
Octopus Energy · London
ABOUT THE ROLE Octopus was founded with a mission to use technology to accelerate us towards a low-carbon future. That’s why we created Kraken - our own techno...
Octopus was founded with a mission to use technology to accelerate us towards a low-carbon future. That’s why we created Kraken -
our own technology platform from scratch which now serves over 70 Million households and is a core reason why Octopus is the
number one energy supplier in the UK. We do it by hiring clever, curious, and self-driven people, enabling them with modern tools
and infrastructure and giving them lots of autonomy.
We have been using GenAI in live, customer-facing environments since 2022, including one system that creates tens of thousands of
high-quality emails for our Energy Specialists, combining our deep knowledge of the energy industry and the Octo communication
style with customer-specific data from Kraken.
We are now looking for a Senior AI Engineer. You will build and scale the systems that allow Octopus teams to use Generative AI
models (LLMs, RAG, agents). You will be hands-on, working with a cross-functional team to build out flagship AI projects, and the
platforms that enable others to succeed with Generative AI.
You’ll work on developing solutions that genuinely move us closer to Net Zero in a company passionate about building great
technology to change the way customers use energy. You’ll have wide open problems to solve, so you’ll need to be comfortable with
ambiguity, figuring out an approach and validating it fast.
500M+ downloads. 80M+ monthly users. A decade of building – and we’re still accelerating. Flo is the world’s #1 health & fitness app worldwide on a mission to build a better future for female health. Backed by a $200M investment led by General Atlantic, we became the first product of our kind to reach a $1B valuation in 2024 – and we’re not slowing down. With 7M paid subscribers and the highest-rated experience in the App Store’s health category, we’ve spent 10 years earning trust at scale. Now, we’re building the next generation of digital health – AI-powered, privacy-first, clinically backed – to help our users know their body better. The job We are looking for a Senior Software Engineer with deep expertise in AI/ML infrastructure to join our AI Platform team and help build the GenAI platform that powers every AI feature at Flo. You will bridge core infrastructure, data engineering, and LLM development to deliver production-grade medical safety judges, fine-tuning pipelines, evaluation frameworks, and real-time personalisation. The team operates 60+ LLM-based evaluation judges, develops proprietary fine-tuned health models, and maintains active partnerships with Databricks, Google, OpenAI, Anthropic, and AWS. What you’ll do * LLM Judge Ecosystem: build and scale Judge-as-a-Service, prompt registries, calibration pipelines, and evaluation orchestration using MLflow 3.x * Fine-Tuning and Serving: develop LoRA/SFT/preference optimisation pipelines for health-domain models (Llama, Gemma, MedGemma) and manage model serving at scale on Databricks * Data and Evaluation Pipelines: build synthetic Q&A generation, golden test sets, reward function engineering, and Delta table schemas in Unity Catalog for reliable, reproducible evaluation data * Infrastructure: maintain Terraform-managed AWS infrastructure (EKS, S3, IAM), Databricks AI Gateway, and CI/CD pipelines (GitHub Actions) with evaluation gates and progressive rollout * Cross-Functional Impact: collaborate with Product, Security, Analytics, and Medical teams, develop internal SDKs and APIs consumed by 5+ teams, and engage directly with technology partners on pre-release capabilities Experience and skills Must have: * Engineering maturity: 7+ years of software engineering, 4+ years focused on ML/AI platforms * LLM experience: recent hands-on work with at least one of: fine-tuning, prompt engineering, LLM evaluation, or model serving * Technical stack: strong Python across production services and data pipelines, data engineering fundamentals (Spark, Delta tables, Parquet) * Platform and infrastructure: Databricks (MLflow, Unity Catalog, Model Serving), AWS (EKS/Kubernetes, IAM), Terraform, GitHub Actions * Cross-domain flexibility: comfort working across ML, data engineering, and infrastructure. You don’t need to be expert in all three, but you contribute wherever the team needs it Nice to have: * LLM evaluation frameworks (judges, graders, calibration methodology) or fine-tuning techniques (LoRA, RLHF/DPO, model distillation) * ML data engineering: synthetic data generation, evaluation dataset design, annotation pipelines * Healthcare, regulated industry, or safety-critical AI systems experience * Prompt optimisation frameworks (DSPy or similar), feature stores (Tecton) #LI-KP1 #LI-Hybrid Annual Salary Range (ranges may vary based on skills and experience) £120,000—£150,000 GBP How we work We’re a mission-led, product-driven team. We move fast, stay focused and take ownership – from brief to build to impact. Debate is encouraged. Decisions are shared. We care about craft, ship with purpose, and always raise the bar. You’ll be working with people who take their work seriously, not themselves. It takes commitment, resilience, and the drive to keep going when things get tough. Because better health outcomes are worth it. What you'll get We support impact with meaningful reward. Here’s what that looks like: * Competitive salary and annual reviews * Opportunity to participate in Flo’s performance incentive scheme * Paid holiday, sick leave, and female health leave * Enhanced parental leave and pay for maternity, paternity, same-sex and adoptive parents * Accelerated professional growth through world-changing work and learning support * In-person collaboration and work in a hybrid model, with 3 days per week spent in the office * 5-week fully paid sabbatical at 5-year Floversary * Flo Premium for friends & family, plus more health, pension and wellbeing perks Diversity, equity and inclusion Our strength is in our differences. At Flo, hiring is based on merit, skill and what you bring to the role – nothing else. We’re proud to be an equal opportunity employer, and we welcome applicants from all backgrounds, communities and identities. Read our privacy notice for job applicants.
ABOUT US Engelhart was founded in 2013 by BTG Pactual Group as a commodities trading company. Our business model is “asset light” and highly diversified – giving us the ability to adapt effectively and nimbly to changing market conditions. We have assembled successful multidisciplinary teams, leveraging advanced fundamental analysis with deep quantitative and weather research capabilities. Our activities are underpinned by strong risk management practices and by powerful technology and operational excellence. We have exceptional teams with diverse global backgrounds and decades of experience, and are driven by a highly collaborative culture, across products and competencies. In 2024, Engelhart acquired Trailstone, a global energy trading and technology company. The acquisition provides us with new expertise, analytics and proprietary technology which is being used to provide risk management and optimisation services to help maximise the value of our clients’ renewable power. The acquisition also expanded Engelhart’s capabilities into physical natural gas across North America, a critical fuel to support the energy transition. Our talented and experienced individuals work together according to its four company values: Performance, Agility, Collaboration, Entrepreneurship. ABOUT THE ROLE As a Technology Manager in our Tech Data, AI & UX team, you will lead a high-impact engineering group responsible for building, scaling, and operationalising data and AI capabilities across Engelhart’s trading, quantitative, risk and operational functions. This is a hands-on leadership role at the intersection of data engineering, AI platform delivery, front-office technology, and commodities trading The role reports to the Global Head of Tech - AI, Data & UX and will play a central part in implementing Engelhart’s AI Business Plan. That plan positions AI as a federated capability enabled by a central Tech AI team with responsibilities across platform, governance and delivery, working closely with trading desks, Quant & Systematic teams, MOBO, Risk, Compliance, People, senior management, external AI providers, cloud providers, data providers, BTG Pactual, Gridfuse, Metdesk and other partners. This role will work directly with Traders, Quants, FO Analysts, Risk, Compliance and Technology stakeholders. Experience with systematic trading, quantitative research workflows, or trading analytics platforms is highly desirable. The successful candidate will help translate front-office needs into robust technical capabilities, ensuring that AI and data solutions are useful, trusted, governed and adopted in real workflows. The broader mandate is to help Engelhart move from experimentation to production-grade AI capability: improving productivity, making company knowledge searchable, enabling AI-assisted workflows, and embedding AI into analytics through initiatives such as Risk Copilot, Treasury Copilot, Power Forecast Copilot, Trader Copilot, and Quant Copilot. ABOUT YOUR TEAM You will manage a team consisting of four Senior Data Engineers and two AI & Agentic Platform Interns, guiding delivery across both the core data engineering estate and the emerging agentic AI platform. The Senior Data Engineers are focused on building and maintaining data pipelines, integrating and cleansing data, supporting analytical and operational use cases, and enabling predictive analytics, machine learning, data mining, and systematic trading initiatives. The AI & Agentic Platform Interns support the design and implementation of Engelhart’s central Agentic AI platform, including orchestration layers, agent runtimes, AWS Lambda integrations, MCP servers, agent skills, knowledge bases, vector databases, retrieval pipelines, and AI productivity tooling. BREAKDOWN OF RESPONSIBILITIES This will be a full-time role based in our London office and owning the following responsibilities: * Lead and develop the AI & Data engineering team, directly managing four Senior Data Engineers and two AI & Agentic Platform Interns, setting clear priorities, coaching technical growth, reviewing delivery quality, and ensuring the team operates with high ownership, collaboration, and continuous improvement. * Drive implementation of the Agentic AI platform, supporting orchestration layers, agent runtimes, AWS-hosted services, Lambda-based tooling, MCP servers, knowledge bases, vector databases, retrieval pipelines, agent skills and secure deployment patterns within Engelhart’s internal network. * Support implementation of the AI Business Plan, helping deliver the central Tech AI team’s mandate across platform, governance and delivery, and contributing to the strategic themes of productivity, knowledge and data discovery, AI-assisted workflows, and AI-assisted analytics. * Support delivery of AI use cases such as Trader Copilot, Quant Copilot, Risk Copilot, Treasury Copilot, Power Forecast Copilot, reconciliation automation, AI Explorer, text-to-SQL, Confluence/wiki agents, contract/vendor agents and self-service AI workflows where relevant to the agreed roadmap. * Own delivery of scalable data engineering capabilities across Engelhart’s data landscape, including ingestion of structured and unstructured data, data cleansing, enrichment, transformation, storage, distribution, visualisation and operational reuse for Data Scientists, Traders, Quant developers and business stakeholders. * Partner with Quant and Systematic teams to enable data, AI and engineering capabilities that support research workflows, model-adjacent analytics, signal review, back testing support, code review, documentation and systematic trading productivity, while respecting ownership boundaries with Quant and trading teams. * Translate front-office requirements into practical technology solutions, working closely with Traders, Quants, FO Analysts, Risk and other business teams to identify high-value opportunities. * Champion production-grade engineering standards, including robust architecture, secure data access, maintainable code, CI/CD, infrastructure-as-code, observability, documentation, testing and clear operational ownership. * Ensure AI solutions are governed appropriately, contributing to standards around evaluation, provenance, human-in-the-loop design, auditability, monitoring, access control and safe deployment in collaboration with Compliance, Risk, AI Security and senior Technology stakeholders. * Measure and communicate value delivered, helping connect technical delivery to adoption, cost savings, front-office efficiency and business impact. The AI Business Plan identifies annualised value delivered and value-weighted adoption as key success measures. ABOUT YOU This individual will be an experienced engineering manager from a commodities trading environment. Someone who is comfortable leading a team of senior engineers whilst remaining close enough to the architecture and code to challenge design decisions, unblock delivery and set a high technical bar. The successful individual will understand that AI adoption is not just about models or tools; it depends on data quality, platform reliability, governance, user trust and day-to-day workflow fit. We believe the following background, experiences and skills are essential for application: * Strong domain understanding of commodities trading is essential. * Academic background or equivalent professional experience in Computer Science, Engineering, Data Science, Information Systems, Quantitative Finance, Mathematics or a related technical field. * Significant experience leading data engineering, AI engineering, platform engineering or technology delivery teams in a demanding business environment. * Proven experience managing, coaching and developing engineers; including senior individual contributors and early-career technical talent. * Strong hands-on understanding of modern data engineering practices, including data ingestion, transformation, cleansing, storage, distribution, data quality, documentation and operational support. * Advanced proficiency in Python and the wider Python data ecosystem, including experience with Pandas or comparable libraries for data crawling, parsing, analysis and engineering workflows. * Experience with analytical, time-series, or large-scale data platforms. ClickHouse is preferred and Redshift is also relevant, based on the current technical landscape. * Strong experience with cloud-native engineering, preferably AWS, including practical understanding of services such as S3, Lambda, Athena, EMR, Fargate, Kinesis, EC2, API Gateway, CloudWatch, and related architecture and security patterns. * Hands-on experience with Docker, Git, CI/CD, infrastructure-as-code, and modern software delivery practices. * Practical understanding of AI, LLM, or Generative AI application architecture, including RAG, knowledge bases, vector databases, prompt engineering, evaluation, orchestration, agent workflows, or AI-assisted developer tooling. * Experience engaging directly with Traders, Quant developers, Data Scientists, analysts or front-office stakeholders to gather requirements, challenge assumptions and deliver useful technical solutions. * Strong understanding of commodities trading, particularly Oil, Power, and Gas; including the role of market data, analytics, risk, weather, fundamentals, trading workflows and front-office decision support. * Ability to translate complex technical concepts for both technical and non-technical audiences, influencing decisions and building trust with stakeholders across levels. * Strong organisational skills and a strong sense of ownership, accountability, and follow-through. Preferably with a bias toward delivering production-grade solutions rather than prototypes that do not land. In addition, the following experiences and skills are not required, but highly desirable for this role: * Commodities coverage: Oil, Power, and Gas. * Experience in systematic trading, quantitative research platforms, trading analytics, signal generation, back testing workflows, or model-adjacent engineering. * Practical exposure to agentic AI frameworks and implementation patterns, such as LangChain, n8n, MCP servers, AWS Bedrock, Postgres with pgvector, Bedrock Knowledge Bases, Pinecone, Chroma, or comparable tools. * Experience designing or operating secure internal AI platforms, including private model deployment, VPC-based architectures, data-access controls, auditability, monitoring, and vendor due diligence. * Familiarity with AI governance, evaluation suites, provenance, human-in-the-loop workflows, risk classification, model monitoring, audit trails, and compliance considerations such as the EU AI Act. * Experience with REST APIs, SSIS, Entity Framework, internal API design, Python packages, and integration patterns across enterprise systems. * Experience with big data technologies such as Apache Spark, Databricks, Parquet, or Hive. * Experience with data visualisation libraries or platforms, including Plotly or equivalent tooling. * Experience working with GitHub Copilot-style engineering workflows, internal AI chat, summarization pipelines, or AI productivity tooling. * Experience working in a federated technology model where a central platform team enables business-aligned teams to own and improve their own workflows. * Experience engaging with external data vendors, cloud providers, consulting partners, or group-level technology partners. WHAT WE OFFER * Competitive compensation and participation in Engelhart’s discretionary bonus plan. * 25 days of annual holiday entitlement, excluding UK public holidays. * Robust benefits package such as medical, dental, life insurance, generous pension contribution, and supplemental benefits partially subsidised by the Company. * Eligibility to receive external and internal training in accordance with our Training & Development Policy. We believe in inclusivity and are therefore dedicated to ensuring all employees – across gender identity, race, ethnicity, sexual orientation, religion, life experience, background and more – feel welcome and included in the company. We promote diversity because we believe it is essential to our ability to think holistically.
ReqID: FEQ327R328 Recruiter: Kanwal Matharu Location: London, United Kingdom - Hybrid Skills: Data Science, Machine Learning, AI, LLM, GenAI As a Senior Specialist Solutions Engineer (SSE), ML Engineering, you will be the trusted technical ML expert to both Databricks customers and the Field Engineering organisation. You will work with Solution Architects to guide customers in architecting production-grade ML applications on Databricks, while aligning their technical roadmap with the evolving Databricks Data Intelligence Platform. You will continue to strengthen your technical skills through applying the latest technologies in GenAI, LLMOps, and ML, while expanding your impact through mentorship and establishing yourself as an ML expert. You will be reporting to the Manager, Field Engineering (Specialist Team) The impact you will have: * Lead the architectural design of production-grade ML workloads on our unified platform, encompassing the entire MLOps lifecycle from end-to-end pipeline creation and optimization (training/inference) to seamless integration with cloud-native services. * Provide advanced technical support to the Solution Architects during the technical sales cycle by building MVPs, leading deep-dive technical sessions, and strategically aligning ML/data science solutions to complex customer business challenges using relevant real-world examples. * Serve as the trusted technical advisor for customers developing GenAI solutions, specializing in the design and implementation of RAG architectures on enterprise knowledge bases, enabling natural language querying of structured data, and establishing content generation and monitoring frameworks. * Drive community growth and platform adoption through thought leadership activities, including the creation of technical tutorials and training materials, as well as leading hackathons and presenting at industry conferences. What we look for: * Experienced, technical, customer-facing, and with a background in Data Science / Machine Learning, and Data Engineering. Looking to learn and develop in a customer-facing technical role as a subject matter expert (SME) in a pre-sales environment. * Pre-sales or post-sales experience working with external clients across a variety of industry markets Data Science/ML Skills * Hands-on industry ML experience in at least one of the following: * ML Engineer: Develop production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring * Data Scientist: Experience with the latest techniques in natural language processing, including vector databases, fine-tuning LLMs, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI * Hands-on experience working with Distributed Spark based systems. * Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience * Experience communicating and teaching technical concepts to non-technical and technical audiences alike * Passion for collaboration, life-long learning, and driving our values through ML * [Preferred] 2+ years customer-facing experience in a pre-sales or post-sales role * [Preferred] Experience working with Apache Spark™ to process large-scale distributed datasets * Can meet expectations for technical training and role-specific outcomes within 3 months of hire * Can travel up to 30% when needed About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.