AI Lead, Python Tools

JetBrains

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 We are an equal opportunity employer We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation. We process the data provided in your job application in accordance with the Recruitment Privacy Policy.

Tibber

We're at a pivotal moment for both Tibber and the planet. When joining Tibber, you won’t just help scale a forward-thinking tech company – you’ll contribute to a real shift in how people consume electricity. With millions of smart devices connected to the Tibber platform (like electric vehicles and smart thermostats), we have one of the most unique energy trading portfolios on the market. We’re looking for a AI Solutions Lead to join us in making the energy transition happen – maybe that’s you? ---------------------------------------------------------------------------------------------------------------------------------- Job Mission 🚀 As AI Solutions Lead, you drive execution within Tibber's company-wide AI program. You embed in teams across the business, identify where AI can create the most value, and ship working solutions - fast. This is a hands-on strategic role. You combine technical depth with the ability to navigate stakeholders, align with business priorities, and scale what works across the organization. ---------------------------------------------------------------------------------------------------------------------------------- What you'll do ✅ * Rapid AI Deployment * Identify high-leverage opportunities for AI across Tibber’s products and operations * Design and implement prototypes within days - not months * Cross-Functional Impact * Embed temporarily in different teams (product, customer support, trading, etc.) * Translate business problems into AI-driven solutions * Build & Ship * Develop and deploy models, agents, and automations (LLMs, ML models, pipelines) * Integrate AI into production systems with engineering teams * Tooling & Enablement * Create reusable AI tools, frameworks, and internal platforms * Enable non-technical teams to leverage AI effectively * Experimentation * Run fast experiments, validate impact, and scale what works * Balance speed with measurable business value ---------------------------------------------------------------------------------------------------------------------------------- What we're looking for⚡ You are a hands-on AI builder who enjoys turning business problems into working solutions. You are comfortable writing code, working closely with both engineers and business stakeholders, and taking ideas all the way into practice. Required Skills * Strong hands-on experience building and deploying AI solutions in production * Confident in Python or TypeScript, and comfortable working with APIs, data pipelines, and system integrations * Have worked with LLM-based applications, such as automations, agents, or retrieval-based solutions * Know how to move quickly from idea to prototype, and from prototype to real usage * Have experience helping non-technical teams adopt AI in their workflows * Are pragmatic, structured, and focused on business impact * Communicate clearly and work well across functions We see it as a plus if you have... * Experience with energy markets, IoT, or real-time data systems * Background in startups or high-growth tech environments * Familiarity with MLOps / deployment pipelines * Experience with automation tools and internal AI platforms ---------------------------------------------------------------------------------------------------------------------------------- 💆🏻‍♀️💆🏽‍♂️The Tibber Mindset Tibber is not your typical energy supplier. Our tech helps hundreds of thousands of households lower and shift their energy consumption to more sustainable and affordable hours. We’re here to accelerate the energy transition – not in theory, but in everyday life. Being on a mission to change an industry, fundamentally also means being prepared for the unexpected. We do what others say can’t be done, try and fail together but never lose sight of our users. We work passionately with sustainability and a circular approach, both with our own products and in the entire ecosystem that is affected by everything we do. Starting out with two passionate founders in 2016, we're now 300+ people working for Tibber in our offices in Stockholm, Førde, Berlin, Amsterdam, and Oslo. We will continue to grow within our markets, and we are thrilled to be backed by investors like Balderton Capital, Eight Roads Ventures, Founders Fund, Summa, and Schibsted. Diversity of thought fuels better products, so we welcome applicants of every background, identity and lived experience. Ready to be part of powering the energy transition? Apply below!

BlueCrest Capital Management

Department overview: The Front Office AI Technology Team sits within the Front Office Technology department and provides a shared capability for the development, operation, and adoption of AI across the firm. The team is responsible for building and supporting enterprise‑grade AI capabilities, including LLM‑powered applications, retrieval‑augmented generation (RAG) systems, agent‑assisted workflows, and scalable internal AI tooling. We develop the core AI foundations required to deploy AI safely and at scale, while also working closely with the business to ensure these capabilities are used effectively in day‑to‑day workflows. This includes supporting experimentation, guiding practical adoption, and helping teams embed AI into real processes where it delivers measurable benefit. A key focus of The Front Office AI Technology Team is ensuring that AI solutions are reliable, secure, and aligned with the firm’s control and risk frameworks. The team balances innovation with discipline, providing common tooling, patterns, and guidance that allow AI to be used consistently and responsibly across research and operational contexts. Role overview: Key Responsibilities: AI Enablement & Integration * Act as a go‑to point of contact for teams who want to understand what AI tools are available and how to use them effectively. * Run workshops, demos, and hands‑on sessions that help users understand the benefit of using LLMs and emerging AI related technologies both for business users and more technical teams. * Support day‑to‑day adoption of Microsoft Copilot, ChatGPT and Claude alongside other approved AI tools by embedding them into real workflows. Training & Best Practice * Deliver practical training on prompt engineering, AI limitations, and good usage patterns for both technical and non‑technical audiences. * Create and maintain reusable materials such as prompt examples/libraries, walkthroughs, and short guidance notes. * Continuously refine training content based on user feedback and emerging best practice. Understanding Business Processes * Spend time with teams to understand their existing processes, pain points, and where work is slow, repetitive, or manual. * Help teams articulate problems clearly enough that AI tooling can be applied sensibly. * Map simple end‑to‑end workflows and identify realistic opportunities for AI assistance. Light Prototyping & Applied AI * Build simple prototypes or proof‑of‑concept workflows using Python, internal libraries, or approved AI APIs alongside tools such as MS Copilot Studio. * Pair with engineers or platform teams when ideas move beyond quick prototypes. * Focus on small, shippable improvements rather than large, speculative solutions. Feedback & Continuous Improvement * Collect structured feedback on what works, what doesn’t, and where users get stuck. * Share insights with The Front Office AI Tech Team, governance, and Infrastructure Tech teams to help guide tooling, documentation, and prioritisation. * Help surface recurring themes rather than one‑off requests. Adoption Metrics, Reporting & Insight * Support the definition and tracking of adoption metrics for approved internal AI tools. * Work with Front Office Technology and platform teams to help maintain simple reporting and dashboards that show usage and engagement patterns (for example: active users, frequency of use, and common use cases). * Monitor adoption trends and identify areas of low engagement or friction that may require additional enablement, training, or tooling changes. * Combine quantitative usage data with qualitative user feedback to build a clear view of how AI tools are being used in practice. * Share regular adoption insights with relevant stakeholders to inform prioritisation of training materials, documentation, and incremental improvements to AI tooling. Why this role exists: The firm is investing heavily in modern AI platforms and tools, but technology alone does not create value. Real impact comes when teams change how they work. This role exists to help front‑office and technology teams translate AI capability into everyday practice, replacing one‑off experimentation with well‑understood patterns, better habits, and repeatable workflows. Through hands‑on enablement, training, and applied problem‑solving, the AI Integration Lead ensures that AI use is both effective and appropriately governed, allowing teams to move faster without increasing operational or compliance risk. What makes this role different: This role offers the chance to work directly with trading desks, providing a rare and exciting opportunity to gain direct front-office exposure. You’ll work at the intersection of business context and applied AI: understanding how teams operate, then helping them adopt approved AI tools safely and effectively through training, workflow mapping, and lightweight prototyping. It’s ideal for someone who enjoys ambiguity, values practical impact over hype, and wants to see their work change how teams operate day-to-day.   Skills & Experience Essential: * Demonstrated interest in evolving applied AI technologies and their use in improving real business processes in a practical and controlled manner. * Experience delivering or supporting training, workshops, or enablement sessions for technical and non‑technical audiences. * Hands‑on experience using modern AI tools beyond typical end‑user interaction, including:                 - Practical understanding of prompt engineering techniques and common LLM failure modes                 - Experience grounding AI outputs in data (e.g. through document retrieval, APIs, MCP or structured context rather than free‑text prompting alone)                 - Exposure to designing AI‑assisted workflows that support repeatable tasks rather than one‑off interactions. * Familiarity with enterprise and low‑code AI tooling, such as Microsoft Power Apps, Power Automate, Copilot Studio, Claude Cowork, or similar workflow and AI enablement platforms. * Practical experience assessing AI output quality and limitations for real business use cases, and iterating prompts or workflows to improve reliability. * Comfortable working with Python at a practical level (scripts, APIs, data handling), without requiring production‑grade engineering expertise. * Strong communication skills, with the ability to explain technical concepts clearly to non‑technical users. * Comfortable operating in environments with evolving requirements, and able to iterate pragmatically rather than waiting for complete specifications. Desirable: * Familiarity with retrieval‑augmented generation (RAG) concepts at a practical level, such as working with internal documents or structured reference data. * Experience designing or supporting simple AI‑assisted workflows for document handling, summarisation, data extraction, or knowledge access. * Awareness of responsible AI considerations in regulated environments, including basic data handling, validation of outputs, and appropriate human review. * Exposure to lightweight agent‑style patterns (e.g. tool use, structured outputs, task decomposition), without requiring ownership of complex agent frameworks. About you: You are a bright and approachable individual who works well with others and enjoys understanding how different teams operate in practice. You are comfortable engaging with both technical and non‑technical stakeholders and are able to communicate clearly and pragmatically. Alongside your technical experience, you may bring experience from a client‑facing or commercially oriented role earlier in your career, which helps you understand business priorities and frame solutions in a way that resonates with users. You have a strong interest in applied AI and a genuine curiosity about how emerging tools can improve the way people work. You are motivated to explore new capabilities, experiment hands‑on, and understand where AI can add value in real workflows. Your approach is practical rather than theoretical, and you are focused on achievable improvements rather than technology for its own sake. You take a considered and responsible approach to AI integration. You are aware of the limitations of AI tools and the importance of appropriate controls, validation, and oversight, particularly in a regulated environment. You are comfortable discussing both the benefits and constraints of AI with users, helping set realistic expectations and encouraging sensible use. You work well in collaborative environments where priorities and requirements evolve. You are adaptable, open to feedback, and comfortable learning by doing. You take satisfaction from helping others build confidence with new tools and from supporting inte across teams, bringing a constructive and measured mindset to your work.   BlueCrest is committed to providing an inclusive environment for its workforce. As an employer, we provide equal opportunities to all people regardless of their gender, marital or civil partnership status, race, religion or ethnicity, disability, age, sexual orientation or nationality.