We are looking for passionate technologists to join our Pre-Sales organization to ensure that our growth is grounded and guided by strong technical alignment with our platform and the needs of our customers.

MongoDB Pre-Sales Solution Architects are responsible for guiding our customers and users to design and build reliable, scalable systems using our data platform. Our team is made up of seasoned technical sales professionals, software architects, entrepreneurs, and developers who take direct responsibility for customer success, including the design of their software, deployment, and operations. You'll work closely with our sales executives, helping customers solve business problems by leveraging our solutions, playing a key role in winning deals and driving the business forward. You'll be a trusted advisor to a wide range of users from startups to the world's largest enterprise IT organizations. 

We are looking to speak to candidates who are based in Munich for our hybrid working model.

As an ideal candidate, you will have:

• 5 to 8  years of related industry experience, ideally 2 years of experience in a customer facing role
• Minimum of 2 years experience with modern scripting languages (e.g. Python, Node.js, SQL) and/or popular programming languages (e.g. C/C++, Java, C#) in a professional capacity
• Experience implementing scalable and highly available distributed systems in the cloud and on-prem
• Demonstrated ability to work with customers to review complex architecture of existing applications, providing guidance on how to improve by leveraging technology
• Excellent presentation, communication, and interpersonal skills, with the ability to convey complex technical and business concepts in a clear and compelling manner to technology and business leadership
• Ability to work with a cross functional sales team to formulate and execute an end to end deal cycle
• The ability to travel up to 25%
• A Bachelor’s degree or equivalent work experience

You may also have:

• Experience developing, deploying, or supporting applications with any of the major cloud providers 
• Experience working in a technical pre-sales capacity 
• Experience with database programming and data models 
• Experience in data engineering or AI/ML projects
• Understanding of popular sales methodologies/ frameworks such as MEDDPICC/ Command of the Message
• A MongoDB Certification
• A Cloud Provider Certification

What you do at MongoDB:

In this role, you will work on complex opportunities where analysis of situations or data requires an in-depth evaluation of various factors. You will:

• Design and Architect: Design scalable and performant applications, systems and infrastructure for large software projects leveraging MongoDB
• Customer Advising and Value Articulation: Guide customers on architecture patterns and optimisation strategies for MongoDB, while clearly communicating its business value to the relevant stakeholders
• Sales Partnership: Collaborate with the sales team to drive account success through account planning, opportunity prioritization/qualification and pipeline generation strategy, while taking ownership of the technical aspects (including but not limited to technical discovery, demos, proof of value, presentations, sizing and documentation)
• Demand Generation: Proactively generate demand within the sales territory through self-driven technical initiatives, participation in events such as industry trade shows and account-based marketing events
• Customer Success: Foster strong customer relationships, build champions and ensure customer success and satisfaction
• Innovation and Improvement: Continuously seek opportunities to innovate and improve MongoDB solutions and processes (e.g. by relaying field feedback to the product team), as well as proactively mentor other Solutions Consulting team members 
• Personal Training and Development: Engage in ongoing training and professional development to stay abreast of MongoDB product suite as well as industry trends

What you will learn:

MongoDB Product Suite Mastery:

• Core Database Server: Master the fundamentals and advanced features of MongoDB's core database
• Atlas and Advanced Services: Gain expertise in Atlas (fully managed cloud database service), Atlas Stream Processing, Atlas Data Lake, Atlas Full-Text Search, Atlas Vector Search, and Charts
• Relational Migrator: Learn to migrate from relational databases seamlessly

Market-Relevant Technologies:

• Hyperscaler Ecosystem: Gain expertise in designing complex systems utilizing cloud services on hyperscaler platforms
• Complementary Technologies: Enhance your skills with partner and complementary technologies such as Apache Kafka and Kubernetes

Modern Architecture Design:

• Design Patterns and Methodologies: Embrace best practices in microservices, DevOps, cloud, and security
• Cutting Edge RAG and AI Architectures: Help customers on their generative AI journey and working with industry leading partners in the space

Sales Techniques and Soft Skills:

• Effective Communication: Master presentations, demonstrations, and whiteboarding
• Client Interaction: Develop strategies for discovery and objection handling

Industry Insights:

• Diverse Market Verticals: Gain exposure to a broad spectrum of interesting use cases across various industries

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 60,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

Req ID: 1273390805

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.

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