Applied Computing Technologies Ltd.

Applied Computing was founded in 2024 to build Orbital, a physics-informed foundation model for energy operations. We’re live across oil and gas, refineries, and petrochemicals, working towards our mission: sustainable abundance for a growing planet. The hydrocarbon industry keeps the world running. But its complexity has left operators tied to legacy systems, making critical decisions on less than 10% of available data. We built Orbital to change that. It’s a foundation model built specifically for energy that lets companies use AI at scale, harnessing all of their operational data and optimising in real time for any metric. Decisions get faster, operations get safer, and carbon intensity falls. We’ve raised over $32 million, including one of the largest seed rounds for an AI company in the UK. We’re just getting started As a Senior Full Stack Engineer on the Core AI team, you will build the platform that makes Orbital a scalable product. You will own the internal application layers, developer facing APIs, shared UI components, and integration frameworks that power every Orbital deployment. This is a product engineering role focused on building reusable systems. You will collaborate with AI research, Infra, and software teams to translate complex industrial workflows into reliable system components and intuitive user interfaces. Your work will define how users interact with Orbital across control rooms, engineering teams, and cloud-based environments. What Success Looks Like • Orbital ships with high-quality dashboards and interfaces that users rely on daily • Core APIs and services provide stable, well-documented contracts for AI, data, and automation features • Frontend and backend codebases are modular, well-structured, and easy to extend • Releases are frequent, reliable, and backed by strong CI/CD pipelines • Features scale from one deployment to many without site-specific rework or bespoke engineering Requirements • Strong software engineering fundamentals (data structures, algorithms, complexity) • Solid understanding of system design patterns and architectural trade-offs • Strong proficiency in JavaScript / TypeScript • Experience building complex applications in React or Svelte • Ability to design reusable UI components and frontend architecture • Python for APIs, orchestration, and data integration • Backend experience with Node.js, FastAPI, Express, or similar frameworks • Experience designing and maintaining API-driven systems • Experience building containerised microservices using Docker and Kubernetes • Familiarity with distributed systems and event-driven architectures • Experience with message brokers such as Kafka or RabbitMQ • Comfortable working in Linux environments for debugging and performance tuning • Hands-on experience with AWS (EKS, S3, IAM, CloudWatch, networking fundamentals) Product & Engineering Mindset • Comfortable operating in a fast-moving product environment with evolving requirements • Strong collaboration skills across AI, infra, and product teams • Bias toward reliability, resilience, and long-term maintainability • Ability to design systems that scale across customers, sites, and industrial verticals • Comfortable shipping on a bi-weekly release cadence What This Role Is Not • Not a pure frontend or UI-only role • Not infrastructure-only or DevOps-focused • Not a research or modelling role • Not a one-off project engineer; this role builds core platform primitives 1. Full Stack Product Development • Build features across the product stack: data access, backend services, APIs, and UI layers • Develop backend logic that exposes: o Time-series forecasts o Physics-based model outputs o LLM and agent outputs As stable product features - Create internal tools and workflows that support multiple engineering and operational use cases without custom deployments - Ensure all application layers meet strict standards for: o Reliability o Security o Observability o Performance Across cloud and on-prem environments 2. Platform & Microservices Architecture • Design and implement containerised microservices running in Kubernetes clusters • Create shared services and libraries that enable reuse across Orbital verticals • Define API boundaries and service contracts that allow AI and infra layers to evolve independently 3. Core Platform Engineering • Collaborate with Product, AI Research, ML Engineering, and Infra teams on: o Product requirements o Long-term platform architecture • Build interface layers that expose inference, physics-based reasoning, and optimisation as first-class platform capabilities • Implement abstractions for: o Data ingestion o Inference orchestration o Scheduling o Monitoring and health checks • Establish design patterns and engineering standards that unify the Orbital ecosystem 4. Software Engineering Excellence • Write clean, modular, maintainable code across frontend and backend systems • Set up and improve CI/CD pipelines for: o Automated testing o QA o Rapid, safe releases • Participate in code reviews and architectural discussions • Leverage modern agentic coding tools to increase velocity while maintaining correctness and readability Competitive salary and benefits Ability to work from the office or remote Employment contract in UK or India, EOR or contractor options available in other jurisdictions Exciting high traction AI product

About Applied Computing Applied Computing was founded in 2024 to build Orbital, a physics-informed foundation model for energy operations. We came out of stealth less than a year ago and have seen exceptional early traction: live deployments across oil and gas, refineries, and petrochemicals, strategic investment from industry leaders, and validation from some of the world’s most demanding operators. The hydrocarbon industry keeps the world running. But its complexity has left operators tied to legacy systems, making critical decisions on less than 10% of available data. We built Orbital to change that. It is a foundation model built specifically for energy that lets companies use AI at scale, harnessing all of their operational data and optimising in real time for any metric. Decisions get faster, operations get safer, and carbon intensity falls. We have raised over $40 million, including one of the largest seed rounds for an AI company in the UK. We are 32 people, flat structure, high autonomy. We’re just getting started. The RoleMost of our customers are extraordinary at what they do. They’ve spent decades mastering the chemistry, physics, and operational complexity of some of the most demanding industrial environments on the planet. Most of them have never used an LLM. None have deployed a multi-agentic foundation model in live operations. Orbital is not a simple tool. It does not behave like software they have used before. It reasons across data, surfaces patterns that were previously invisible,and gives operators capabilities that require a fundamentally different way of working. Getting from first deployment to daily, confident, self-directed use is a journey. This role owns that journey. As Head of Adoption, you will build and lead the function responsible for taking our customers from Orbital-curious to Orbital-obsessed. That means structured programmes, on-site presence, adult learning design, changemanagement, and an obsessive focus on one outcome: operators who trust the product, use it fluently, and advocate for it internally. The end state is not a customer who attended a training session. It is a customer who has changed how they work, who has identified other teams that should be using Orbital, and who is pushing us to build more. The PersonYou have a rare combination. You understand how adults learn new things, especially adults who are already expert in something else and have no obvious reason to change. You know that resistance to new tools is rarelyabout the tools and almost always about trust, identity, and workflow disruption.You are comfortable in industrial environments. You do not need to understand refinery chemistry, but you need to be able to sit in a control room, earn the respect of an operator who has been doing this job for twenty years,and help them see that Orbital makes them better at it, not redundant because of it.You build systems, not sessions. One-off training is not adoption. You know how to design a programme that moves people through capability stages, identifies who is ready to go further, and creates the internal momentum that means customers ask us for more without being pushed. You measure outcomes, not activity. Completion rates and attendance figures mean nothing to you. You care about daily active use, workflow integration,and whether customers are bringing new teams to the table. What Success Looks LikeDays 1-30You have spent time on-site with at least two customers. You have mapped the current state of adoption across our live accounts: who is using Orbital daily, who is using it occasionally, who has effectively stopped, and why. You have formed a clear view of the biggest adoption blockers and presented your findings to the leadership team. Days 30-90You have built the first version of the AC adoption framework: user personas, capability stages, and the programme structure that moves customers from one stage to the next. You are running the first structured adoption engagement with a customer, and you have identified at least two potentialchampions across our accounts. Months 3-6Adoption metrics are defined, tracked, and visible. At least one customer has a trained champion actively running their own internal sessions. The product team has received a structured set of adoption-derived requirements. Account management has a clearer view of which accounts are ready for expansionconversations based on adoption health. Months 6-12Adoption is a measurable, managed function. Daily active use has increased across the customer base. At least one account has expanded scope or headcount because of adoption-driven demand, not commercial pushing. Thechampion network spans multiple customers, and customers are beginning to learn from each other. We have a repeatable playbook that scales without requiring your personal presence in every account. How We Work-Flat structure. No layers of management between you and the decision. No committees for decisions that one person should own.- High autonomy, high accountability. We will not tell you how to do the job. We will care a lot whether you do it well.- Direct communication. We say what we think, including when we disagree. Feedback is fast and honest, not softened into uselessness.- This role requires real presence. You will be on customer sites regularly. That is not a nice-to-have, it is the job.- We move quickly. The adoption methodology you build in month one will be different by month six. That is expected and good. Essential Experience- Proven track record of driving technology adoption in enterprise orindustrial environments, where users were expert practitioners with noobvious motivation to change.- Experience designing and running structured change programmes, notone-off training. You understand capability staging, reinforcement, andhow to sustain momentum across months, not days.- Comfortable working with technically complex products and translatingthat complexity into accessible, role-specific learning.- Experience identifying and developing internal champions withincustomer organisations, and using those champions to drive scale.- Strong data instinct. You define adoption metrics, track them rigorously,and use them to make decisions about where to focus and when toescalate.- Confident operating at multiple levels within a customer organisation:from the operator on shift to the VP who signed the contract. Nice to Haves- Background in adult learning design or organisational changemanagement.- Experience in energy, utilities, manufacturing, or other operationalindustries where the workforce is domain-expert and change-averse.- Familiarity with AI or data product adoption specifically: the uniquechallenges of getting users to trust model outputs rather than rule-basedsystems.- Experience building customer community or champion networkprogrammes at scale. Key Responsibilities 1. Adoption Strategy and Programme Design-Build and own Applied Computing’s adoption methodology: the structured path from first deployment through operational fluency to customer champion. - Design adoption programmes for different user personas: front-line operators, process engineers, plant managers, and executive sponsors. Each group has different needs, different blockers, and a different definition of value.-Create the tools, materials, and frameworks that make adoption repeatable across customers, industries, and deployment types.-Define what AI-native looks like for an energy operator and build the curriculum that gets them there.2. Customer Engagement and Change Management-Lead on-site adoption engagements with customers. Be present in the environments where Orbital runs. Understand the day-to-day reality of the people we are asking to change how they work.- Work with customer stakeholders to build internal buy-in: identifying sponsors, surfacing quick wins, and creating the internal narrative that sustains momentum after we leave.- Navigate resistance. Recognise the difference between technical blockers and human ones, and address both without conflating them.- Partner with forward deployed engineers and delivery teams to ensure adoption programmes are sequenced correctly alongside technical deployment.3. Champion Development- Identify and invest in the operators and engineers within customer organisations who have the curiosity and influence to become Orbital champions.- Build a structured programme that takes champions from power user to internal advocate: someone who runs their own sessions, brings new colleagues to the product, and escalates expansion opportunities.- Build a cross-customer champion network over time. Customers learning from customers is more powerful than us telling them what is possible.- Track champion progress and use it as a leading indicator of account health and expansion readiness. 4. Adoption Measurement - Define the metrics that actually measure adoption: daily active users, workflow completion rates, feature depth, session frequency, and self-directed use versus prompted use.- Build visibility of these metrics across the business. Adoption health should be as visible as pipeline and ARR.- Use adoption data to identify at-risk accounts early, before it becomes a commercial problem.- Feed adoption patterns back into product and engineering: what is consistently hard to learn, what features are never used, what workflows are being improvised around. 5. Feedback Loop to Product and Commercial- Translate adoption blockers into specific, evidenced product requirements. If customers consistently struggle with the same thing, that is a product problem.- Work with account management and commercial leadership to identify expansion signals. A customer who has three champion-level users and two new teams asking questions is a customer ready for a biggerconversation.- Contribute to onboarding documentation, in-product guidance, and any materials that extend the adoption programme beyond direct engagement. What This Role Is Not- A customer success role. You are not managing commercial relationships, handling renewals, or owning account health from a revenue perspective.- A training function. Delivering workshops and tracking attendance is not this job. This role exists to change behaviour, not to run sessions.- A support function. You are not the escalation point for technical issues or bug reports.- A consultancy. You are not doing the work for customers. You are building their capability to do it themselves.- A content production role. You will create materials, but you are primarily in the field, not at a desk writing e-learning modules. Benefits- Competitive salary benchmarked at the 90th percentile for the role,level, and location.- Meaningful equity. We are pre-Series A and growing fast.- 28 days holiday including bank holidays.- Private health insurance.- Remote-first with a London hub for collaboration.- Direct access to the founding team and a front-row seat to building oneof the most technically ambitious AI companies in Europe.

About Applied Computing Applied Computing was founded in 2024 to build Orbital, a physics-informedfoundation model for energy operations. We came out of stealth less than ayear ago and have seen exceptional early traction: live deployments across oiland gas, refineries, and petrochemicals, strategic investment from industryleaders, and validation from some of the world’s most demanding operators. The hydrocarbon industry keeps the world running. But its complexity has leftoperators tied to legacy systems, making critical decisions on less than 10% ofavailable data. We built Orbital to change that. It is a foundation model built specifically forenergy that lets companies use AI at scale, harnessing all of their operationaldata and optimising in real time for any metric. Decisions get faster, operationsget safer, and carbon intensity falls. We have raised over $40 million, including one of the largest seed rounds foran AI company in the UK. We are 32 people, flat structure, high autonomy.We’re just getting started. The RoleOrbital is a technically groundbreaking product deployed in some of the mostcomplex industrial environments on the planet. The science is proven and theresults are real. What we need now is someone who can make it exceptional touse. As Head of Product, you will own the end-to-end product experience: what webuild, how it behaves, how operators interact with it day-to-day, and how weevolve it as we scale. You will work directly with our CAIO and engineeringleadership to turn deep technical capability into software that peoplegenuinely love using. You do not need to arrive knowing the difference between a CCR unit and ahydrocracker. We will teach you the domain. What you must bring is relentlessproduct craft: an obsession with usability, a sharp instinct for what matters tothe person in front of the screen, and the discipline to ship things that workrather than things that look good on a roadmap. This role is for someone who has already built products that people did notjust use, they preferred. Who has made complex workflows feel simple. Whogets frustrated when good technology is buried under bad UX. Whounderstands that adoption is a product problem, not a training problem. The PersonYou are a product obsessive. Not a roadmap manager, not a process owner.Someone who genuinely cares whether the interface in front of an operator at3am in a refinery control room is clear, fast, and trustworthy.You read user behaviour, not just user feedback. You know that what peoplesay they want and what they actually need are often different things, and youhave the tools and instincts to close that gap. You can hold a rigorous conversation with a PhD-level Ai Researcher aboutmodel behaviour and then walk out and translate that into a product decisiona plant operator will understand. You are comfortable being the bridge. You move quickly, make decisions with incomplete information, and changeyour mind when the evidence demands it. You do not wait for consensus. Youbuild things, watch what happens, and improve them. Key Responsibilities1. Product Strategy and Roadmap-Own the Orbital product roadmap from strategy through to delivery,working closely with our CAIO and engineering leads.-Define and prioritise what we build next based on customer usage,deployment feedback, and commercial opportunity.-Translate operator workflows and energy industry problems intoconcrete product decisions without needing those problems explainedtwice.-Make the hard calls on what we do not build, as ruthlessly as the calls onwhat we do. 2. User Experience and Usability- Own the end-to-end user experience across Orbital: dashboards, alerts,investigation workflows, configuration, and reporting.- Establish and enforce usability standards. If something takes too manyclicks, too much training, or too much explanation, it is not finished.- Build a feedback loop with operators and engineers in the field. Fly outto customer sites. Sit in control rooms. Watch people use the product.- Work with design and engineering to produce interfaces that feel fast,clear, and reliable in high-stakes industrial environments. 3. Discovery and Customer Insight- Run structured discovery with existing customers and prospects toidentify product gaps, friction points, and expansion opportunities.- Synthesise usage data, customer calls, and field observations into clearproduct direction.- Partner with forward deployed engineers and delivery teams to capturewhat is working and what is not, in production.- Feed commercial intelligence back into product decisions: what isblocking sales, what is driving expansion, what is causing churn. 4. Delivery Partnership- Work with engineering to define clear acceptance criteria, scopeboundaries, and launch standards.- Maintain a relentless focus on shipping. A perfect spec that ships late isnot better than a good spec that ships now.- Own the product launch process: internal alignment, customercommunication, documentation, and adoption tracking.- Measure what you ship. Track feature adoption, workflow completion,time-to-value, and usage depth. If you built it and nobody used it, thatmatters. 5. Platform Thinking- Orbital runs across cloud, edge, and partner-native environmentsincluding Databricks and AWS. Product decisions must account fordeployment context.- As we expand into new industry verticals and use cases, help definehow the product scales: what is core, what is configurable, what isbespoke.- Contribute to product positioning and packaging decisions alongsidecommercial leadership. What This Role Is Not- A project management role. You are not here to run sprints, manage Jiraboards, or chase engineers for status updates.- A customer success role. You care about customers, but your job is tobuild the product, not to manage the relationship.- A design role. You will have opinions on UX and you will need to guidedesign quality, but you are not the designer.- A committee. You will consult widely but you will decide. If everyproduct decision requires five sign-offs, you are doing it wrong.- A domain expert role. We are not hiring someone who already knowsenergy. We are hiring someone who already knows product. Essential Experience- Demonstrable track record of shipping software products that usersconsistently praised for ease of use and clarity.- Experience working on complex B2B or enterprise software withtechnically sophisticated end users (engineers, analysts, operators, orequivalent).- Able to read and act on product usage data. You have built and useddashboards, funnels, and behavioural analytics to make productdecisions.- Experience working directly with ML or AI engineering teams, and aworking understanding of how model-driven products behavedifferently from rule-based ones.- Comfortable representing the product to customers, prospects, andinvestors. You can demo the product, explain the roadmap, and handlehard questions without preparation.- Minimum five years in a product role, with at least two in a senior orlead position owning a full product area. Nice to Haves- Exposure to industrial, operational technology, or engineering softwareproducts.- Experience building products that run in constrained or specialistenvironments (edge, embedded, or regulated).- Background working in or with energy, utilities, manufacturing, orprocess industries.- Familiarity with data-heavy interfaces: time series visualisation,