The AI Retrieval team powers the intelligence behind Asana's AI features by finding relevant work graph content and delivering it to LLM context windows. Our work enables AI features that truly understand your work—both within and outside of Asana—and use that understanding to take action. We also own Asana's traditional search experience.

As a Senior Software Engineer on the AI Retrieval team, you'll build the systems that make Asana's AI smart and responsive. You'll tackle challenging problems in search and retrieval, working to improve the speed, cost-efficiency, and quality of our systems while expanding their capabilities to new data sources.

This role is based in our Warsaw office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements.

We offer a Contract of Employment (UoP) for our employees in Poland.

What you'll achieve

• Reduce the latency and cost of our retrieval system, making Asana's AI features faster and more efficient
• Improve the quality and relevance of search results to help users find exactly what they need
• Expand the retrieval system's capabilities to query new Asana objects and third-party data sources
• Build and optimize search infrastructure using OpenSearch/ElasticSearch
• Contribute to ML-powered features like embeddings-based retrieval and semantic search
• Collaborate with cross-functional partners in New York City while building strong relationships with your Warsaw-based peers

About you

• 6+ years of experience writing code in a production environment 
• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making
• Hands-on experience in search engineering, including with OpenSearch or ElasticSearch
• Experience with embeddings and machine learning approaches to search and retrieval
• Experience in an Applied AI role is a plus

We know that the best ideas and solutions come from multi-dimensional teams. That's because these teams reflect a variety of backgrounds and professional experiences. If you are excited about this role and feel your experience can make an impact, please don't be shy - apply today.

At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply.

What we’ll offer

• Generous, transparent and fair compensation system (base salary and RSUs)
• Contract of Employment (and the option of 50% tax deductible costs for author’s rights usage in respect of applicable roles ) 
• Health insurance with dental and travel coverage (Lux Med) 
• Breakfast and lunch catering on the days that you work from the office
• Vacation allowance
• Career growth budget 
• Home office setup budget 
• Gym/Fitness card
• Fertility healthcare and family-forming support with Carrot
• Mental Health Support in Modern Health
• Group life insurance
• MacBooks with all necessary accessories

For this role, the estimated base salary range is between 31,917 - 40,583 PLN gross per month (subject to all taxes and necessary deductions). The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.

In addition to base salary, your compensation package may include additional components such as equity and sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role.

#LI-Hybrid

We're looking for a AI Engineer. The Enterprise AI team is a new, agile group of builders dedicated to empowering Asana’s internal functions through the design and implementation of scalable AI workflows. We partner cross-functionally with business and engineering teams, maintaining tight feedback loops with our users to ensure our solutions directly enhance critical GTM processes. By automating high-value business logic, we serve as a critical pillar in driving Asana’s broader goal of building the Agentic Enterprise Foundations.

This role is based in our Warsaw office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements.

We offer a Contract of Employment (UoP) for our employees in Poland.

What you’ll achieve

• Own the AI integration layer, architecting the connective tissue between foundational LLMs and our core GTM stack (e.g., Salesforce, Databricks) to automate high-value business logic.
• Design prompting strategies, orchestration logic, and tool integrations that enable AI systems to retrieve data, reason over context, and take action across internal systems.
• Build AI data infrastructure, including retrieval pipelines and RAG systems, to ensure AI outputs are grounded in accurate product documentation and customer insights.
• Design and deploy intuitive AI interfaces - ranging from Slack apps to Chrome extensions - to bring AI directly into existing user workflows.
• Lead the transition from POC to production, rapidly prototyping AI pilots while ensuring underlying architectures are optimized for performance, security, and scale.
• Partner with GTM and RevOps stakeholders to identify process friction and translate business requirements into technical AI solutions that drive revenue.
  
  

About you

• 5+ years of experience designing, building, and deploying AI-driven or intelligent systems in enterprise environments.
• At least 1+ year of hands-on experience working with Generative AI technologies such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and prompt engineering. 
• Strong proficiency in Python and SQL, with the ability to confidently process data, build integrations, and extend automation platforms.
• Proven experience building AI-powered applications, agents, or LLM-powered automations that deliver measurable business value beyond basic chatbots.
• Hands-on expertise with agent frameworks (e.g., LangChain, LlamaIndex) and designing multi-step reasoning workflows.
• Experience building reliable, business-critical workflows using automation and iPaaS platforms like n8n, Workato, or Zapier.
• A business-first mindset with an understanding of GTM motions and the ability to identify where AI creates the most strategic leverage.
• Strong communicator capable of explaining complex automation logic and AI behavior to non-technical stakeholders across Sales and Marketing.
• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.
  
  

At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply.

What we’ll offer

• Generous, transparent and fair compensation system (base salary and RSUs)
• Contract of Employment (and the option of 50% tax deductible costs for author’s rights usage in respect of applicable roles ) 
• Health insurance with dental and travel coverage (Lux Med) 
• Breakfast and lunch catering on the days that you work from the office
• Vacation allowance
• Career growth budget 
• Home office setup budget 
• Gym/Fitness card
• Fertility healthcare and family-forming support with Carrot
• Mental Health Support in Modern Health
• Group life insurance
• MacBooks with all necessary accessories

For this role, the estimated base salary range is between 26,417 - 29,583 zł PLN gross per month (subject to all taxes and necessary deductions). The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.

In addition to base salary, your compensation package may include additional components such as equity and sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role.

#LI-Hybrid

The Asana Marketing team is responsible for fueling business growth and building a brand customers love. We create campaigns and content to attract new accounts and inspire current ones to grow with us. We’re looking for a Technical SEO Manager to own the technical foundation of Asana’s organic search performance. You’ll ensure asana.com is built for maximum crawlability, indexability, and performance—driving technical implementations that support visibility across traditional and AI-powered search surfaces, including LLM-driven discovery.

This role is based in our Warsaw office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

We offer a Contract of Employment (UoP) for our employees in Poland.

What you’ll achieve

• Develop and execute a technical SEO roadmap, prioritizing site architecture, crawlability, and indexation to drive global business impact.

• Build and maintain SEO monitoring dashboards to ensure continuous visibility into crawl health and site performance.

• Partner closely with web engineering to drive site speed and Core Web Vitals improvements across all marketing and product web surfaces.

• Own the technical requirements for site migrations and platform changes, ensuring long-term scalability and performance.

• Implement advanced structured data and schema markup to improve coverage across search features and LLM-driven discovery results.

• Leverage AI tools to scale technical audits and crawl analysis, creating more efficient workflows for issue detection and prioritization.

• Manage international technical SEO, including hreflang implementation and regional targeting strategy.

About you

• 5+ years of technical SEO experience managing complex enterprise-level websites.

• Deep understanding of crawl mechanics, indexation, and JavaScript rendering.

• Proven experience with structured data implementation and technical SEO tools like Screaming Frog, Botify, or Google Search Console.

• Strong proficiency in HTML, CSS, JavaScript, and HTTP fundamentals, with the ability to work effectively within engineering constraints.

• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.

• Analytical mindset with the ability to translate complex technical concepts into actionable insights for non-technical stakeholders.

• Experience managing international SEO requirements and large-scale site migrations.

What we’ll offer

Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.

For this role, the estimated base salary range is between 18,333 PLN - 20,333 PLN gross per month (subject to all taxes and necessary deductions).The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.

In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role.

We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:

• • Generous, transparent and fair compensation system
  • Contract of Employment (and the option of  50% tax deductible costs for author’s rights usage in respect of  applicable roles ) 
  • Health insurance with dental and travel coverage (Lux Med) 
  • Meals reimbursement on the days that you work from the office
  • Career growth budget 
  • Home office setup budget 
  • Gym/Fitness reimbursement
  • Fertility healthcare and family-forming support with Carrot
  • Mental health support in Modern Health
  • Group life insurance
  • MacBooks with all necessary accessories

These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role.

#LI-Hybrid

What You’ll Do:

The GPU Performance Team is responsible for the automated testing and verification of CoreWeave’s ever-expanding fleet of nodes and infrastructure.   The team plays a critical role in ensuring that the hardware we deliver to customers is stable and performant throughout its lifecycle.  

About the role:

We are seeking a Senior Software Engineer to join the GPU Performance team to help us build and refine our automation platforms and workflows for reliability, efficiency, scalability and observability. This individual will join a team of Golang and Python developers innovating kubernetes-based solutions to hardware performance testing. As a member of the GPU Performance  team, you would have the opportunity to:

• Design and Implement solutions for testing infrastructure at scale through automation.
• Develop platforms, workflows, data structures, API endpoints, and other testing management tools and capabilities.
• Create test plans, deployment automation, dashboards, alerts, and insights into our performance testing platform.
• Grow, change, invest in your teammates, be invested-in, share your ideas, listen to others, be curious, have fun, and, above all, be yourself.

Who You Are: 

You are a software engineer with a strong bias toward reliability, automation, and scale. You’re comfortable owning services end‑to‑end and working close to hardware, but your primary tools are Go or Python, Kubernetes, and well‑designed APIs.

• Have experience building and maintaining backend services and APIs (REST/gRPC) and are comfortable integrating with infrastructure systems (Kubernetes, CI/CD, telemetry, metrics backends).
• Are motivated by automation at scale: you’d rather design a controller, workflow, or platform than run one‑off tests by hand.
• Are familiar with system metrics, performance, and health (e.g., GPU/CPU, network, storage, or similar infra) and know how to turn raw metrics into dashboards, alerts, and actionable insights.
• Are comfortable designing and implementing performance tests and validation workflows that run across many nodes and clusters.
• Care about code quality, observability, and operational readiness: logs, metrics, tracing, alerting, and on‑call are part of how you think about building systems.
• Are willing to participate in an on‑call rotation and help own the stability of the platforms you build.
• Work well in a collaborative, curious, and feedback‑driven team: you invest in your teammates, share ideas openly, and are excited to help shape how CoreWeave validates hardware performance at fleet scale.

Preferred:

• Write and maintain Kubernetes custom controllers and operators to automate infrastructure testing.
• Contributions to OSS projects such as  llm-d, vLLM, or PyTorch
• Exposure to benchmarking large GPU fleets or multi-region clusters.
• Experience with CUDA kernels, NCCL/SHARP, RDMA/NUMA, or GPU interconnect topologies.

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! 

The base salary range for this role is zł321,000 to zł535,000. The starting salary will be determined by job-related knowledge, skills, experience, and the market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

The Role

At Cognism, the security of our data, our systems and our clients’ systems is a business priority. Information security is embedded in the way we work, and we are driving a culture where the fastest path is the securest path. As the function continues to mature, we are now hiring for a Director of Security Engineering & Operations to report directly to our CISO. In this role you will own and drive the technical security strategy for Cognism’s web and data products, as well as our corporate environment. You will be responsible for designing a security programme that protects our most sensitive assets: our data, our data fusion engine and the logic that powers it. As a trusted partner to our R&D leadership team you will help to define and drive the long-term security engineering maturity roadmap, driving alignment across engineering leaders, product leadership and IT. If you’re energised by the idea of shaping measurable security processes and controls, from the ground up, aligning engineering around secure-by-design principles, and elevating operational excellence, then this is the role for you. This is a rare opportunity to define the technical security vision for a dataintensive product at a moment where AI, scale, and engineering velocity are creating new and exciting challenges. You will shape how Cognism builds securely for the next decade.

What success looks like

Within 12 months, you will have:

• Delivered a unified security engineering roadmap aligned with engineering leadership.
• Matured secure SDLC adoption across Web and Data engineering.
• Improved MTTD/MTTR through stronger SOC operations.
• Invested in and mentored a team with clear ownership, KPIs, and engineering trust.
• Reduced engineering friction by creating pragmatic, developerfriendly guardrails

What You'll Own

Security Strategy & Engineering Integration

• Define and own Cognism's technical security strategy that seeks to embed security-by-design within our web and data products, our data fusion engine and pipelines, and our corporate landscape. You will drive a strategy that is pragmatic, risk-ranked, and aligned to engineering velocity.
• Work directly with product and technology leadership as a strategic partner. You will drive ownership and accountability, clearly agreeing ways of working between your team and product and technology teams.
• Set and direct a secure SDLC strategy that engineers engage with, coaching and mentoring our application security engineer with running our threat modelling program, embedding security in CI/CD, and iteratively improving our vulnerability management processes.
• Partner with engineering leadership to ensure risk-driven supply chain management across our product, ensuring what we bring in doesn't undermine what we protect.
• Work directly with our Director of IT operations to ensure our corporate security posture is mitigating risk and empowering our employees to be as secure as possible, through guardrails that protect unacceptable risk but don’t stifle innovation.

Data & AI Security

• Partner with our VP of Data Engineering to strengthen the security of our enrichment engine, data pipelines, and warehouse ecosystems.
• Direct a strategy that considers security across the full data stack - from ingestion through to the warehouse - with a focus on access governance, data classification, and secrets management as non-negotiables.
• Define how Cognism embeds AI securely as LLMs and agentic workflows move deeper into the product and our technology teams’ operations.
• Partner with our CISO to shape and implement an AI security posture that is embedded in strong security foundations, helping us stay ahead of the threat landscape rather than reacting to it.

Detection, Response & SOC Partnership

• Own the strategic relationship with our 24/7 outsourced SOC holding them to a high standard on threat hunting, threat intelligence utilisation, and automated response, not just SLA compliance.
• Ensure Cognism has a holistic, well-maintained SIEM that reflects how we operate and improves continuously as the threat landscape evolves.
• Build the internal team into a trusted escalation layer, with clear incident response playbooks, rehearsed escalation paths, and a feedback loop that sharpens detection over time.

Team & Culture

• Lead a team of application and infrastructure security engineers, setting the standard for technical excellence and deep partnership with their engineering counterparts.
• Build a security culture where developers raise security questions early, understand threat models, and own remediations, not because policy requires it, but because the culture makes it natural.
• Be the security leader Cognism's engineers want in the room: credible enough to be trusted, collaborative enough to be included, and strategic enough to make it count.

What We Need

Leadership & influence

• Demonstrated experience building security programmes from scratch or transforming them significantly in a product-led, engineering-first company.
• A track record of influencing engineering culture and earning trust, not enforcing it.
• Experience managing external security partners, (e.g 24/7 Security Operations Centre, penetration testing 3rd parties) and raising their performance through clear accountability, not just contract reviews.
• Able to communicate risk in business terms to exec and board audiences, and technical terms to engineers, without losing precision in either direction.

Technical foundation

• Strong AppSec expertise (OWASP, API security, SAST/DAST, SDLC) with practical threat modelling experience – enough to challenge and coach our most senior application security engineers.
• Handson understanding of data security, cloud data warehouses, and pipeline integrity – enough to ensure we are driving the right programme of work across our technology department.
• Cloud security fluency with working knowledge of container and Kubernetes security, IAM design, and cloud-native security tooling – enough to clearly identify, prioritise and challenge solutions for implementing security in our cloud environment.
• Working knowledge of AI/LLM security risks: enough depth to assess integrations, define guardrails, and evolve the programme as the technology does.

Mindset

• Risk-based by instinct: prioritises based on both technical and business impact
• Builder mentality: energised by creating structure where there isn't any, pragmatic about sequencing, and focused on outcomes over coverage.
• Genuinely curious about AI, not just its security risks, but its potential to improve how security is done.

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

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

We are looking for a Staff Machine Learning Engineer, AI Applications to join Bolt’s Customer Support Product team and lead the quality, learning, and knowledge foundations behind our AI automation stack. You will have the opportunity to shape how we evaluate and align LLM-based systems, improve knowledge quality and retrieval, and build the feedback loops that continuously improve customer support automation. If you are passionate about applied ML, retrieval and knowledge systems, and making AI products measurably better in production, this role will perfectly suit you.

With over 200 million customers in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, national origin, age, or disability.

Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission!

As a Staff Machine Learning Engineer, you will operate at the intersection of advanced AI, knowledge systems, and Bolt’s production support ecosystem, setting the technical direction for how we measure, improve, and scale AI quality across conversational experiences. You will help ensure our systems are accurate, helpful, grounded, and aligned with business and customer needs.

This is a high-impact, high-scope role where you will define the quality and learning strategy behind our AI systems, partner closely with engineering, product, operations, and domain experts, and turn real-world support interactions into durable improvements across models, retrieval, and workflows.

You will work closely with engineers and cross-functional partners building Bolt’s AI automation stack, helping ensure our systems are not only scalable and reliable, but also grounded, aligned, and continuously improving in production.

• Lead alignment of Customer Support AI system behaviour to Bolt’s business goals, customer experience standards, and policy requirements, improving answer quality, consistency, grounding, and escalation behaviour..
• Build and scale knowledge mining capabilities that turn conversations, support tickets, workflows, policies, and operational data into reusable knowledge assets and improvement signals.
• Own the evaluation strategy for LLM-powered customer support systems, including offline benchmarks, golden datasets, human review workflows, online experimentation, and production quality metrics.
• Develop feedback loops that connect production failures and human corrections back into prompts, retrieval, benchmarks, and model behaviour, enabling continuous improvement of automation quality.
• Partner closely with engineers working on AI application infrastructure, contributing ML expertise to areas such as tool-use quality, routing behaviour, memory quality, and multi-step task performance.
• Influence roadmap and technical direction across teams by bringing clarity to trade-offs in model behaviour, retrieval quality, experimentation, and business impact.

We are not really looking for Node.js experts, but for cross-language engineers for whom a specific stack is just a tool to solve a problem, not the solution itself.

• You have hands-on experience with retrieval-augmented systems, search, ranking, or knowledge-based AI applications, and understand what drives high-quality grounded responses.
• You have worked on knowledge-heavy or policy-constrained domains where correctness, consistency, and trust matter.
• You have experience building feedback loops from user behaviour, QA signals, annotations, or operational outcomes into system improvements.
• You are able to operate at both strategic and hands-on levels: defining long-term direction while also diving into data, experiments, and failure analysis.
• You have strong communication and stakeholder management skills, and can align engineering, product, and operations around quality strategy and trade-offs.
• Experience with LLM-based pipelines or agentic AI systems is a strong plus, especially in areas such as tool use, routing, memory, multi-step reasoning, or human-AI orchestration.

Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying if you feel you’re the kind of person described above!

• Play a direct role in shaping the future of mobility.
• Impact millions of customers and partners in 600+ cities across 50+ countries.
• Work in fast-moving autonomous teams with some of the smartest people in the world.
• Accelerate your professional growth with unique career opportunities.
• Get a rewarding salary and stock option package that lets you focus on doing your best work.
• Enjoy the flexibility of working in a hybrid mode with a minimum of 2 days in the office each week to foster strong connections and teamwork.
• Take care of your physical and mental health with our wellness perks.

*Some perks may differ depending on your location and role.

❗️Please note that this role is office based for Valencia, Spain (RAS Valencia - Servicios Profesionales de Recursos Humanos).

❗️If you need to be relocated, we take care of the process.

We are developing an innovative platform for intelligent gameplay analysis and complex in-game scenario automation. Our team builds internal tooling that bridges the gap between Computer Vision, text analysis, and modern LLM architectures to achieve deep, real-time understanding of game mechanics.

Key Responsibilities:

• Core Development: Designing and maintaining an in-house AI-powered service for intelligent automation.
• Computer Vision: Training and calibrating Object Detection and Classification models (CNNs, DETR) on unique proprietary datasets.
• Intelligent Analysis: Integrating OCR solutions and LLMs to interpret data and structure information from dynamic content.
• MLOps: Building pipelines for model retraining based on "low-confidence" predictions (Active Learning).
• Infrastructure: Containerizing solutions and ensuring their scalability and performance.

Our Tech Stack & Requirements:

• Experience: 4+ years in software development (Backend / Full Stack / SDET).
• AI/ML Background: Proven hands-on experience with Detection Transformers (DETR) or modern CNN architectures.
• LLM & Agents: Understanding of AI Agent principles; experience building tools and integrations with LLMs (LangChain, Indexing, Tool-use).
• Python: Strong proficiency in Python and experience in AI tool development.
• Engineering Excellence: Deep understanding of TDD, clean architecture principles, and database management (PostgreSQL/MySQL).
• Networking: Experience designing APIs (REST, GraphQL, WebSockets).
• English: Upper-Intermediate (technical documentation, professional communication).

Nice to Have:

• Experience with Kubernetes and Docker.
• Understanding of microservices architecture.
• Experience setting up CI/CD pipelines (GitLab CI, GitHub Actions).

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

We are looking for a Staff Backend Engineer, AI Applications to join Bolt’s Customer Support Automation team and architect the core AI agent infrastructure that powers our automation stack. You will have the opportunity to design and build multi-age nt orchestration frameworks, routine execution engines, and evaluation (LLM evaluations) and tracing pipelines that are scaling Customer Support automation. If you are passionate about agentic AI, distributed systems, and building platforms that operate at massive scale, this role will perfectly suit you.

With over 200 million customers in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, national origin, age, or disability.

Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission!

As a Staff Engineer, you will operate at the intersection of advanced AI and Bolt’s production engineering ecosystem, setting the technical direction for conversational experiences that are personalized, empathetic, and natural, while meeting strict business, compliance, and reliability requirements. This is a high-impact, high-scope role where you will guide platform evolution, amplify the effectiveness of multiple teams, and deliver resilient systems that enhance customer experience at a global scale.

• Define and evolve the technical vision for next-generation conversational assistants, setting architecture and long-term direction across multiple teams and partner orgs.
• Drive adoption of scalable patterns for agentic AI systems, including orchestration, memory, tool use, and multi-channel consistency.
• Design and productionize GenAI-powered customer support systems, covering agent frameworks, tooling, guardrails, observability, and backend services.
• Build reusable platform capabilities that enable teams to develop, deploy, and iterate on conversational experiences reliably
• Cross-org technical leadership and alignment: Identify ecosystem gaps and define interfaces, standards, and integration patterns across teams. Lead cross-functional alignment and execution, influencing roadmaps and driving consensus on platform direction.

We are not really looking for Node.js experts, but for cross-language engineers for whom a specific stack is just a tool to solve a problem, not the solution itself.

• You have experience of thriving in an environment that has a fast customer-feedback cycle and having empathy for the end-user
• You have a data-driven mindset with comfort around ML evaluation methodology - you know how to measure whether an AI system is actually working
• You have a drive for leading initiatives and features till the end, even if the last mile is the hardest.
• You have strong system design skills, particularly in distributed systems, event-driven architectures, and high-throughput data pipelines.
• You have hands-on experience with LLM-based pipelines or agentic AI patterns (tool use, routing, state machines, multi-agent coordination).
• You possess solid understanding of algorithms and data structures.

Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying if you feel you’re the kind of person described above!

• Play a direct role in shaping the future of mobility.
• Impact millions of customers and partners in 600+ cities across 50+ countries.
• Work in fast-moving autonomous teams with some of the smartest people in the world.
• Accelerate your professional growth with unique career opportunities.
• Get a rewarding salary and stock option package that lets you focus on doing your best work.
• Enjoy the flexibility of working in a hybrid mode with a minimum of 2 days in the office each week to foster strong connections and teamwork.
• Take care of your physical and mental health with our wellness perks.

*Some perks may differ depending on your location and role.

About Shelf

The enterprise is going agentic — but most AI agents fail when they hit real business complexity. Shelf is changing that.

We’ve built the operating system for agentic AI: a platform that models your policies, workflows, and operational logic into an AI Data Model so agents don’t just respond — they reason. The result? AI that understands how your business actually runs and delivers precise, compliant, auditable outcomes at scale.

Brands like Amazon, Nespresso, HelloFresh, and KeyBank trust Shelf to power AI agents that resolve 85% of cases autonomously, cut handle times by 20–25%, and turn hours-long processes into seconds. We’re partnered with Microsoft, Salesforce, OpenAI, Snowflake, and Databricks — and recognized by Gartner (Cool Vendor) and IDC (Innovator) for our approach.

If you want to sell the infrastructure that makes agentic AI actually work in the enterprise, you’re in the right place.

Our mission is to empower humanity with better answers everywhere.

Senior Frontend React Developer:

As a Frontend Engineer at Shelf, you'll craft the interfaces that make enterprise AI accessible and trustworthy. While others are building chatbots, we're solving the harder problem: how do you build UIs that help users confidently navigate AI-powered systems processing millions of documents, while maintaining enterprise-grade reliability?

You won't just build React components — you'll architect production-ready Next.js applications that handle high-load scenarios with complex states, real-time AI streaming, and multiple layers of enterprise functionality. Every interface decision you make directly impacts how knowledge workers at the biggest companies in the market interact with their most critical information.

This is frontend engineering at its most demanding. You'll tackle challenges like building real-time streaming interfaces for LLM responses, architecting state management for concurrent AI operations across multiple tenants, creating accessible interfaces for complex knowledge graphs with thousands of nodes, and ensuring blazing fast interactions even with petabytes of searchable content. Your components will bridge everything from enterprise authentication systems to cutting-edge AI models, requiring both sophisticated technical skills and sharp product instincts.

We obsess over frontend quality because we're building the trust layer for AI itself. When your interfaces gracefully handle edge cases, provide clear feedback during AI processing, and remain performant under load, you're not just meeting UX standards - you're directly enabling users to trust AI-powered answers and make critical business decisions with confidence.

You'll work on production SSR applications serving thousands of enterprise users, implementing localization for global markets, ensuring accessibility compliance, and maintaining security standards that pass SOC 2 audits. Your code will integrate with our Elasticsearch clusters, DynamoDB tables, and Aurora PostgreSQL databases through the largest park of REST APIs, handling real-time websocket updates for AI streaming and collaborative features.

We're a product company that ships fast without compromising on lasting quality. You'll work alongside proactive, ever-learning engineers who actively use AI coding assistants (OpenAI Codex, Claude Code) to accelerate development. We build custom MCP servers, implement DSPy pipelines for LLM optimization, and experiment with different AI tools for implementation. In our environment, AI isn't just what we build — it's how we build.

The best engineers we know are drawn to problems that matter. If you're excited by the challenge of building interfaces that make the AI revolution actually usable and trustworthy for enterprise users, this role offers the rare combination of technical depth, meaningful impact, and the prestige of solving UX patterns that the industry hasn't figured out yet.

Responsibilities

• Design and implement production-ready Next.js SSR applications with complex state management, handling high-load scenarios and real-time AI interactions at scale
• Build interfaces for AI-powered features including streaming LLM responses, semantic search across millions of documents, interactive knowledge graphs, intelligent content recommendations, and AI agentic builders
• Architect component libraries and maintain our design system in Storybook, ensuring reusability, accessibility, and consistent UX patterns across the platform
• Develop enterprise-grade functionality including multi-language support, accessibility compliance, cross-browser compatibility, and security implementations that meet SOC 2 standards
• Create comprehensive technical specifications and component API designs that clearly communicate interface decisions, performance trade-offs, and accessibility considerations
• Build and optimize data-heavy UIs using React Flow for node-based graphs, Highcharts for analytics visualizations, and custom virtualization for handling large datasets
• Instrument components for performance monitoring, track Core Web Vitals, implement error boundaries, and build automated visual regression tests with Playwright
• Take full ownership of the features you build, monitoring their performance in production, optimizing bundle sizes, and ensuring they scale gracefully as user load grows
• Work with SWR for intelligent data fetching, caching, and revalidation strategies that minimize API calls while keeping UIs responsive and data fresh
• Integrate with backend services via REST APIs, handle websocket connections for real-time updates, and implement optimistic UI patterns for seamless user experiences
• Leverage AI coding assistants to accelerate development while maintaining high code quality, and contribute to building internal AI agents that automate frontend workflows
• Stay current with React ecosystem best practices, Next.js updates, AI UX patterns, and modern frontend architecture—experiment with new approaches and share findings with the team
• Contribute to our engineering standards and practices through thoughtful code reviews, mentor colleagues on frontend best practices, and actively participate in our culture of continuous learning

Requirements

• Over 5 years of professional frontend engineering experience, including more than 3 years specializing in React and modern JavaScript/TypeScript
• Production Next.js experience - you've built and shipped SSR applications at scale, understand app router patterns, server components, and the trade-offs between SSR, SSG, and CSR
• Deep TypeScript expertise - you write type-safe code with generics, utility types, and advanced patterns. 
• Complex state management - hands-on experience architecting state solutions for challenging scenarios: real-time collaboration, optimistic updates, multi-tenant data isolation, and large-scale data synchronization
• Enterprise application development - you've built applications with localization (i18n), accessibility, security best practices, and compliance requirements. You understand the complexity beyond "making it work"
• AI/LLM interface experience - you've built interfaces for AI-powered features: streaming token responses, chat UIs, semantic search, or similar real-time AI interactions
• High-load optimization - proven track record optimizing applications for performance under heavy traffic, large datasets, and concurrent operations. You monitor Core Web Vitals and know how to improve them
• Modern CSS mastery - strong expertise with Tailwind CSS and/or CSS-in-JS solutions. You can implement pixel-perfect designs while maintaining responsive layouts and dark mode support
• Write well-structured, testable code with thoughtful component abstractions and clean APIs. You know when to abstract and when to keep it simple
• Strong problem-solving skills and genuine curiosity - you don't wait for designs to be perfect but proactively identify UX issues and propose solutions. You're never satisfied with "good enough" and constantly refine your craft
• Experience with AI coding assistants (OpenAI Codex, Claude, etc.) and eagerness to push the boundaries of AI-assisted development. Part of this role involves creating AI agents to automate portions of the frontend workflow
• Familiarity with observability and monitoring tools like Datadog, Sentry, or similar platforms for tracking frontend performance and errors in production
• Upper-Intermediate or better English skills for technical communication, documentation, and collaborating with distributed teams
• Present your work effectively both verbally and visually - you can articulate design decisions, create component documentation, and explain technical trade-offs clearly

Be a Plus:

• Experience with React Flow, Highcharts, or other complex data visualization libraries
• Understanding of Node.js/Python/backend fundamentals - you can read backend code and contribute to API design discussions
• Experience with SWR, React Query, or similar data fetching libraries
• Hands-on experience with vector search UIs, RAG interfaces, or semantic search implementations
• Familiarity with MCP (Model Context Protocol), DSPy, or other cutting-edge AI frameworks
• Experience with monorepo tools (Lerna, Turborepo, Nx) and managing shared component libraries
• AWS services knowledge (S3, CloudFront, Lambda) and understanding of serverless architectures
• Built or contributed to design systems or open-source component libraries
• Experience with Playwright, Puppeteer, or Cypress for comprehensive E2E testing
• Experience building AI agent interfaces or agentic AI workflows

What Shelf Offers:

• B2B contract
• Company Stock Options
• Hardware: MacBook Pro
• Modern technical stack. Develop open-source software
• Premier AI development environment: GitHub Copilot, Claude Code, OpenAI Codex, TypingMind, v0, MCP Servers, plus credits for experimenting with emerging AI tools

Why Shelf

• Our Leadership Team has deep knowledge management and AI domain expertise and enterprise SaaS background to execute this plan
• We love our customers and our customers love us. Ask a Shelf customer why, and they’ll tell you it’s because of our innovative capabilities, rock-solid reliability, they truly enjoy working with our people, but most of all – it’s the improvements they see in their business KPIs.
• We have raised over $60 million in funding and our investors include Tiger Global, Insight Partners, Connecticut Innovations, and others
• We have high velocity growth powered by the most innovative product in our category, 3X growth for 3 years in a row
• We now have over 100 employees in multiple U.S. states and European countries, and we have ambitious hiring goals over the next few months

Our Values:

Quality - We’re united by our focus on world‑class Quality. Quality in all things – starting with everything that leaves your desk. Everything you touch – every email, report, campaign, and piece of code – should be outstanding. Your work product should blow people away. Having people look at what you’ve done and say, “Wow.” That’s the standard here. Remember that how you do anything is how you do everything. Focus on craftsmanship—your ability to make things better.

Momentum - for us means that you should know that the things you’re responsible for are moving forward. When you look around and see something that’s stalled, get it moving again. We pride ourselves on “ball movement.” When your boss or team leaves you with something, they should return to see measurable progress. Small, continuous movement is our recipe for success. Constantly look for how to make the work around you move forward. We want you to initiate solutions, ideas, and progress. Don’t wait for it to come to you—reach out and create movement. All the time.

Accountability - We expect every team member to feel that they are accountable for more than anyone might normally expect. Each of us should feel real responsibility for things even at the edge of our control. We consistently share and align on expectations, give each other open and respectful feedback, and use those two drivers to ensure that every agreement we make with one another is clear and complete.

Hard Work - We’re here to do something difficult together. We care intensely about the mission and we expect that from our teammates. That care means that we work hard here. Hard work comes with long hours, extra effort…and real opportunity at Shelf. Your passion for creating and sustaining output is a part of our DNA. Support each other, cheer each other on, drive the mission forward. Great teams sustain intense effort together to win.

Learning Agility - We’re innovating in one of the fastest‑moving spaces in history at a time of accelerating global change. That’s incredibly exciting and requires each of us to commit fully to learning each and every day so that we can be the best at what we do. None of us know everything. All of us can learn anything. Staying open and constantly curious is a key success driver at Shelf. It also requires humility. We prize people who are consistently humble and open to making mistakes and growing from them. Recognize also that learning itself is a skill…we need you to be really good at it. Keep dialing in your own understanding about how you learn best and push yourself to keep growing.

Adapt and Thrive - Overcoming challenges lives deep in our DNA. We have a proud history of understanding and living the reality that obstacles are our opportunities…they’re the key to our success. Change is a constant in our business and fighting change is counterproductive. We need you to be good at being uncomfortable and understand that discomfort is the key to growth. Cultivate your own ability to adapt and know that struggling well is something you’ll share with every team you’re on at Shelf. Our company stories are about thriving through real difficulty…together.

Win Together - We win or lose as a team. Always. Everything you do here is connected to the rest of the organization. Part of our shared team environment demands full honesty…real candor and directness with one another. We expect you to constantly be thinking about how to support your teammates and the company, always acting in service to our shared mission and what’s best for the organization as a whole.

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

We are looking for a Senior ML Platform Engineer to join our ML Platform team to build, evolve and scale AI Infrastructure that powers Bolt's intelligent services

With over 200 million customers in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, age, or disability.

Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission!

The ML Platform Team makes ML/AI easy at scale. We streamline development, testing and deployment of ML/AI systems for hundreds of real-time algorithms. 

We own training orchestration, an inference software stack and infrastructure, and a Feature Store, including VectorSearch and RAG tooling. We develop LLM tools and CI/CD for ML, covering the whole range of ML infrastructure needs.

Our tech stack includes TypeScript, Python, Spark (batch and structured streaming), Airflow, n8n, MLflow, LiteLLM, AWS SageMaker, Redis, Elasticsearch, Docker, Kubernetes, AWS (S3, EKS), Terraform, Great Expectations. 

• Designing, building, and optimising components of Bolt’s ML Platform.
• Optimise and extend our in-house Feature Store Platform serving billions of data points in real-time.
• Tune infrastructure (k8s and AWS) and build automations to achieve the best cost-performance.
• Proactively solve technical challenges, discover and build new features, enabling develop efficiency.
• Support our internal users and help with troubleshooting, and turn user problems into scalable solutions.
• Raise our product and technical quality bar, promoting software engineering best practices.

• 5+ years of experience in Software Engineering, out of which 2+ in ML/MLOPS/AI Engineering.
• Experience in leading and delivering complex cross-team projects.
• Production experience with Python, Spark, and Kubernetes.
• Experience in MLOPS and AI ecosystem, and developing end-to-end ML/AI solutions at scale.
• You strive for technical excellence while staying pragmatic to achieve outcomes for the users.

Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying!

• Accelerate your professional growth with unique career opportunities.
• Enjoy a rewarding salary and stock options, knowing that as Bolt succeeds, so do you.
• Take care of your physical and mental health with our wellness perks.
• Celebrate 5 years at Bolt with a 1-month paid sabbatical to recharge.
• Connect with colleagues at annual company events and smaller team gatherings.
• Balance flexibility and in-person collaboration with our hybrid model, including at least 12 monthly in-office days.

*Some perks may differ depending on your location and role.

We are looking for a Senior ML Platform Engineer to join our ML Platform team to build, evolve and scale AI Infrastructure that powers Bolt's intelligent services

With over 200 million customers in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, age, or disability.

Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission!

The ML Platform Team makes ML/AI easy at scale. We streamline development, testing and deployment of ML/AI systems for hundreds of real-time algorithms. 

We own training orchestration, an inference software stack and infrastructure, and a Feature Store, including VectorSearch and RAG tooling. We develop LLM tools and CI/CD for ML, covering the whole range of ML infrastructure needs.

Our tech stack includes TypeScript, Python, Spark (batch and structured streaming), Airflow, n8n, MLflow, LiteLLM, AWS SageMaker, Redis, Elasticsearch, Docker, Kubernetes, AWS (S3, EKS), Terraform, Great Expectations. 

• Designing, building, and optimising components of Bolt’s ML Platform.
• Optimise and extend our in-house Feature Store Platform serving billions of data points in real-time.
• Tune infrastructure (k8s and AWS) and build automations to achieve the best cost-performance.
• Proactively solve technical challenges, discover and build new features, enabling develop efficiency.
• Support our internal users and help with troubleshooting, and turn user problems into scalable solutions.
• Raise our product and technical quality bar, promoting software engineering best practices.

• 5+ years of experience in Software Engineering, out of which 2+ in ML/MLOPS/AI Engineering.
• Experience in leading and delivering complex cross-team projects.
• Production experience with Python, Spark, and Kubernetes.
• Experience in MLOPS and AI ecosystem, and developing end-to-end ML/AI solutions at scale.
• You strive for technical excellence while staying pragmatic to achieve outcomes for the users.

Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying!

• Accelerate your professional growth with unique career opportunities.
• Enjoy a rewarding salary and stock options, knowing that as Bolt succeeds, so do you.
• Take care of your physical and mental health with our wellness perks.
• Celebrate 5 years at Bolt with a 1-month paid sabbatical to recharge.
• Connect with colleagues at annual company events and smaller team gatherings.
• Balance flexibility and in-person collaboration with our hybrid model, including at least 12 monthly in-office days.

*Some perks may differ depending on your location and role.

We’re looking for a Full Stack Engineer to join the Documents Team. Our team is working on building and scaling a new web application, expanding the ecosystem of one of our key products. This is a great opportunity to have a real impact on product decisions, architecture, and user experience while working across both frontend and backend.

What you’ll do: 

• Developing user-facing application(s):

             - Main stack is Typescript, React, Nextjs, Tailwind

             - Back-end is Node, Nestjs, Postgres, AWS

• Back-end tasks to power new functionality for both web and iOS app
• Working with product and marketing teams to define clear requirements and estimates
• Writing tests
• Always teaching others and giving helpful feedback
• Good SEO and accessibility is a must
• Experience with various third-party integrations as we will integrate more and more

About you:

Front-end:

• React, CSS
• Next.js, TailwindSEO
• SEO, Accessibility
• Smooth animations
• Responsive UI
• Pixel-perfect implementation

Back-end:

• Nest.js and Postgres
• Distributed systems and event-based architecture
• SQL skills and experience working with ORMs
• CI/CD, and infrastructure setup
• Third-party integrations and their side-effects

Overall:

• Strong English skills (we have several required meetups in English, plus engineers present the features themselves in English)
• Enjoy working on pet projects, finds opportunities to learn and try something outside of work projects only
• Enjoy both back-end and front-end.

Would be a plus:

• AI integrations
• External LLM tools, like LangFuse, LangChain, etc.
• Desire to build automations
• Interest in knowledge sharing

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

Job Description

About the Role

We are looking for a Senior / Staff Backend Engineer in Poland to join Inflect as a contractor on our Engineering team and take strong technical ownership of key backend services. This is a hands-on, execution-focused role for an experienced engineer who enjoys building, scaling, and improving production systems that directly power the business.

This role is suitable for a senior engineer operating at senior or early staff level, with strong technical ownership and autonomy.

You will work in a small, senior engineering team, where each engineer has significant ownership, autonomy, and direct impact on the product. You will have a real influence on backend architecture, technical direction, and tooling choices, while staying closely aligned with product and business goals.

This role does not involve people management or ownership of legacy systems - it is focused on building, scaling, and improving modern backend services.

About Inflect

Inflect builds and operates an IT infrastructure marketplace, connecting buyers and service providers through a single, product-driven platform - not a software house or agency.

We manage complex marketplace workflows at the intersection of cloud infrastructure, network services, and large-scale compute (CPU/GPU). Our marketplace integrates directly with service providers and enables buyers to discover, compare, and transact infrastructure services in a frictionless way.

Our engineering culture values pragmatism, ownership, and fast feedback. We focus on delivering real business value over rigid process frameworks or excessive ceremony.

How You’ll Work

• Primary working hours are in the Polish (CET) time zone, with regular collaboration and overlap with engineers and stakeholders in the United States
• Hybrid work model: 1–2 days per week in our Warsaw office is preferred
• Daily communication in English with US-based engineers and partners
• Close collaboration with Product, Backend, and Infrastructure-focused teammates

Responsibilities

• Take technical ownership of key backend services that power Inflect’s marketplace and service provider integrations
• Design, implement, and scale backend systems that support onboarding and integration of new groups of service providers
• Actively collaborate with Product and Engineering leadership to translate marketplace and integration requirements into pragmatic, production-ready technical solutions
• Design and implement distributed backend services with a strong focus on:
• reliability
• throughput and latency
• resiliency
• delivery speed
• and cost efficiency
• Rapidly validate ideas, build production-ready solutions, and iterate based on real usage and feedback
• Write robust, well-structured code with full test coverage to ensure reliability and long-term maintainability
• Proactively identify architectural, performance, and scalability risks and address them before they impact the business
• Mentor other engineers through code reviews, technical discussions, and knowledge sharing, helping raise overall engineering quality
• Maintain empathy for end users while staying focused on delivering measurable business value

Definition of Success (First 6 Months)

Success in this role after approximately 6 months means:

• Successfully delivering backend integrations with a new group of service providers, enabling them to operate within Inflect’s marketplace
• Ensuring that core marketplace flows (e.g. provider onboarding, offer availability, transactional or pre-transactional workflows) are reliable, scalable, and production-ready
• Taking ownership of the backend systems that support these flows and being accountable for their correctness, stability, and performance
• Becoming a trusted technical partner for product and engineering leadership in the evolution of the marketplace
• Improving delivery speed and technical confidence of the team through better tooling, CI/CD, and pragmatic engineering practices

Minimum Requirements

• 7+ years of professional backend development experience, including 5+ years of production experience in Go
• Strong experience designing, building, and operating backend systems at scale in cloud environments
• Hands-on experience with relational and in-memory data stores such as Postgres and Redis
• Experience deploying and operating services in AWS, GCP, or another major public cloud
• Ability to communicate technical concepts clearly and collaborate effectively across teams
• Native-level Polish (spoken and written) and strong professional English for daily collaboration with US-based engineers
• Familiarity with JIRA and Confluence for day-to-day workflow management

Highly Valued / Nice-to-Have Experience

These skills are highly valued, but not required. They will significantly accelerate your impact at Inflect:

• Marketplace or transaction-heavy systems
• Experience building platforms that connect multiple parties, handle pricing logic, or manage marketplace-style workflows.
• AI-enabled backend systems
  • Experience building and shipping LLM-powered features (chatbots, internal AI tools) and designing multi-agent workflows (planner/worker, master-agent orchestration, tool delegation, memory strategies)
  • Practical prompt/context engineering (structured outputs, context limits, prompt versioning)
  • Ability to debug and improve AI quality in production (hallucinations, retrieval relevance, logging, evals)

• Infrastructure or networking domain exposure
• Familiarity with cloud infrastructure, network services, or large-scale compute systems (CPU/GPU), even at a conceptual or integration level

What You Won’t Be Doing

• No people management
• No ownership of large, legacy monolithic systems
• No rigid, ceremony-heavy process frameworks

We are looking for a Senior ML Platform Engineer to join our ML Platform team to build, evolve and scale AI Infrastructure that powers Bolt's intelligent services

With over 200 million customers in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, age, or disability.

Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission!

The ML Platform Team makes ML/AI easy at scale. We streamline development, testing and deployment of ML/AI systems for hundreds of real-time algorithms. 

We own training orchestration, an inference software stack and infrastructure, and a Feature Store, including VectorSearch and RAG tooling. We develop LLM tools and CI/CD for ML, covering the whole range of ML infrastructure needs.

Our tech stack includes TypeScript, Python, Spark (batch and structured streaming), Airflow, n8n, MLflow, LiteLLM, AWS SageMaker, Redis, Elasticsearch, Docker, Kubernetes, AWS (S3, EKS), Terraform, Great Expectations. 

• Designing, building, and optimising components of Bolt’s ML Platform.
• Optimise and extend our in-house Feature Store Platform serving billions of data points in real-time.
• Tune infrastructure (k8s and AWS) and build automations to achieve the best cost-performance.
• Proactively solve technical challenges, discover and build new features, enabling develop efficiency.
• Support our internal users and help with troubleshooting, and turn user problems into scalable solutions.
• Raise our product and technical quality bar, promoting software engineering best practices.

• 5+ years of experience in Software Engineering, out of which 2+ in ML/MLOPS/AI Engineering.
• Experience in leading and delivering complex cross-team projects.
• Production experience with Python, Spark, and Kubernetes.
• Experience in MLOPS and AI ecosystem, and developing end-to-end ML/AI solutions at scale.
• You strive for technical excellence while staying pragmatic to achieve outcomes for the users.

Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying!

• Accelerate your professional growth with unique career opportunities.
• Enjoy a rewarding salary and stock options, knowing that as Bolt succeeds, so do you.
• Take care of your physical and mental health with our wellness perks.
• Celebrate 5 years at Bolt with a 1-month paid sabbatical to recharge.
• Connect with colleagues at annual company events and smaller team gatherings.
• Balance flexibility and in-person collaboration with our hybrid model, including at least 12 monthly in-office days.

*Some perks may differ depending on your location and role.