leasing more accessible, transparent, and efficient. With over 1,000 partner dealerships and nearly 2 million users across the DACH region and the Netherlands, we’ve become Germany’s #1 leasing platform. To keep growing and driving innovation in the mobility space, we’re looking for a Senior Software Engineer to join our high-performance team at our Düsseldorf office. 

As a Senior Software Engineer, you will play a key role in designing and developing robust, scalable applications that power one of the largest automotive leasing marketplaces in Europe. You’ll collaborate with a cross-functional team to build and evolve solutions that are architecturally sound, easy to maintain, and built for long-term impact. You’ll help shape technical direction while raising the bar for software quality and stability across the platform. 

What you’ll do:

• Join one of our builders’ teams to build great products loved by our customers. 
• Apply an AI-first mindset to every phase of you-build-it-you-run-it: from design and coding to testing, deployment and operations.
• Work hands-on in real product codebases (for example TypeScript/Node/Next.js or Java/Spring), using GenAI tools to accelerate development, improve quality and simplify existing systems.
• Build and evolve AI-powered internal tools and workflows (assistants for coding, reviews, documentation, testing) that engineers across AutoScout24 can rely on every day.
• Act as a multiplier and culture driver: coach teams on effective GenAI usage, share patterns and anti-patterns, and help establish AI-first ways of working across our engineering organization.
• Experiment, measure and improve: run small, data-informed experiments with teams, learn what works in our context, and turn successful approaches into repeatable standards and playbooks. 

What you’ll bring: 

• Experience leveraging AI and Generative AI (GenAI) to enhance engineering productivity — including code generation, debugging, reviews, documentation, and decision support — with a proactive mindset toward adopting tools that streamline development and drive innovation. 
• Deep, hands-on experience building production systems (we expect you’ve spent at least 5 years doing this, possibly much more), ideally with PHP and Laravel as well as TypeScript/Node.js/Next.js on AWS, Azure or GCP.
• Demonstrated personal excellence in using GenAI coding tools (for example GitHub Copilot, ChatGPT, Claude Code, Cursor, OpenAI Codex) to significantly improve your own development speed and quality: code generation, refactoring, debugging, tests and documentation. 
• Experience integrating LLM APIs (such as OpenAI, Anthropic, Azure OpenAI, Vertex AI or similar) into applications or internal tools.
• Strong communication and influencing skills: you can introduce new tools and practices, align stakeholders, handle skepticism and iterate based on feedback.
• A curious, growth-oriented mindset: you actively seek out new practices and tools, you are comfortable learning in public, and you help others do the same.
• A pragmatic view of GenAI: you understand its limitations and risks and know how to put guardrails in place (reviews, tests, policies) to keep usage safe, compliant and sustainable at scale.
• Experience with performance optimization, caching strategies, and system observability is a plus. 

A culture of growth  

With over 50 nationalities represented, we’re proud to welcome people of all backgrounds to our growing community, and we’re always finding new ways to help people feel welcomed and included. Here, you’ll have the tools, training and support you need to work in a way that suits you, learn new skills and reach your potential.  

For a career where you can drive our business and shape your future, apply now. 

Join Apaleo and Shape the Future of Hospitality Tech!

Apaleo is the world’s most open, API-first property management platform powering the next generation of hospitality operations. Its modular, AI-powered infrastructure enables hoteliers to customise their tech stack, automate routine work, and deliver seamless, personalised guest experiences, powered by best-in-class apps and autonomous AI agents that adapt to every stay.

We are looking for a Senior Backend Engineer (f/m/d) to build the foundation of Apaleo’s market-facing API layer, bringing agentic booking into hospitality and enabling the next generation of guest-facing AI experiences.

This is a highly autonomous role where you will design and ship the Storefront API, a production-grade, scalable interface that allows external systems (like ChatGPT and booking platforms) to interact directly with Apaleo.

You’ll operate at the intersection of backend engineering and AI, starting with clean API architecture and evolving into systems that power intelligent, agent-driven interactions.

What You’ll Be Up To

Build the Storefront API from Scratch

• Design and implement a production-grade, multi-tenant API / MCP
• Enable seamless integration with external platforms and AI agents
• Ensure scalability, reliability, and high performance from day one

Own the Full API Lifecycle

• Define API schemas and contracts (OpenAPI)
• Implement versioning strategies and backward compatibility
• Design authentication, authorization, and security patterns
• Build rate limiting and usage controls
• Ensure strong documentation and developer experience
• Set up monitoring and observability

Work Across Distributed Systems

• Integrate with existing .NET microservices
• Connect to event-driven systems (Kafka or similar)
• Navigate and improve a complex distributed architecture

Operate in the Cloud

• Deploy and manage services in AWS
• Work with Docker and containerized environments
• Contribute to infrastructure as code practices

Collaborate on AI-Driven Use Cases

• Partner with AI engineers to enable agent-based workflows
• Build APIs that integrate with LLM-powered systems
• Help evolve the platform toward AI-native product capabilities

Shape Engineering Standards

• Define best practices for:
  • API design
  • System architecture
  • Code quality and maintainability
• Contribute to how the ecosystem team scales and operates

What You’ll Bring to the Team

Core Requirements

• Proven experience building and operating production-grade APIs at scale
• Strong expertise in REST API design and architecture
• Solid experience with C# / .NET 8+
• Hands-on experience with AWS, Docker, and infrastructure as code
• Strong understanding of microservices and distributed systems
• Ability to work independently and make architectural decisions
• Interest in AI systems and integrations

Mindset & Traits

• Self-starter — you take ownership and drive work without waiting for direction
• Comfortable with ambiguity — you can build in evolving, low-structure environments
• Pragmatic decision-maker — you balance speed with long-term scalability
• Builder mindset — you enjoy creating systems from scratch
• Curious about AI — you’re motivated by where backend systems meet intelligent agents

Nice to Have

• Experience with:
  • Event-driven systems (Kafka or similar)
  • Multi-tenant SaaS architectures
  • Developer-facing or public APIs
• Exposure to:
  • LLM integrations or agent-based systems
  • Python
  • Any major frontend framework
• Background in hospitality tech (not required)

Why This Role Matters

This role is about more than building APIs, it’s about defining how external systems interact with Apaleo in an AI-first world.

You’ll:

• Lay the foundation for market-facing, AI-integrated products
• Enable guest-facing experiences powered by intelligent agents
• Help transform Apaleo into a platform ready for autonomous systems

What We Offer

Culture & Growth

• A Diverse & International Team: Work alongside passionate professionals from over 20 nationalities, bringing unique cultural perspectives, backgrounds, and experiences to shape the future of hospitality tech.
• Growth & Development: As we scale, so do your opportunities. You’ll benefit from 360° feedback reviews, a dedicated learning budget, and plenty of chances to take on more responsibility. Our evolving career framework ensures you have increasing opportunities to learn new skills, advance your career, and make an impact.
• Autonomy & Ownership: Great ideas can come from anywhere. We empower you to take responsibility, make decisions, and contribute directly in an environment built on trust, transparency, and collaboration.
• Shape the Future of Hospitality Tech: Be part of a fast-growing scale-up transforming the hospitality industry. From day one, your work drives real impact and you’ll have the freedom to bring your ideas to life.
• Competitive & Fair Compensation: We believe great work deserves great pay. Our salaries are competitive and guided by benchmarking data to ensure fairness across all roles and teams. We make sure to recognize and reward performance and contribution.

Perks & Lifestyle

• Flexible & Remote Work Options: We focus on results, not clocking hours. You can work from home, the office or in a hybrid setup, with flexibility to adapt your schedule as long as it makes sense for your role, your team and our business.
• Free Public Transport: Travel across Germany with ease using our fully covered Deutschland Ticket.
• Team Connection: Strong connections fuel collaboration. We celebrate and connect through regular team dinners, company meetups, Oktoberfest celebrations, Christmas parties, and other offsite events.
• Paid Time Off: Enjoy 30 days of vacation to fully disconnect, recharge, and return inspired.
• Health & Wellbeing: Prioritize your health with access to hundreds of gyms, fitness studios, and wellness options through our EGYM Wellpass membership.

You independently lead the most complex AI deployments Smartsheet undertakes. You own the full engagement lifecycle from technical discovery through production deployment through solutions org handoff. You architect multi-agent solutions, design client-personalized MCP resource packs, and build the Deployment Kits that transform how 200+ solutions consultants and partners operate. You mentor junior FDEs, drive the intelligence loop, and present field findings at weekly Applied AI strategy sessions. You are building a function, not filling a role.

What You Will Do

• Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout.
• Own the AI workshop program for your pod, customize modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning.
• Architect multi-agent solutions selecting the right coordination pattern for each customer’s workflow characteristics and compliance requirements.
• Design client-specific and industry-specific MCP resource packs that serve personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically.
• Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn’t done.
• Lead Solutions Enablement Sprints: transfer AI deployment patterns to solutions consultants and partners with training materials and certification criteria.
• Drive the intelligence loop: author strategic memos, present field findings weekly, contribute Agent Bricks and Skills, file RFCs for platform improvements.
• Mentor junior FDEs on customer engagements, code reviews, and Deployment Kit quality.

Required

• 6–10+ years production software engineering, including 3+ years deploying AI/ML to production. Deep Python; strong TypeScript/JavaScript.
• Proven track record leading complex enterprise technical engagements. You’ve managed customer relationships, navigated security reviews, and delivered production systems organisations depend on.
• Deep production LLM experience: multi-agent orchestration, MCP/tool-use, RAG optimisation, evaluation frameworks, agent deployment at scale.
• System architecture expertise spanning enterprise systems, cloud infrastructure, and AI services explainable to a CIO and a junior engineer.
• Demonstrated ability to create reusable technical assets that others use in production. You think in platforms, not projects.
• Strong written and verbal communication. Architecture documents, runbooks, strategic memos, training materials. Your Deployment Kits are your portfolio.
• You leave teams better than you found them. You make sure the people you work with understand what was built, why it works, and how to own it without you.
• Ability to travel.  This role requires domestic and international travel approximately 25–50% of the time.
• Elligible to work in Germany on an ongoing basis
• Fluency in English is required
• BS or MS in Computer Science, a related field, or equivalent industry experience

Nice to Have: 

• Experience founding or scaling an FDE/solutions engineering function. 
• Technical founder background. Databricks, AWS Bedrock, or Temporal experience. 
• Deep domain knowledge in healthcare, financial services, or government. Agent framework contributions (Strands SDK, LangChain, open-source MCP servers).
• Proficiency in German/French language will be an added advantage
• Familiarity of AI governance, ethics, and regulatory requirements (e.g. GDPR, UK/EU AI Act) 

Location: Berlin (Hybrid) Travel: ~25%

About Parloa:

Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience - one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like Booking.com, HealthEquity, Allianz, SAP, BarmeniaGothaer, and TUI already deploying Parloa at scale. 

About the role:

We are on a mission to transform how people interact with companies by making every conversation seamless, personalized, and human-like. Our AI Agent Management Platform empowers enterprises to create and manage AI voice and chat agents at scale, turning interactions into lasting relationships.

As our Deployment Strategist, you will drive AI transformation at Global 2000 enterprises as the “Field CPO” for Parloa’s most strategic customers. You will own the bridge between customer outcomes and product reality, translating business needs into deployable product capabilities for customers like Booking.com, Allianz, Decathlon, and TUI.

This is an opportunity to build a new industry. Agentic AI for enterprise is nascent. You’ll define what “good” looks like - at the forefront, with the hardest customers, solving the toughest problems.

Areas of ownership:

• Land big clients (Global 2000 with complex, off-roadmap needs) and ensure their AI transformation succeeds.
• Manage stakeholders across business and tech (CEO, COO, CIO, CTO, VP Support), owning deployment from value thesis through production to expansion.
• Translate customer needs into product capabilities (not one-off customizations) that become reusable platform features.
• Build prototypes, make product changes, and create business plans hands-on - execution over PowerPoints.
• Represent customers to Parloa Product and represent Parloa Product to customers, bridging both worlds.
• Navigate ambiguity in agentic AI workflows, ROI models, and change management where no playbook exists yet.
• Own hard conversations: tradeoffs, “no,” re-scoping, and timeline realism with strategic accounts.
• Influence without authority across Product, Engineering, Sales, and Customer Success to drive outcomes.
• Feed validated learnings to product roadmap, turning customer work into platform capabilities that compound.

Who you are:

• 7-12 years of experience in enterprise software (solution architecture, product, or consulting) with a proven track record of customer-facing delivery.
• “Field CPO” mentality: ability to translate customer outcomes into product reality and vice versa.
• Business + tech stakeholder leadership: presented to C-suite across business and tech functions, demonstrated value, and ensured solutions make business sense.
• Product thinking: built client-specific roadmaps aligned with platform strategy.
• Architectural credibility: scoped off-platform features, assessed feasibility, and ensured supportability.
• Influence without authority: led cross-functional teams (Product, Eng, Sales, CS) without direct reports.
• Adaptability: comfortable being uncomfortable, willing to learn, operates in ambiguity.
• Hands-on execution: gets hands dirty - built prototypes, made product changes directly, created business plans. Not just an advisor.

Nice-to-have:

• Industry diversity: experience in travel, fintech, insurance, retail, healthcare, telecom, or enterprise software - we’re building a team with a broad industry perspective.
• Industry-changing companies: worked at companies that transformed their industry (Booking.com, Decathlon, N26, Deel, Stripe, Uber, Airbnb).
• Hypergrowth experience: thrived in fast-scaling environments (e.g., 25 to 1500 people).
• Background as Palantir Deployment Strategist, AWS/GCP Solutions Architect, or product roles at hypergrowth tech.
• Tech stack: architectural understanding of Python, TypeScript, Terraform, K8s, Azure/AWS.
• AI/ML: LLM pipelines, agentic AI deployment, prompt engineering.
• Learning loop: created reusable patterns from custom work, fed learnings to product.

Our recruiting process:

TA Screen (45 min) → Hiring Manager Call (45 min) → Product + Commercial Stakeholder Call (60 min.) →Technical Stakeholder Call (60 min.) → Case Study (take-home) → Bar Raiser Interview (60 min.)

Ready to build a new industry? Submit your resume and a brief cover note: “What’s a customer outcome you owned? What did you personally build/execute (not just advise)?”

Why Parloa?

We’re at the beginning of a new era in customer experience, one where AI doesn’t just respond, but understands, reasons, and takes action. We’re building agentic AI that enterprises trust with their most important customer moments: complex questions, high volumes, real stakes. When millions of people reach out to a brand, those interactions aren’t just support tickets; they’re defining experiences. We’re here to raise the standard: making every conversation seamless, intelligent, and genuinely helpful. If you care about shaping how businesses and customers connect at scale—and want your work to matter in real, everyday moments—this is where you do it.

At Parloa, ownership isn’t a buzzword; it means being accountable for outcomes, not just tasks. We operate in a category that’s evolving fast, where the bar is high, and the problems are complex. We hire people who think in solutions, communicate with clarity, and follow through. People who are comfortable making decisions, taking responsibility, and raising the standard for themselves and those around them.

We’ve grown beyond the earliest startup phase, but we’ve kept the intensity: fast execution, direct feedback, and a strong expectation to contribute meaningfully from day one.

Backed by leading global investors like General Catalyst, EQT Ventures, and Altimeter Capital, we’re scaling with a clear ambition: to become the global category leader in enterprise-grade conversational AI.

About Parloa

Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience, one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like IKEA and Booking.com already deploying Parloa at scale. 

About the role:

As a Principal Applied Scientist at Parloa, you will define and drive our applied AI strategy across AI agents and Generative AI.

This is a highly hands-on and high-impact role at the intersection of research and production. You will explore, validate, and scale approaches that directly shape our product, from model evaluation and routing to agent behavior, memory, and context engineering, while defining how these systems should be measured, benchmarked, and improved across the industry.

Beyond execution, you will act as a technical leader: identifying opportunities, setting direction, and building the foundations of applied science at Parloa.

Areas of ownership:

• Define and lead applied AI initiatives across agent systems, LLM evaluation, and model optimization
• Own ambiguous problem spaces end-to-end: from framing and experimentation to production impact
• Design and implement evaluation & benchmarking frameworks, leveraging and challenging industry standards — and where needed, defining new ones
• Drive innovation in agentic systems, including topics like routing, memory, and context engineering
• Prototype and validate new approaches (e.g., model combinations, fine-tuning strategies, or open-weight models)
• Translate research into production-ready solutions, working closely with engineering teams
• Act as a technical authority and multiplier, mentoring others and shaping best practices
• Establish and lead the Applied Science guild, fostering knowledge sharing and raising the bar across teams
• Influence product and technical strategy, identifying where applied science can unlock the most value

Who you are:

• 12+ years of experience in Applied Machine Learning, Applied Science, or a related field, with a proven track record of delivering ML/AI systems in production
• Experience with agent-based systems or multi-step LLM workflows
• Strong recent experience working with LLMs and Generative AI systems, ideally in production environments
• Demonstrated ability to own and drive ambiguous problem spaces end-to-end—from problem framing to measurable impact
• Deep understanding of evaluation methodologies, benchmarking, and model performance analysis, including human-in-the-loop approaches
• Hands-on technical skills, with the ability to prototype, experiment, and ship solutions in collaboration with engineering teams
• Experience working on production systems, balancing speed, quality, and scalability
• Proven technical leadership and influence, with experience shaping direction, mentoring others, or driving cross-team initiatives
• Ability to operate at both strategic and execution levels, connecting long-term vision with day-to-day decisions
• Strong communication skills, with the ability to clearly articulate ideas and influence technical and non-technical stakeholders
• Evidence of broader impact (e.g., published work, open-source contributions, internal initiatives, or industry influence) is a plus

We know that great candidates don’t always meet every single requirement. If you’re excited about this role and believe you could make an impact, we encourage you to apply, even if your experience doesn’t perfectly match every qualification.

Nice to have

• Familiarity with model routing, fine-tuning, or open-weight models
• Background in human-in-the-loop evaluation or annotation systems
• Contributions to public research, blogs, or open-source projects

Our recruiting process:

Talent Acquisition → Technical Peer Interview → 360° Technical Interview Loop → Bar Raiser

Why Parloa?

We’re at the beginning of a new era in customer experience, one where AI doesn’t just respond, but understands, reasons, and takes action. We’re building agentic AI that enterprises trust with their most important customer moments: complex questions, high volumes, real stakes. When millions of people reach out to a brand, those interactions aren’t just support tickets; they’re defining experiences. We’re here to raise the standard: making every conversation seamless, intelligent, and genuinely helpful. If you care about shaping how businesses and customers connect at scale—and want your work to matter in real, everyday moments—this is where you do it.

At Parloa, ownership isn’t a buzzword; it means being accountable for outcomes, not just tasks. We operate in a category that’s evolving fast, where the bar is high, and the problems are complex. We hire people who think in solutions, communicate with clarity, and follow through. People who are comfortable making decisions, taking responsibility, and raising the standard for themselves and those around them.

We’ve grown beyond the earliest startup phase, but we’ve kept the intensity: fast execution, direct feedback, and a strong expectation to contribute meaningfully from day one.

Backed by leading global investors like General Catalyst, EQT Ventures, and Altimeter Capital, we’re scaling with a clear ambition: to become the global category leader in enterprise-grade conversational AI.

About Parloa

Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience - one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like Booking.com, HealthEquity, Allianz, SAP, BarmeniaGothaer, and TUI already deploying Parloa at scale.

About the role:

As a Senior Agent Architect at Parloa, you will play a key role in transforming customer service with AI Agents. In this customer-facing role, you will support the implementation of Parloa's solutions, enhancing customer experiences for clients and partners.

Using your expertise in Large Language Models (LLMs), Prompt Engineering, NLP & NLU conversational design, and integration platforms, you will craft effective AI workflows and build connections to enterprise systems and ensure quality, performance, and end-to-end operational readiness. You will design, prototype, and validate conversational solutions for AI agent deployments, including the integration layer that connects Parloa's platform to customers' existing technology stacks, and guide customers and partners in maximising the value of Parloa's AI solutions.

Areas of ownership:

• Scope and implement AI Agent deployments, providing strategic advice and execution support to customers and partners. 
• Leverage your knowledge of LLM internals (e.g., embeddings) to analyze customer requirements and design precise prompts for reliable, user-aligned behavior. 
• Simplify complex workflows and processes into digestible conversational components, enabling LLMs to handle challenging tasks effectively. 
• Fine-tune conversational flows and voice output (e.g., SSML, Lexicons, Regex) to align with customer brand standards. 
• Build and configure integrations between customers' systems and Parloa's Platform, connecting external tools (e.g., CRMs, ERPs, ticketing systems, contact center platforms) via integration platforms and APIs to deliver end-to-end enterprise solutions.
• Collaborate with Forward Deployed Engineers on complex or custom integration scenarios that go beyond standard integration capabilities. 
• Identify and solve blockers together with other departments at Parloa (e.g. Product, Agent Integration Engineering, or Sales) and the customer. 
• Apply structured testing approaches to validate AI agent behaviour, quality, and performance under real-world conditions. 
• Document best practices, how-to guides, and product capabilities for internal and external audiences, representing the expertise of the Agent Architect team.

Who you are:

• 3+ years of experience in enterprise customer-facing roles, with proven expertise in conversation design and AI agent development to create engaging and intuitive conversational experiences
• Ability to analyze customer requirements and craft LLM prompts that align with desired outcomes
• Entrepreneurial mindset with initiative, results orientation, and ability to identify opportunities for impact
• Proficiency with advanced prompting strategies such as chain-of-thought prompting, few-shot learning
• Strong project and stakeholder management skills, with passion for meeting milestones and effective communication
• Analytical and critical thinker with expertise in risk assessment, problem-solving, and strategy, plus solid knowledge of data structures, system integrations, and enterprise APIs
• Familiarity with API authentication patterns (OAuth, API keys, JWT), data transformation and field mapping logic
• Proficiency in REST API design, JSON/XML data structures, and API testing tools (Postman, etc.)
• Experience reading and consuming API documentation across enterprise SaaS platforms (CRMs, ERPs, contact center platforms)
• Exceptional attention to detail and logical thinking, with a proven ability to identify and address subtle nuances in conversational flows, ensuring a seamless and engaging user experience
• Familiarity with A/B testing methods to ensure AI agent performance at scale

Our Recruiting Process:

Talent Acquisition → Hiring Manager → Technical Interview(s) → Bar Raiser

Who we are

The role

At Helsing, we are redefining perception by building foundational intelligence for the physical world. You will research, design, and train large-scale Foundational Models that transform complex multimodal sensor data into cutting-edge autonomous capabilities.

We are seeking an individual at the intersection of AI Research and Machine Learning Engineering, with a proven track record in LLM/VLM/(multimodal) backbones. Your primary focus will be training and fine-tuning Vision-Language Models on our custom datasets to power our different products. You'll be responsible for the entire model lifecycle, from data curation and training to evaluation.

You should apply if you

• Hold an MSc or PhD in Machine Learning, Computer Science, or Mathematics with a focus on Deep Learning.

• Possess theoretical understanding and practical experience in training Foundational Models (LLMs, VLMs, or other large-scale multimodal models) from scratch or through fine-tuning.

• Have strong software engineering skills in Python and fluency with modern DL frameworks (PyTorch/JAX). You don’t just import libraries; you are comfortable writing custom layers, loss functions, and distributed training loops.

• Are a clear communicator who can build from complex theoretical concepts and contribute to the company's internal research culture.

• Have a "first-principles" mindset: you enjoy reading the latest ArXiv papers and implementing them into the codebase rapidly.

Note: We operate at an intersection where women, as well as other minority groups, are systematically under-represented. We encourage you to apply even if you don’t meet all the listed qualifications; ability and impact cannot be summarised in a few bullet points.

Nice to have

• Top-Tier Research Track Record: You have authored publications in top-tier conferences (NeurIPS, ICML, ICLR, CVPR, ACL) specifically regarding attention mechanisms, efficient transformers, or multimodal learning.

• Experience training models on large-scale GPU clusters.

• Proven experience in data curation, data cleaning, data pruning, and building robust data pipelines for large-scale datasets.

Join Helsing and work with world-leading experts in their fields

• Helsing’s work is important. You’ll be directly contributing to the protection of democratic countries while balancing both ethical and geopolitical concerns. 

• The work is unique. We operate in a domain that has highly unusual technical requirements and constraints, and where robustness, safety, and ethical considerations are vital. You will face unique Engineering and AI challenges that make a meaningful impact in the world. 

• Our work frequently takes us right up to the state of the art in technical innovation, be it reinforcement learning, distributed systems, generative AI, or deployment infrastructure. The defence industry is entering the most exciting phase of the technological development curve. Advances in our field of world are not incremental: Helsing is part of, and often leading, historic leaps forward. 

• In our domain, success is a matter of order-of-magnitude improvements and novel capabilities. This means we take bets, aim high, and focus on big opportunities. Despite being a relatively young company, Helsing has already been selected for multiple significant government contracts.  

• We actively encourage healthy, proactive, and diverse debate internally about what we do and how we choose to do it. Teams and individual engineers are trusted (and encouraged) to practise responsible autonomy and critical thinking, and to focus on outcomes, not conformity. At Helsing you will have a say in how we (and you!) work, the opportunity to engage on what does and doesn’t work, and to take ownership of aspects of our culture that you care deeply about. 

What we offer

• Competitive salary and VSOP options

• Relocation support: up to €2,500 and 4 weeks temporary accommodation

• Learning: €500/£450 yearly allowance

• Health & wellness: gym membership and mental health support (Nilo.health)

• Social: regular company events and monthly social allowances

• Enhanced parental leave: 22 weeks fully paid for primary caregivers & 6 weeks for secondary caregivers

• Family support: 5 days of paid family emergency leave, 100% remote work option during pregnancy and phased return to work

These are the core benefits across all locations, there may be additional benefits in certain locations.

Helsing is an equal opportunities employer. We are committed to equal employment opportunity regardless of race, religion, sexual orientation, age, marital status, disability or gender identity. Please do not submit personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, data concerning your health, or data concerning your sexual orientation. 

At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the world’s most robust and effective developer tools. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

We are now building services and agentic tools that provide AI coding agents and end users with deeper context about codebases. Our code retrieval service already delivers meaningful improvements in agent speed and task performance, and we aim to push this further – extracting richer insights than snippets alone at the scale of several hundred thousand repositories. 

We are looking for an AI Engineer who can design and implement agentic tools from scratch, bring them to the end users, and make coding with agents smarter, faster, and more reliable.

In this role, you will:

• Translate product needs into agentic tools and services and ship them to production.
• Scale prototypes to large numbers of users.
• Improve and test our semantic search service.
• Build evaluation pipelines for code retrieval and coding task performance.

We’ll be happy to have you on our team if you have:

• At least five years of hands-on NLP experience.
• Experience in information retrieval systems.
• Strong experience in LLM prompt and tool engineering, as well as with AI agents.
• Solid programming skills in Python and/or Kotlin (and the willingness to learn the language you’re unfamiliar with).
• Experience building and operating production-grade software systems.

We’d be especially thrilled if you have:

• Experience developing in Kotlin or Java.
• Previously worked with code intelligence (e.g. AST, symbol graphs).

#LI-DNI

Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning.

Spectrum collects data from an organization's code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that's extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge.

A resident of JetBrains' startup incubator, Spectrum enjoys startup speed and autonomy, and is backed by 25 years of developer tooling expertise. We are looking for a Senior ML Researcher to develop the core methods that make Spectrum possible – novel approaches to temporal ontology extraction, contradiction detection, and semantic alignment across heterogeneous software artifacts. You will help define and execute the research agenda, while also collaborating with JetBrains Research and external academic advisors.

Your responsibilities will include:

• Developing methods for LLM-based ontology construction from code, documentation, and issue trackers, including contradiction detection and reasoning over the resulting knowledge graph.
• Creating datasets, metrics, and benchmarks that drive measurable improvements across the system.
• Prototyping and validating research ideas, then collaborating with ML and software engineers to bring them to production.
• Collaborating with JetBrains Research and external academic advisors to shape our research agenda.
• Publishing research findings at top venues and representing Spectrum in the research community.

We expect you to have:

• A PhD (or equivalent research experience) in NLP, knowledge graphs, ontology learning, information extraction, or a closely related field.
• A strong publication record in at least one of the following areas: knowledge graph construction, ontology learning, information extraction, or NLP.
• Experience applying LLMs to structured knowledge extraction tasks.
• Experience designing and running rigorous experiments, including hypothesis formulation, ablation studies, and statistical evaluation.
• Strong Python and PyTorch skills, with the ability to implement research ideas from scratch.
• Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences.
• Proficiency in English, both written and verbal.

Our ideal candidate would also have:

• Experience with ontology engineering, semantic web technologies (OWL, RDF, SPARQL), or ontology alignment.
• A background in code analysis, developer tools, or software engineering research.
• Experience with knowledge graph embedding methods or graph neural networks.
• Experience in early-stage startups – you enjoy the zero-to-one phase.
• Actively contributed to relevant open-source projects.

What we offer:

• A competitive salary and JetBrains benefits.
• A generous runway and corporate resources with startup autonomy.
• Full support for publishing ML research and attending industry conferences.
• Collaboration with JetBrains Research and external academic advisors in the knowledge graph and ontology learning community.
• A motivated team that moves fast, with short feedback loops, rapid prototyping, and lots of ownership.
• A rare applied research role where your methods ship in a real product used by software teams.

Why join JetBrains? 

• Strong base salary. We offer competitive pay that reflects your skills and experience.
• Flexible work location. Enjoy the freedom to work from home or from the office.
• Remote work. Spend up to 30 days per year working remotely from abroad.
• Extra time off. More days to relax, recharge, and do the things you love.
• Medical insurance allowance. Enjoy peace of mind for you and your family
• Learning and development opportunities. Access to conferences, courses, and language classes.
• Language classes. Pick up the local language or sharpen your English skills.
• Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays.
• Mental health support. To help you feel your best, we provide easy access to professional mental health services.
• Sports benefit. Enjoy an on-site gym or sports club stipend.
• Internal events. Join company-wide celebrations and team gatherings.

*Some benefits may vary depending on location.

#LI-DNI

The impact you will make

For Finance, data is key. You will be the owner of our Finance digital infrastructure, ensuring our systems are always fit for purpose. With your support we will take our Finance processes to the next level of digitalization, leverage every AI-driven opportunity, and maintain high standards of data quality at all times. You will own Microsoft Business Central end to end, consolidate ERP ownership within Finance and build the automation infrastructure that allows Finance to scale without adding headcount. Our goal: enable our teams to focus their energy on solving the challenge of fusion, not on administrative processes.

Your responsibilities

• Take end-to-end ownership of Finance data and digital systems, with a strong focus on continuously innovating and optimizing Microsoft Dynamics 365 Business Central as the core ERP platform
• Own the BC product backlog: triage, prioritize and implement system improvements, configuration changes and new modules
• Lead the adoption and integration of AI-powered features and automation tools, leveraging MS Dynamics 365, Power Automate, Power Apps and Power BI
• Design, build and maintain Finance automation workflows using Power Automate, AI agents and API integrations
• Design and implement advanced KPI dashboards and predictive analytics solutions for actionable, forward-looking decision-making
• Serve as the internal SME and first point of contact for all Finance system questions, actively reducing external consultant dependency
• Drive month-end close to WD4 or earlier across all Group entities
• Collaborate closely with Finance, Purchasing, IT, FP&A, PMO and Corporate Development on cross-functional integrations
• Support the Finance team with a start-up mindset, championing innovation, agility and continuous improvement

What you bring

• In-depth hands-on experience with Microsoft Dynamics 365 Business Central across configuration, extensions, reporting and integrations, minimum 3 years in an ERP ownership or power-user role
• Practical experience with APIs, Power Automate and AI or LLM tooling in a Finance or ERP context
• First experience with Copilot Studio
• Strong understanding of Finance processes: AP, AR, month-end close and consolidation
• A degree in business administration, finance controlling or data analytics
• A keen eye for data quality with a solid grasp of data lifecycles and compliance-driven processes
• Strong analytical skills and a knack for finding practical solutions
• You bridge systems and business, not just IT
• Fluent in English, German is a plus

Nice to have

• Experience with agentic AI workflows or Copilot Studio in Finance environments
• Power Apps development for Finance-facing tools
• Exposure to supply chain or procurement modules within BC or a comparable ERP system

At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

The Python Ecosystem team builds PyCharm – one of the most popular Python IDEs in the world – along with the Python plugin for IntelliJ IDEA. As AI changes how developers write, debug, and ship code, we’re making our Python tools AI-native. We’re looking for an AI Lead to drive this effort by shaping the architecture, building key components hands-on, and guiding the team in making strong decisions around AI-powered product development.

In this role, you will:

• Lead the technical design of AI features in PyCharm and our Python tooling, including MCP integrations, agent workflows, tool design, and context management.
• Prototype and ship features yourself – this is a hands-on technical leadership role.
• Help the team adopt AI technologies effectively by providing technical guidance, reviewing approaches, and sharing practical patterns.
• Evaluate emerging AI tools, frameworks, and providers, and make pragmatic decisions about what to build and what to integrate.
• Work closely with product managers, ML engineers, QA specialists, and senior developers to turn product ideas into solid technical plans.
• Navigate a large Kotlin/Java codebase and expose IntelliJ Platform capabilities – such as code analysis, inspections, refactorings, and type inference – to AI-powered workflows.
• Contribute to cross-team AI efforts and help define shared engineering patterns where appropriate.

We’d love to talk to you if you have:

• Strong software engineering experience, particularly in Python and/or Kotlin/JVM.
• Deep, hands-on familiarity with modern AI tooling for developers, including coding assistants, agents, MCP, and LLM-based workflows.
• Experience working in large, mature codebases and delivering meaningful technical change without compromising quality.
• Familiarity with LLM evaluation and benchmarking.
• A track record of making good technical decisions in fast-moving, ambiguous areas like proposing architectures, building prototypes, and iterating based on feedback.
• Strong communication skills and the ability to influence technical direction without formal authority.
• A strong product sense and care about solving real user problems, not just building interesting technology.

Nice to have:

• Experience with IDE or developer tooling internals, such as language servers, code analysis, or related systems.
• Experience with the Python AI/ML ecosystem.

Why join JetBrains? 

• Strong base salary. We offer competitive pay that reflects your skills and experience.
• Flexible work location. Enjoy the freedom to work from home or from the office.
• Remote work. Spend up to 30 days per year working remotely from abroad.
• Extra time off. More days to relax, recharge, and do the things you love.
• Medical insurance allowance. Enjoy peace of mind for you and your family
• Learning and development opportunities. Access to conferences, courses, and language classes.
• Relocation support. We help make your move as smooth and stress-free as possible. (keep if relevant for the role)
• Language classes. Pick up the local language or sharpen your English skills.
• Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays.
• Mental health support. To help you feel your best, we provide easy access to professional mental health services.
• Sports benefit. Enjoy an on-site gym or sports club stipend.
• Internal events. Join company-wide celebrations and team gatherings.

*Some benefits may vary depending on location.

#LI-DNI 

Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning. 

Spectrum collects data from an organization’s code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that’s extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge.

Spectrum is a resident of JetBrains' startup incubator, with startup speed and autonomy, and backed by 25 years of developer tooling expertise. We are looking for a top-class ML Engineer who will help us shape the future of software development. You will own our AI and ML engineering stack and help define the research agenda for our team. Your technical vision and design decisions will directly shape the product and determine its success.

Your responsibilities will include:

• Designing and building the ML/LLM solution for data ingestion, knowledge extraction, retrieval, and subsequent reasoning.
• Creating the datasets, metrics, and pipelines that drive measurable improvements across the system.
• Architecting and improving agents for context retrieval, knowledge extraction, and data alignment, which includes prompt engineering, model selection, and inference optimization.
• Establishing MLOps practices, including orchestration, observability, and experiment tracking.
• Collaborating with the engineering team on system design and with JetBrains Research on the research agenda.
• Defining hiring criteria, growing the ML team, and shaping the ML team culture.

We expect you to have:

• A proven track record as an ML/AI Lead.
• At least five years of experience in ML/AI systems, with at least two years focused on LLMs and generative AI.
• A deep understanding of the LLM ecosystem, including model architectures and fine-tuning approaches.
• Hands-on experience with:
• Prompt engineering and LLM pipeline design, including evaluation.
• Agentic frameworks such as LangChain, LlamaIndex, LangSmith, smolagents, or an equivalent.
• Vector databases and retrieval-augmented generation (RAG) patterns.
• Deploying and scaling LLM-powered applications using APIs (e.g. OpenAI or Anthropic) or open-source models.
• Strong Python skills – Kotlin knowledge would be a plus.
• Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences.
• Proficiency in English, both written and verbal. 

Our ideal candidate would have:

• Experience with ontologies, knowledge graphs, or graph-based reasoning.
• Experience in early-stage startups – you enjoy the zero-to-one phase.
• The ability to think strategically about product-led AI, beyond just training models in isolation.
• A background in code analysis, developer tools, or software engineering research.
• Experience with multi-agent systems or complex agentic workflows.
• Actively contributed to relevant open-source projects or publications.

What we offer

• A competitive salary and JetBrains benefits.
• A generous runway and corporate resources with startup autonomy.

#LI-KP1

Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning.

Spectrum collects data from an organization's code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that's extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge.

A resident of JetBrains' startup incubator, Spectrum enjoys startup speed and autonomy, and is backed by 25 years of developer tooling expertise. We are looking for a Senior AI/ML Engineer to build and evolve the ML-powered systems at the heart of our product.

Your responsibilities will include:

• Designing and building the ML/LLM solution for data ingestion, knowledge extraction and retrieval, and subsequent reasoning.
• Creating datasets, metrics, and pipelines that drive measurable improvements across the system.
• Architecting and improving AI agents, which will involve prompt engineering, model selection, and inference optimization.
• Contributing to our MLOps practices, including orchestration, observability, and experiment tracking.

We expect you to have:

• At least four years of experience building ML/AI systems in production environments, with hands-on LLM experience.
• A deep understanding of the LLM ecosystem, including model architectures and fine-tuning approaches.
• Hands-on experience with:
• Prompt engineering and LLM pipeline design, including evaluation.
• Agentic frameworks such as LangGraph, Pydantic AI, or an equivalent.
• Retrieval-augmented generation (RAG) patterns and vector databases.
• Deploying and scaling LLM-powered applications using APIs (e.g. OpenAI or Anthropic) or open-source models.
• Strong Python skills – Kotlin knowledge would be a plus.
• Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences.
• Proficiency in English, both written and verbal.

Our ideal candidate would also have:

• Experience with ontologies, knowledge graphs, or graph-based reasoning.
• Experience in early-stage startups – you enjoy the zero-to-one phase.
• A background in code analysis, developer tools, or software engineering research.
• Experience with multi-agent systems or complex agentic workflows.
• Actively contributed to relevant open-source projects or publications.

What we offer:

• A competitive salary and JetBrains benefits.
• A generous runway and corporate resources with startup autonomy.
• A motivated team that moves fast, with short feedback loops, rapid prototyping, and lots of ownership.
• Opportunities to publish research at top venues in collaboration with JetBrains Research.

#LI-DNI

A career driven by you. Join AutoScout24 Group and experience life in the fast lane. We’re not just leading the market; we’re creating it. We’re constantly innovating, evolving, and transforming things for our customers. We’re driven, ambitious, and determined to do our best work together. For a career that doesn’t stand still, where you can put your ideas in the driving seat and change the way the world moves, join our international community. 

As Senior GenAI Data Scientist, you’ll join our Data Science organisation and drive the development of next-generation AI solutions across the company. You will take ownership of building agentic GenAI systems, integrating knowledge into models, and setting up strong evaluation and monitoring frameworks that ensure we deliver reliable, scalable, and high-value AI products. This position is permanent and located in Munich (Germany) or Toronto (Canada).

What you’ll do:

• Design and build agentic GenAI systems using modern frameworks such as LangChain, AutoGen or Atomic Agents, taking the lead on translating product needs into scalable AI solutions and delivering production-ready implementations.
• Develop and maintain knowledge integration pipelines, including RAG architectures, custom model fine-tuning, vector search, and other grounding methods to ensure our AI systems have the right context for accurate, relevant outputs.
• Define evaluation strategies, build ground-truth datasets, and create automated test and monitoring setups to ensure stable long-term model performance and proactively detect issues such as drift or hallucination.
• Collaborate with engineering, data, and product teams to integrate AI components into platforms, workflows, and customer-facing products, designing clean APIs, robust pipelines, and scalable deployment patterns.
• Act as a hands-on expert for GenAI topics, mentoring peers, guiding solution architecture, and driving best practices in coding, testing, observability, and documentation across the organisation.
• Experiment with new tools, models, and architectures, identify high-impact AI opportunities, and build prototypes that can scale into production-ready solutions. 

What you’ll bring: 

• A degree in computer science, data science, engineering, or a related field.
• Experience building agentic GenAI systems in production (e.g., LangChain, AutoGen, Atomic Agents, or similar frameworks).
• Strong coding skills in Python and experience with robust software engineering practices.
• Practical experience with RAG pipelines, vector databases, embeddings, or fine-tuning workflows.
• Strong understanding of common challenges in AI development (ground-truth evaluation data, monitoring, integration complexity, model drift).
• Experience deploying AI systems in a cloud environment and working with modern ML stacks.
• Familiarity with MLOps, prompt engineering, or LLM-based application design.
• Ability to explain complex AI topics in clear and actionable language to technical and non-technical stakeholders.
• High motivation, ownership mentality, and a strong drive to build impactful AI products.
• Fluency in English; German is a plus.

A culture of growth. With over 50 nationalities represented, we’re proud to welcome people of all backgrounds to our growing community, and we’re always finding new ways to help people feel welcomed and included. Here, you’ll have the tools, training and support you need to work in a way that suits you, learn new skills and reach your potential. 

For a career where you can drive our business and shape your future, apply now. 

A career driven by you. Join AutoScout24 Group and experience life in the fast lane. We’re not just leading the market; we’re creating it. For a career that doesn’t stand still, where you can put your ideas in the driving seat and change the way the world moves, join our global community. 

We’re hiring a strong Software Engineer / AI Enabler to multiply the impact of our Product & Technology organization. This role is for someone who is excited about GenAI’s boosting their own engineering performance and productivity and now wants to influence a large, ambitious organization—raising the bar for how software is delivered in a complex, established and market-leading business, not a greenfield startup. 

The engineering world is moving very fast. We are all learning every day. Your core traits should be curiosity and a strong drive to learn and grow. We do not expect you to know everything. We expect you to help accelerate our curiosity and learning culture, and to become AI-first together with us. 

What you’ll do 

• Join one of our builders’ teams to build great products loved by our customers.
• Apply an AI-first mindset to every phase of you-build-it-you-run-it: from design and coding to testing, deployment and operations.
• Work hands-on in real product codebases (for example TypeScript/Node/Next.js or Java/Spring), using GenAI tools to accelerate development, improve quality and simplify existing systems.
• Build and evolve AI-powered internal tools and workflows (assistants for coding, reviews, documentation, testing) that engineers across AutoScout24 can rely on every day.
• Act as a multiplier and culture driver: coach teams on effective GenAI usage, share patterns and anti-patterns, and help establish AI-first ways of working across our engineering organization.
• Experiment, measure and improve: run small, data-informed experiments with teams, learn what works in our context, and turn successful approaches into repeatable standards and playbooks. 

What you need to succeed 

• Deep, hands-on experience building production systems (we expect you’ve spent at least 5 years doing this, possibly much more), ideally with TypeScript/Node.js/Next.js or Java/Spring Boot on AWS, Azure or GCP.
• Proven experience working in large, existing codebases and delivering well-tested, maintainable features in web or backend services.
• Demonstrated personal excellence in using GenAI coding tools (for example GitHub Copilot, ChatGPT, Cursor, OpenAI Codex) to significantly improve your own development speed and quality: code generation, refactoring, debugging, tests and documentation.
• Experience integrating LLM APIs (such as OpenAI, Anthropic, Azure OpenAI, Vertex AI or similar) into applications or internal tools.
• Strong communication and influencing skills: you can introduce new tools and practices, align stakeholders, handle skepticism and iterate based on feedback.
• A curious, growth-oriented mindset: you actively seek out new practices and tools, you are comfortable learning in public, and you help others do the same.
• A pragmatic view of GenAI: you understand its limitations and risks and know how to put guardrails in place (reviews, tests, policies) to keep usage safe, compliant and sustainable at scale. 

With over 50 nationalities represented, we’re proud to welcome people of all backgrounds to our growing community. Here, you’ll have the tools, training and support you need to work in a way that suits you, learn new skills and reach your potential. 

For a career where you can drive our business and shape your future, apply now. 

A career driven by you. Join AutoScout24 Group and experience life in the fast lane. We’re not just leading the market; we’re creating it. We’re constantly innovating, evolving and transforming things for our customers. We’re driven, ambitious and determined to do our best work, together. For a career that doesn’t stand still, where you can put your ideasin the driving seat and change the way the world moves, join our global community.

We’re hiring a Software Engineer to join Search & Performance group at AutoScout24 – the group behind the Algorithms and Data Quality that powers the AutoScout24 Search Experience and Ad Products. This role is about real ownership: you’ll work on high-traffic systems, shape key parts of our user experience, and contribute to critical business outcomes.   

What you’ll do:   

• Work on product and tech initiatives finding the right mix between effort, quality and user value
• Optimize and improve the AS24 technology stack by targeting individual and team efficiency, applying future proven concepts, architectural principles, and frameworks
• Support our agile product development approach 

   What you need to succeed:   

• Deep expertise in Java and Spring Boot, with a breadth of knowledge across a range of languages and technologies in both Object-Oriented and Functional paradigms; able to quickly grasp new concepts and tools Experience with Scala is a plus
• 5+ years of Software Engineering experience, hands-on experience with PostgreSQL, DynamoDB, Kafka, and AWS is a strong plus
• Team player but also decisive mentality
• Demonstrated personal excellence in using GenAI coding tools (for example GitHub Copilot, ChatGPT, Cursor, OpenAI Codex) to significantly improve your own development speed and quality: code generation, refactoring, debugging, tests and documentation.
• Experience integrating LLM APIs (such as OpenAI, Anthropic, Azure OpenAI, Vertex AI or similar) into applications or internal tools.
• A pragmatic view of GenAI: you understand its limitations and risks and know how to put guardrails in place (reviews, tests, policies) to keep usage safe, compliant and sustainable at scale. 

A culture of growth  

With over 50 nationalities represented, we’re proud to welcome people of all backgrounds to our growing community, and we’re always finding new ways to help people feel welcomed and included. Here, you’ll have the tools, training and support you need to work in a way that suits you, learn new skills and reach your potential.  

For a career where you can drive our business and shape your future, apply now. 

About the role

As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping large enterprises understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability.

Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems.

Responsibilities:

• Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation

• Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success

• Support customers building with both the Claude API and Claude for Work

• Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives

• Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack

• Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases

• Identify common integration patterns and contribute insights back to our Product and Engineering teams

• Travel occasionally to customer sites for workshops, technical deep dives, and relationship building

• Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns

You may be a good fit if you have:

• 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager

• Native German speaker with fluent English proficiency

• Experience working with enterprise customers, navigating complex buying cycles involving multiple stakeholders

• Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more

• Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders

• Experience designing scalable cloud architectures and integrating with enterprise systems

• Comfortable with python

• Familiarity with common LLM frameworks and tools or a background in machine learning or data science

• Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities

• A love of teaching, mentoring, and helping others succeed

• Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities

• Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

About the role

As a Partners Solutions Architect on the Applied AI team at Anthropic, you will be a Pre-Sales architect focused on cultivating technical relationships with our Global and Regional System Integrators (GSIs/RSIs), and our cloud partners (AWS and GCP). You will strengthen our relationships with key partners to accelerate indirect revenue, enable their AI practices, and execute on long-term GTM strategy.

Responsibilities:

• Strategic Technical Partnership: Be a technical thought partner to the Anthropic GTM partnerships team, providing technical expertise to better understand the partner landscape, driving key strategic programs, and identifying opportunities to deepen partner technical capabilities. Embed with GSI and cloud partner technical teams to enable their AI practices, support troubleshooting, evangelize Anthropic in their developer communities, and serve as an escalation point for complex technical issues.

• Joint Solution Development: Collaborate with partners to identify high value industry-specific GenAI applications, develop joint solutions and codify reference architectures / best practices to accelerate time to deployment

• Customer Deal Support:  Intervene directly to unblock strategic customer deals where partners are the primary delivery vehicle, providing deep technical expertise and solution architecture guidance.

• Partner Ecosystem & Events: Represent Anthropic at partner events such as GSI customer workshops, AWS summits, and industry conferences. Lead or support partner-specific developer events, hackathons, and technical enablement sessions, especially for technically native communities.Product Feedback: Validate and gather feedback on Anthropic's products and offerings, especially as they relate to partner use cases and deployment patterns, and deliver this feedback to relevant Anthropic teams to inform product roadmap and partner strategy.

You may be a good fit if you have:

• 5+ years of experience in technical customer-facing/partner-facing roles such as Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager

• Track record of successfully partnering with GSIs and/or cloud providers to solve complex technical challenges, from initial solution design through customer delivery

• Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more

• Strong presentation & technical communication skills with the ability to translate requirements between technical and business stakeholders

• Experience designing scalable cloud architectures and integrating with enterprise systems

• Familiarity with common LLM frameworks and tools or a background in machine learning or data science

• Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities

• A love of teaching, mentoring, and helping others succeed

• Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems

At JetBrains, code is our passion. Ever since we started back in 2000, we have strived to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production and free developers to focus on creativity and problem-solving.

The IntelliJ AI team develops the AI-specific core of JetBrains IDEs. We work on agentic workflows, intelligent editing assistance, and new AI-powered capabilities that redefine how developers interact with the IDEs.

We are looking for a Senior Software Developer to help us build the next generation of AI-powered features in JetBrains IDEs.

In this role, you will:

• Integrate state-of-the-art AI agents into our IDEs, continuously improving the developer experience of working with them.
• Enhance agent capabilities by equipping them with the most intelligent tools available in our IDEs.
• Create novel AI features with no direct market analogues, experimenting with and exploring the new possibilities brought by modern AI technologies.
• Measure and evaluate the performance of agents and other AI features to achieve reliability and reproducibility.

We are looking for engineers who:

• Want to help build the best IDEs in the world and push the boundaries of developer tools.
• Have strong knowledge of Java, Kotlin, or similar languages.
• Are comfortable designing and developing complex software systems.
• Are self-driven and able to take end-to-end ownership of challenging features.
• Possess strong communication skills in English, both written and verbal.

Experience that would be especially valuable:

• Building AI-powered features, especially with LLM-based systems.
• Developing IDEs, code editors, or complex desktop applications.
• Working on performance-sensitive or correctness-critical systems.
• Concurrent programming and performance optimization.

Why join JetBrains?

• Strong base salary. We offer competitive pay that reflects your skills and experience.
• Flexible work location. Enjoy the freedom to work from home or from the office.
• Remote work. Spend up to 30 days per year working remotely from abroad.
• Extra time off. More days to relax, recharge, and do the things you love.
• Medical insurance allowance. Enjoy peace of mind for you and your family.
• Learning and development opportunities. Access to conferences, courses, and language classes.
• Relocation support. We help make your move as smooth and stress-free as possible.
• Language classes. Pick up the local language or sharpen your English skills.
• Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays.
• Mental health support. To help you feel your best, we provide easy access to professional mental health services.
• Sports benefit. Enjoy an on-site gym or sports club stipend.
• Internal events. Join company-wide celebrations and team gatherings.
  *Some benefits may vary depending on location.

#LI-IM1

Why this role exists

You will be the bridge between our employees and the tools that will change how they work. Not heavyweight enterprise software. Practical, immediate, high-impact AI adoption across every team and every function.

Your responsibilities

• Roll out a company-wide AI adoption program, starting with LLM chats and practical automation tools
• Work directly with leadership to prioritize and scale what works
• Run regular sessions, workshops and 1:1s to build AI literacy and confidence across the company
• Track and report adoption metrics so impact is visible and provable
• Identify how every team currently works and ideate/implement where AI can remove friction, save time and increase output

What you bring

• Currently enrolled in a Master's program at a top university
• Background in economics, software engineering or a business-facing technical discipline
• Proven hands-on experience bringing AI applications into a company or organization, not just building demos
• You have used LLM´s, built automations and know what actually works in practice
• Hardcore AI user yourself, you do not talk about AI, you use it daily
• Do or build mentality, you move fast and get things done
• Business savvy enough to understand priorities and translate them into action
• C1 Level of English

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Role Description

• As a Senior Applied Value Engineering Consultant - Public Sector you are pushing the envelope in solving business-critical problems. You will be working with our most strategic customers understanding their objectives and key challenges, and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers. This position will focus on our customers across the Public Sector, you’ll spearhead our mission to make processes work for citizens, government agencies and the planet, creating efficient, resilient processes which will shape a modern, citizen-oriented state. 

Key Responsibilities:

• AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude and don’t shy away from complex problems. Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
• Proof projects: End-to-end execution of business-critical Proof-of-Value projects, incl. architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks.
• Ensure Successful Project Outcome: Value Engineers stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Value Engineers specialize in domains (e.g. supply chain) and industries

Requirements:

• 5+ years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions.
• Understanding of generative AI techniques like RAG, few shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
• Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
• Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.
• Excellent communication and presentation skills in English and German. The role requires a high level of fluency in German.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.
• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex)
• Security Certification (SIcherheitsüberprüfung) up to SÜ2

Kineto is a next-generation platform that enables creators, educators, and small businesses to generate, deploy, and operate fully functional AI-powered web applications – instantly and at scale. It combines LLM-driven code generation, multi-tenant Postgres (Neon), dynamic hosting (GKE and Knative), automated deployments (Flux), analytics, billing, and a seamless chat-based UX to make software creation accessible to everyone. Our team is growing rapidly, and we’re now seeking an experienced Infrastructure Engineer who can design, build, and maintain our cloud-native platform, with a focus on scalability, reliability, and automated operations.

What you’ll do:

Cloud and platform engineering (DevOps):

• Design, implement, and manage the core infrastructure powering Kineto's platform on Google Cloud Platform (GCP), including networking, security, and identity management.
• Build and operate resilient, highly available distributed systems using Kubernetes (GKE), Knative, Istio, and related cloud-native technologies.
• Automate the entire infrastructure life cycle (IaC) using Terraform and Terragrunt, ensuring secure, reproducible, and auditable environments.
• Implement and maintain CI/CD pipelines (e.g. GitHub Actions and TeamCity) and deployment tools like Flux and Helm for GitOps-driven application delivery.
• Optimize and manage the multi-tenant data layer on Postgres and Neon, focusing on robust tenant isolation, performance, backups, and safe schema management.

Operational excellence and reliability:

• Drive site reliability engineering (SRE) practices, including monitoring, alerting (Prometheus, Grafana), logging (Loki), and incident response.
• Solve complex operational challenges, such as optimizing scale to zero for cost efficiency, minimizing cold starts, enhancing autoscaling behavior, and managing queue backpressure.
• Implement platform-wide performance tuning (e.g. container resource limits, distributed locks, caching strategies, and GC configurations).
• Ensure platform security and compliance by implementing best practices for secrets management, network segmentation, and vulnerability scanning.

Technical leadership:

• Own major infrastructure roadmap items, including multi-region deployments, disaster recovery planning, advanced tenancy separation, and ephemeral preview environments.
• Champion DevOps and SRE principles across the engineering team, mentoring engineers on cloud-native best practices, operational readiness, and debugging complex distributed systems.
• Collaborate with product and engineering teams to define the long-term vision for the platform's architecture and operational model.

We’d be glad to have you on our team if you:

• Have five or more years of experience building and operating large-scale, commercial cloud-native infrastructure, with a strong focus on DevOps/SRE practices.
• Possess deep, hands-on expertise with GCP (or AWS/Azure) and Kubernetes administration and operations (GKE experience is a strong plus).
• Are proficient with infrastructure-as-code (IaC) tools, particularly Terraform, for managing complex environments.
• Have a solid understanding of Linux internals, networking (CNI and service mesh), security, and distributed system design.
• Are familiar with CI/CD tools, GitOps (e.g. Flux), monitoring stacks (Prometheus/Grafana), and logging systems.
• Thrive in cross-functional teams and excel at communicating complex infrastructure ideas clearly.

#LI-YY1

At JetBrains, code is our passion. Ever since we started, back in 2000, we’ve been striving to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

Today, AI-powered assistance and agents are becoming a core part of how developers work in our IDEs. The ML Workflows Engineering team is dedicated to removing infrastructure challenges, streamlining machine learning operations (MLOps), and enabling teams to focus on the innovative work that matters most – building impactful ML models and intelligent agents. As part of the team, you'll play a key role in designing tools, automation, and pipelines that make machine learning development seamless and intuitive.

By integrating cutting-edge MLOps practices and engineering excellence, we aim to maximize productivity and remove the complexity of ML infrastructure so that our teams can push the boundaries of what’s possible in AI.

As part of our team, you will:

• Build tools, automation, and workflows to simplify infrastructure-heavy tasks, empowering AI teams to focus on experimentation and solving core challenges.
• Develop robust monitoring, logging, and tracing systems to ensure the performance and reproducibility of ML workflows in production.
• Design, implement, and maintain end-to-end machine learning pipelines to enable the seamless development, training, and deployment of ML models and intelligent agents.
• Work with large-scale distributed systems, including GPU clusters, to support training, fine-tuning, and evaluation of ML models.
• Collaborate with product and development teams to transform high-level goals into concrete, scalable, and maintainable systems.
• Optimize workflows for reproducibility, scalability, and cost-efficiency while keeping ML teams productive and focused on innovation.

We’ll be happy to have you on our team if you have:

• Hands-on experience with modern MLOps tooling, including Kubernetes, Cloud providers (GCP and AWS), and ML orchestration frameworks.
• A solid understanding of the ML lifecycle from idea to the customer-facing application.
• The ability to own projects end to end, starting from a high-level problem or product pain point and overseeing it through the design, experimentation, implementation, and iteration phases.
• A customer-centric mindset – you care about how ML engineers are actually working and can translate their needs into actionable, scalable, and maintainable architectural decisions.
• Experience with modern CI/CD systems, like GitHub Actions or JetBrains TeamCity.
• At least three years of Python experience writing clean, maintainable code in modern ML codebases.

Our ideal candidate would have experience with:

• ML orchestrators and workflow tools such as ZenML, Dagster, and Airflow.
• Developing infrastructure components and services using cluster solutions like Kubernetes.
• The development of Python-based backend services.
• Creating and maintaining ML pipelines, including legacy ones.
• Experiment tracking and observability using tools like Weights & Biases, MLflow, Langfuse, or similar.

We’d be especially thrilled if you have experience with: 

• LLM inference frameworks such as vLLM, DeepSpeed, and TensorRT.
• Writing and maintaining Python libraries used by internal (or external) ML engineers.
• A strong theoretical background in NLP and transformer-based approaches.
• Writing code in Java and/or Kotlin.

#LI-HYBRID
#LI-MR1

At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the world’s most robust and effective developer tools. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

We are working on an ambitious new platform that provides AI capabilities to all JetBrains products. Our platform is based on models developed in-house for writing and coding assistance, as well as integration with our strategic partners.

We are looking for a Research Engineer who can contribute to training foundation models for coding tasks. You’ll be working on developing Large Language Models from scratch and deploying them into production environments where they will be accessible by end users across the globe.

We value engineers who: 

• Can plan projects and make decisions independently, consulting with others if needed.
• Identify customer needs and prioritize their tasks accordingly.
• Start with the simplest solutions and gradually add complexity as needed.
• Take sole responsibility for an entire subsystem.
• Have a passion for learning and a desire to stay up to date with the latest developments in the LLM field.

In this role, you will: 

• Work with stakeholders to convert business requirements into technical specifications.
• Train LLMs from scratch on a large GPU cluster.
• Collect and process pre-training and fine-tuning datasets.
• Support and improve existing subsystems.

We’ll be happy to have you on our team if you have: 

• Experience in design, deployment, and support of production ML systems.
• A strong theoretical background in NLP and transformer-based approaches.
• Proficiency with modern deep learning frameworks such as PyTorch and common libraries for NLP.
• Experience in distributed training of multi-billion parameter models.
• Attention to detail in everything you do and great communication skills.

We’d be especially thrilled if you have experience with: 

• LLM inference frameworks such as vLLM, DeepSpeed, TensorRT.
• LLM alignment techniques such as RLHF/RLAIF.
• MLOps tools and practices, including CI/CD for ML.
• K8s and Kubeflow.
• Scientific publications in the NLP field.

How we develop JetBrains AI: 

• A cluster of hundreds of NVIDIA GPUs as training infrastructure.
• Git for source control management.
• Python, PyTorch, and HuggingFace as an ML stack.
• Kubeflow and Weights & Biases for experiment tracking.
• TeamCity as a CI Automation system.

#LI-KP1

At JetBrains, code is our passion. Ever since we started, back in 2000, we’ve been striving to make the strongest, most effective developer tools on earth. Today, AI-powered assistance and agents are becoming a core part of how developers work in our IDEs.

We’re building multi-step coding agents that can understand large codebases, plan changes, call tools, and iterate with the user. As a Research Engineer in the Agentic Models team, you’ll be responsible for the models, training loops, and evaluation pipelines that power these agents.

You’ll work at the intersection of SFT and RL-style post-training, and product-driven evaluation, using our distributed GPU and MapReduce clusters to ship models into JetBrains products.

As part of our team, you will:

• Design, implement, and maintain SFT and RL post-training pipelines for multi-step coding agents.
• Train and adapt LLMs for agent workflows, including planning, tool use, and multi-step interactions inside JetBrains IDEs.
• Build and develop evaluation and simulation environments where coding agents can act, be measured, and compared on realistic developer tasks.
• Design evaluation frameworks and metrics for agent behavior, analyze traces and logs, and close the loop from evaluation back into training, data, and reward design.
• Analyze training and evaluation results to propose and implement improvements to model architectures, training recipes, and datasets.
• Work with large-scale infrastructure, including distributed training on GPU clusters and large MapReduce-style data processing for pre-training and fine-tuning datasets.
• Collaborate closely with research, product, and infrastructure teams to turn high-level product visions into concrete models, experiments, and shipped features. 

We’ll be happy to bring you on board if you have:

• Extensive hands-on experience training LLMs (pre-training, fine-tuning, or post-training) in a research or production setting.
• Deep expertise in modern deep learning frameworks such as PyTorch, and specialized LLM training stacks (e.g. Megatron, NeMo, verl, or similar).
• Strong theoretical and practical understanding of LLM fundamentals: architectures, tokenization, data pipelines, batching, mixed precision, distributed training, and debugging unstable runs.
• The ability to own projects end to end, starting from a high-level problem or product pain point and overseeing it through the design, experimentation, implementation, and iteration phases.
• A product-aware mindset – you care about how developers actually use agents and can translate product needs and failure modes into modeling and evaluation work.
• At least 3 years of Python experience writing clean, maintainable code in modern ML codebases.

Our ideal candidate would have experience with:

• ML orchestrators and workflow tools such as Kubeflow, Dagster, Airflow, ZenML, and/or job schedulers like Kubernetes or SLURM.
• Large-scale data and training pipelines, e.g. MapReduce-style clusters, multi-node GPU training, or workloads on the order of 1M+ CPU/GPU hours.
• Designing and maintaining evaluation pipelines for LLMs or agents, including metrics, dashboards, experiment tracking, and automated regression checks.
• AI agent development, such as tool-using agents, planners, or multi-step coding workflows, and familiarity with agentic frameworks or patterns.
• Experiment tracking and observability using tools like Weights & Biases, MLflow, Langfuse, or similar.
• Inference optimization and serving optimized models in production.

#LI-KP1

At JetBrains, code is our passion. Ever since we started, back in 2000, we have strived to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

We just unveiled JetBrains Central,  a platform for agent-driven software development that connects tools, agents, and infrastructure. It enables automated AI workflows to run, be monitored, and be managed across teams – with clear visibility into results, costs, and performance.

JetBrains Central provides three core capabilities:
Governance and control: Policy enforcement, identity and access management, observability, auditability, and cost attribution for agent-driven work. Some of these functionalities are already available via the JetBrains Central Console.
Agent execution infrastructure: Cloud agent runtimes and computation provisioning that allow agents to run reliably across development environments.
Agent optimization and context: Shared semantic context across repositories and projects, enabling agents to access relevant knowledge, and task routing to the most appropriate models or tools.

Inside the Professional Services department, we are building a team of Forward Deployed Engineers to help our customers adopt AI-native development with JetBrains Central and enable JetBrains consulting partners to transform their customers’ AI-native software development lifecycle.

About the role

As a Principal Forward Deployed Engineer, you will work directly with early adopter customers to deploy JetBrains Central platform into complex enterprise environments and help them move from experimental AI usage to governed, scalable AI-native development.

You will act as a trusted advisor to customer engineering teams and consulting partners, while also mentoring other Forward Deployed Engineers and helping with complex deployments. In this role, you will help establish best practices for enterprise AI adoption and influence how organizations implement AI-driven software development.

This role is often a strong fit for engineers who have previously served as Principal or Staff Engineers, Heads of Engineering, CTOs, or Solutions Architects and who enjoy working directly with customers while staying deeply involved with complex technical systems.

This role combines consulting, architecture, and hands-on engineering. Your work in the field will directly influence how our platform evolves and how enterprises adopt AI-driven development.

You will work directly with the world’s most innovative companies — our client base includes 420 of the Fortune 500 — ensuring they maximize the value of their JetBrains investments.

What you’ll do

• Deploy JetBrains Central platform into enterprise development environments, CI/CD systems, and internal developer platforms.
• Help organizations transition from ad-hoc AI experimentation to governed AI-native development workflows.
• Implement enterprise AI governance, including security policies, access management, and data privacy controls.
• Enable observability for AI-driven development to help organizations understand their AI usage and its impact on productivity, as well as their code-generation patterns.
• Design sustainable AI adoption strategies, including usage controls and cost visibility across multiple model providers.
• Integrate our cloud-based agent execution layer, allowing AI agents to run securely and at scale.
• Collaborate closely with JetBrains product teams to shape the platform based on real-world deployments and customer feedback.
• Create delivery frameworks and train JetBrains partners to deliver the desired scope of service.
• Mentor and support other Forward Deployed Engineers, sharing architectural expertise and helping to scale the team’s deployment practices.

You will thrive in this role if you are

• A consultant at heart who can communicate effectively with both engineers and technical leadership.
• Able to see the whole picture of the software development lifecycle across developer tools, infrastructure, APIs, and cloud systems.
• Experienced at integrating complex software systems into enterprise environments.
• Curious about the future of AI agents and AI-native software development.
• Comfortable working with early adopters and overcoming ambiguous technical challenges.
• Motivated to mentor other engineers and contribute to building a new technical discipline.

What you will bring

• Experience in software-related projects, ideally in a customer-facing or consulting environment.
• Familiarity with Java or Python.
• Experience building or integrating developer platforms, infrastructure systems, or software solutions.
• Familiarity with modern development workflows (CI/CD, developer environments, internal developer platforms, etc.).
• Experience working directly with customers or technical stakeholders.
• Strong problem-solving skills and the ability to operate in fast-evolving technical environments.
• Ability and desire to travel to meet customers.

These would be a plus, but are not blockers

• Experience with industry-specific solutions (fintech, telco, retail, etc.)
• Experience with AI/LLM platforms, agent frameworks, or AI-assisted development tools.
  Experience in solutions engineering, consulting, or forward-deployed engineering roles.
• Familiarity with the JetBrains ecosystem or developer productivity tooling.

#LI-KP1

At JetBrains, code is our passion. Ever since we started, back in 2000, we have strived to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

AI features in JetBrains IDEs, developed by the IntelliJ AI team, have quickly become a core part of how developers work inside our IDEs. The IntelliJ AI team partners with product groups across JetBrains to embed advanced AI features that accelerate developer workflows and deliver real value to software engineers.

We are currently looking to hire a Senior Machine Learning Engineer to help us realize our ambitious vision of creating AI assistance that supports the entire development lifecycle across JetBrains IDEs. If selected, you will join the ML subteam within IntelliJ AI, driving the development of our ML system from end to end by defining evaluation and metrics, shaping context orchestration, and helping product teams tailor AI capabilities to their needs.

In this role, you will:

• Design and drive evaluation frameworks for AI features, including metrics, experiments, and agent trace analysis.
• Diagnose model performance issues (e.g. prompt drift, context mismatches, and latency/quality trade-offs) and translate findings into actionable improvements.
• Experiment with contexts and lightweight models to continuously develop our ML system.
• Act as the ML liaison for product teams across JetBrains, adapting and scaling AI capabilities in JetBrains IDEs to their needs.
• Build and maintain small helper models (e.g. re-rankers, classifiers, embedding models) to support domain-specific tasks.
• Collaborate with colleagues in ML, product, engineering, and analytic teams to deliver improvements and monitor their impact in production.
• Stay up to date with research in the fields of LLMs, agents, and evaluation, bringing best practices into our workflows.
• Mentor junior engineers and help shape team culture, processes, and tooling around experimentation and evaluation.

We’d be happy to have you on our team if you: 

• Have 5+ years of experience as an ML Engineer, with a solid background in production-grade ML systems (especially LLMs and agent architectures).
• Have experience with LLM evaluation methods and frameworks.
• Can design and run end-to-end experiments – hypotheses, metrics, data collection (including traces/logs), analysis, and decision-making.
• Are skilled in context-aware pipelines or conversational/agent systems.
• Have strong Python programming skills.
• Bring hands-on experience in fine-tuning or training smaller models (e.g. domain-specific fine-tuning and lightweight customizations).
• Communicate clearly and effectively across teams, translating ML/AI insights into product features.
• Have prior mentorship experience with ML/evaluation engineers.
• Thrive in a cross-functional, fast-moving environment, taking ownership, iterating quickly, and delivering results.

We’d be especially thrilled if you have: 

• Familiarity with agent-based systems and orchestrating multi-step reasoning agents.
• Experience with the Kotlin programming language.

#LI-MR1

At JetBrains, code is our passion. Ever since we started, back in 2000, we've been striving to make the strongest, most effective developer tools on earth. Today, AI-powered coding agents are becoming a core part of how developers write Kotlin – and we want to make sure they write it well.

The Kotlin AI Value Stream team is responsible for how AI agents understand, generate, and improve Kotlin code across all platforms: Android, Kotlin Multiplatform, server-side, web, desktop, and others. We build the evaluation infrastructure, error analysis tools, and post-training pipelines that measure and improve agent behavior on real Kotlin developer tasks.

As a Research Engineer on this team, you'll own the end-to-end loop: Analyze how agents fail on Kotlin → build evals that capture those failures → research and implement methods to fix them → measure the improvement. Your work will directly shape how millions of developers experience Kotlin through AI coding agents.

As part of our team, you will:

Build tools for agentic error analysis

• Design and implement tooling to systematically capture, classify, and analyse errors that AI coding agents make when generating Kotlin code.
• Build observability pipelines over agentic traces – mining patterns from agent sessions in JetBrains IDEs, Junie, Claude Code, Cursor, and other coding agents.

Build evaluation pipelines

• Design, implement, and maintain evaluation pipelines that measure Kotlin code generation quality across dimensions, including correctness, idiomaticity, build success, framework usage, and test coverage.
• Build simulation environments where coding agents can be measured on realistic Kotlin developer tasks – from greenfield KMP projects and Gradle dependency management to migrating Spring applications from Java to Kotlin.
• Own evaluation infrastructure: metrics, experiment tracking, automated regression checks, and reproducible benchmarking.

Research methods for improving agent and model behavior on Kotlin

• Experiment with post-training techniques (SFT, DPO, GRPO) to improve how models handle Kotlin-specific patterns, idioms, and frameworks.
• Investigate context engineering approaches: CLAUDE.md/AGENTS.md files, compiler-as-verifier feedback loops, Kotlin LSP integration, and MCP-based tooling.
• Run experiments to measure impact: A/B comparisons, benchmark suites, and before/after analyses on real codebases.
• Collaborate with model providers (Anthropic, OpenAI, and Google) to translate Kotlin-specific findings into model improvements.

Build public Kotlin benchmarks

• Design and build open-source benchmarks that measure AI coding agent performance on Kotlin tasks and eventually become the standard reference for the ecosystem.
• Create task datasets covering the breadth of Kotlin usage: the server side (Spring, Ktor), multiplatform projects (KMP), build systems (Gradle), Android, library development, and others.
• Include both mined real-world tasks and carefully designed synthetic tasks that test specific Kotlin capabilities.
• Maintain and evolve benchmarks as models improve, ensuring they remain challenging, relevant, and contamination-resistant.

We'll be happy to have you on board if you have:

• Hands-on experience building evaluation or analysis pipelines for LLMs or AI coding agents in a research or production setting.
• Strong Python engineering skills (at least three years), with the ability to write clean, maintainable code in data-heavy and ML-adjacent codebases.
• Experience with data analysis at scale: querying large datasets (SQL/Athena), building data pipelines, and performing statistical analysis of experimental results.
• The ability to own projects end to end – from identifying a problem in agent traces to designing an eval, running experiments, and shipping a fix.
• A product-aware mindset: You care about how agents are actually used by developers and can translate real failure modes into evaluation and training work.
• Familiarity with Kotlin or a strong willingness to develop deep Kotlin expertise (you'll be living in Kotlin codebases daily).

Our ideal candidate would also have experience with:

• Post-training LLMs: SFT, RLHF, DPO, GRPO – either hands-on training or designing the data and reward pipelines that feed into training.
• Modern deep learning frameworks (PyTorch) and LLM training stacks (TRL, verl, Megatron, or similar).
• AI agent development: tool-using agents, multi-step coding workflows, agentic frameworks.
• Evaluation frameworks and tools: Inspect AI, Promptfoo, LM-evaluation-harness, or custom eval pipelines.
• Experiment tracking and observability: Weights & Biases, MLflow, Langfuse, or similar.
• The Kotlin ecosystem: Android, Gradle, KMP, Spring, Ktor – with an understanding of the developer workflows that agents need to support.
• Contributing to or maintaining open-source projects, especially benchmarks or evaluation tools.

Don't check every box? That's okay – if you're excited about this work and bring strong fundamentals, we'd love to hear from you. We're happy to talk and provide the training you need to grow into the role.

Why join JetBrains? 

• Strong base salary. We offer competitive pay that reflects your skills and experience.
• Flexible work location. Enjoy the freedom to work from home or from the office.
• Remote work. Spend up to 30 days per year working remotely from abroad.
• Extra time off. More days to relax, recharge, and do the things you love.
• Medical insurance allowance. Enjoy peace of mind for you and your family
• Learning and development opportunities. Access to conferences, courses, and language classes.
• Relocation support. We help make your move as smooth and stress-free as possible. 
• Language classes. Pick up the local language or sharpen your English skills.
• Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays.
• Mental health support. To help you feel your best, we provide easy access to professional mental health services.
• Sports benefit. Enjoy an on-site gym or sports club stipend.
• Internal events. Join company-wide celebrations and team gatherings.

*Some benefits may vary depending on location.

#LI-DNI