applied ai engineer

Dentons

<div>
 
 
 Department/Division
 
 : Solutions/Innovation
 
 
 
 Duration
 
 : Permanent
 
 
 
 Type of Role
 
 : Hybrid
 
 
 
 Reference Number
 
 : 10203
 
 
 
 
 
 
 The Team
 
 
 
 
 
 
 The Innovation &amp; AI team sits within the Solutions function and is responsible for identifying, developing and scaling innovative solutions, including AI and legal technology, to enhance client service delivery and internal efficiency.
 
 
 
 
 
 The team works closely with IT, Office of the General Counsel (OGC), Procurement, Solutions/Helix and Practice Groups to pilot, implement and embed new tools and ways of working across the firm.
 
 
 
 
 
 
 The Role
 
 
 
 
 
 
 The Applied AI Engineer designs, builds and productionises AI-enabled solutions for legal and business services delivery. Working consultatively with stakeholders and delivery teams, the role translates use cases into technical designs across Python applications, cloud workflows, enterprise platforms, AI skills, agents, integrations and automations.
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 
 <ul>
 <li>
 Design, build and maintain AI-enabled applications, automations and internal tools using Python, cloud services and enterprise platforms.
 </li>
 <li>
 Work with stakeholders to understand business problems, assess use cases and translate requirements into practical technical designs.
 </li>
 <li>
 Build integrations between internal systems, enterprise platforms, external applications and AI services.
 </li>
 <li>
 Develop reusable AI skills, agents, workflow components and automation patterns that can be adopted across the firm.
 </li>
 <li>
 Build document-focused AI workflows, including extraction, summarisation, search, retrieval and due diligence support.
 </li>
 <li>
 Productise AI pilots by improving reliability, maintainability, testing, evaluation, documentation and reuse.
 </li>
 <li>
 Design and implement multi-step AI workflows, including tool-using, agentic and platform-native automations where appropriate.
 </li>
 <li>
 Collaborate with product, UX, engineering, cloud, innovation and business teams to deliver secure, production-ready solutions.
 </li>
 <li>
 Apply sound engineering judgement around confidential client data, privacy, security, governance and responsible AI.
 </li>
 </ul>
 
 
 
 
 
 Key Skills &amp; Experience
 
 
 
 
 
 <ul>
 <li>
 Python software engineering experience across applications, integrations, automations or internal tools.
 </li>
 <li>
 Experience building or implementing AI/ML or LLM-enabled solutions in production or near-production settings.
 </li>
 <li>
 Experience working with APIs, SDKs, cloud services and enterprise platforms.
 </li>
 <li>
 Practical understanding of prompt engineering, RAG, LLM workflows or agentic patterns.
 </li>
 <li>
 Ability to interview stakeholders and translate business processes into technical designs.
 </li>
 <li>
 Experience with testing, debugging, documentation, Git and maintaining reliable systems.
 </li>
 <li>
 Strong communication and problem-solving skills across technical and non-technical audiences.
 </li>
 </ul>
 
 
 
 
 
 Preferred:
 
 
 
 
 
 <ul>
 <li>
 Experience within a legal, professional services or other document-intensive enterprise environment.
 </li>
 <li>
 Familiarity with document processing pipelines, unstructured data workflows or knowledge retrieval systems.
 </li>
 <li>
 Experience with orchestration frameworks, agents, skill-building frameworks or workflow automation tools.
 </li>
 <li>
 Experience building on enterprise AI platforms or comparable environments.
 </li>
 <li>
 Exposure to governance, security, privacy and responsible AI considerations in enterprise environments.
 </li>
 </ul>
 
 
 
 
 
 Personal Attributes
 
 
 
 
 
 <ul>
 <li>
 Pragmatic and delivery-focused, with the ability to turn ambiguous ideas into working solutions.
 </li>
 <li>
 Consultative and curious, able to ask good questions and challenge assumptions constructively.
 </li>
 <li>
 Collaborative and comfortable working across multidisciplinary teams.
 </li>
 <li>
 Adaptable in a fast-moving environment where requirements and technologies evolve.
 </li>
 <li>
 Clear communicator who can explain technical concepts to non-technical stakeholders.
 </li>
 </ul>
 
 
 
 
 
 Firm Profile
 
 
 
 Across more than 80 countries, Dentons helps you grow, protect, operate and finance your organisation by providing uniquely global and deeply local legal solutions. Polycentric, purpose-driven and committed to inclusion, diversity, equity and sustainability, we focus on what matters most to you. www.dentons.com
 
 
 
 
 
 
 Inclusion and Diversity
 
 
 
 We are committed to building an inclusive culture here at Dentons where our people can thrive, regardless of their background or circumstance. As well as being the right thing to do, it makes good business sense too. A richness of backgrounds, experiences and perspectives helps us best serve our clients and the communities in which we operate. You can find out more about inclusion and diversity at Dentons here: Inclusion and Diversity
 
 
 
 
 
 Dentons is committed to providing equal opportunities for all. We welcome applications from everyone including of any age, ethnicity, religion, sex, sexual orientation, gender identity, nationality, neurotype, disability, or with parental or caring responsibilities. We are also &ldquo;Happy to Talk Flexible Working&rdquo; and welcome conversations about flexible working arrangements.
 
 
 
 
 
 Dentons is a Disability Confident employer. Candidates with a disability may choose to apply under the Disability Confident Scheme. We will offer an interview to disabled applicants who meet the minimum criteria for the role. Where application volumes are high, we may offer interviews to those who best meet the minimum criteria, consistent with our approach for all candidates.
 
 
 
 
 
 During the application process, all applicants have the opportunity to tell us about any adjustments or support they require so they are able to perform at their best. Any information you share with us during the application process is treated in confidence.
 
 
 
 
 
 If you have any questions about this or the role criteria, please email recruitment.matters@dentons.com.
 
 
 
 
 
 
 NO AGENCIES PLEASE
 
 
 
 If you are interested in applying for this position, we welcome direct applications via our careers page, but if you have any questions beforehand, please email recruitment.matters@dentons.com. Enquiries only please &ndash; applications will not be accepted via email.
 
 
 
 
 
 Please note that we will not accept unsolicited CVs sent to the business, nor will we accept any associated terms of business.
 
</div>

Applied AI Engineer

Lorien

<div>
 
 AI Solutions Engineer / Applied AI Engineer
 
 
 Location: London (Hybrid) 3 days onsite
 
 
 Perm
 
 
 Cheapside, London EC2V 6EE
 
 
 
 
 
 Criteria:
 
 
 &bull; AI-Native Engineering Practice
 
 
 &bull; Software Engineering Experience
 
 
 &bull; Databricks and Python Proficiency
 
 
 &bull; Functional Empathy and Stakeholder Engagement
 
 
 &bull; Solution Ownership and Quality
 
 
 
 
 
 We&rsquo;re looking for engineers who are not only deeply technical in AI but also excellent communicators and stakeholder partners.
 
 
 
 
 
 Some engineers love technology for technology&rsquo;s sake. This role is different. At HeadFirst x Impellam, we&rsquo;re looking for someone who enjoys figuring things out, understands how organizations work, and gets a kick out of building solutions that genuinely improve the day-to-day reality of teams across the business.
 
 
 
 
 
 As an Applied AI Engineer, you work directly with departments such as Finance, HR, Sales, and Marketing to streamline processes, eliminate friction, and help people work smarter through AI, automation, and lightweight internal applications. You aren&rsquo;t expected to be an expert in every framework, platform, or tool from day one. What matters more is how you think, how quickly you learn, and how effectively you turn ambiguity into practical results.
 
 
 This is a high-profile role that makes a real difference to the business. You&rsquo;ll spend just as much time understanding workflows, challenging assumptions, and shaping solutions as you do building them. The people who thrive here are curious, pragmatic, and comfortable working closely with stakeholders rather than hiding behind tickets or isolated engineering backlogs.
 
 
 Your impact
 
 
 
 
 
 As an Applied AI Engineer, you&rsquo;ll serve as a consultant, a builder, and a problem solver all in one. You&rsquo;ll work closely with business teams to understand how work actually gets done. Sometimes the challenge is operational inefficiency. Sometimes it&rsquo;s fragmented tools, repetitive manual work, or slow decision-making caused by disconnected systems and unclear information flows.
 
 
 Your role is to identify where AI, automation, or lightweight applications can deliver immediate value, and then help bring that value to life quickly and pragmatically. Rather than spending months designing perfect systems, you focus on delivering usable solutions quickly, gathering feedback early, and improving continuously. This could involve building an internal workflow tool, creating an AI-powered assistant for operational teams, or streamlining reporting and approvals through automation.
 
 
 
 
 
 You work within a modern Databricks and AI-enabled ecosystem, but technology is never the end goal. The real objective is to help teams operate more effectively, make better decisions, and eliminate operational bottlenecks. AI plays a central role in how you work. AI coding assistants and agent-based workflows help accelerate development and experimentation, allowing you to move quickly while still maintaining control over quality, usability, and adoption.
 
 
 At the same time, you work closely with the Platform, Data, and Engineering teams to ensure that the solutions you deliver fit within a scalable and secure organizational environment.
 
 
 
 
 
 What you will do
 
 
 &bull; Work closely with business stakeholders to understand operational challenges, workflows, and inefficiencies;
 
 
 &bull; Translate ideas and business needs into practical tools, automations, and AI-powered solutions;
 
 
 &bull; Build lightweight internal applications that boost productivity and simplify daily work;
 
 
 &bull; Use AI coding assistants and AI-native workflows to speed up delivery and experimentation;
 
 
 &bull; Continuously refine solutions based on real user feedback and adoption;
 
 
 &bull; Support teams in improving processes rather than simply digitizing existing inefficiencies;
 
 
 &bull; Collaborate with Finance, HR, Commercial, and leadership teams on business-critical initiatives;
 
 
 &bull; Balance speed and quality by making pragmatic engineering decisions that maintain momentum;
 
 
 &bull; Introduce smarter workflows through automation, AI agents, and integrated internal tools;
 
 
 &bull; Help shape how AI is adopted responsibly and practically throughout the organization;
 
 
 &bull; Share ideas, best practices, and suggestions for improvement that help teams move faster and work more effectively.
 
 
 
 
 
 Who you are
 
 
 You&rsquo;re someone who enjoys solving problems in complex, real-world environments. You likely combine technical curiosity with strong communication skills and a genuine interest in how businesses operate. You don&rsquo;t need perfect requirements or fully defined roadmaps to get started. Instead, you ask questions, explore possibilities, and move toward solutions quickly. You&rsquo;re energized by learning new things and comfortable adapting as technology evolves. AI doesn&rsquo;t intimidate you. You see it as a practical tool that helps you think faster, build faster, and create more impact.
 
 
 You enjoy collaborating and are comfortable working closely with non-technical stakeholders. You know how to explain ideas clearly, challenge assumptions constructively, and maintain momentum without overcomplicating things. Most importantly, you care about results. You enjoy delivering useful solutions, seeing people adopt them, and improving them over time based on what works in practice.
 
 
 
 
 
 Why this role stands out
 
 
 This is not a traditional engineering role focused solely on technical implementation. You will work closely with decision-makers, influence how teams operate, and help shape the practical implementation of AI across an international organization. The role combines engineering, consulting, problem-solving, and business collaboration in a way that offers broad exposure and a tangible impact.
 
 
 If you enjoy fast-paced environments, practical innovation, and building solutions that people actually use, this role offers the opportunity to have a direct impact on how modern AI capabilities create value within a global business.
 
</div>

AI Solutions Engineer / Applied AI Engineer

Accenture

<div><h2 class="jobSectionHeader">Description</h2>
You build the systems that actually make AI work in enterprise environments, not demos, not prototypes that stall after a pilot, but production agentic architectures running inside real client organizations. The difference between an AI Engineer and what we are looking for is straightforward: you have shipped a multi-agent system in production, you have owned the eval harness, and you know what happens when your agent fails at 2am because you have lived it.
As an AI Engineer (Agentic/Applied), you will design, build, and deploy production-grade agentic AI systems across the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagements.
This sits at the heart of the AI engineering talent market, demand is growing faster than supply and will continue to do so. We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity, combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme.<h2 class="jobSectionHeader">
Key Responsibilities</h2><ul><li>
Design and build production-grade agentic systems end-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability</li><li>
Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning against real quality targets</li><li>
Integrate and abstract across multiple LLM providers &mdash; OpenAI, Anthropic, Vertex AI, and open-source models &mdash; with fallback routing, token, cost, and latency management</li><li>
Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring</li><li>
Embed directly with client engineering teams to design, prototype, and deploy agentic solutions &mdash; workshops, proofs of concept, code-with sessions, and architecture walkthroughs</li><li>
Build reusable patterns, accelerators, and playbooks that scale beyond the individual client engagement and enable the next one to start faster</li><li>
Define and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness; present findings and recommendations to client stakeholders in business terms</li></ul></div>
 
<div><h2 class="jobSectionHeader">Basic Qualifications</h2><ul><li>
5+ years of software engineering experience in production environments</li><li>
Minimum 1 year of hands-on experience designing and deploying agentic AI solutions in a production environment &mdash; non-negotiable</li><li>
Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent &mdash; at production depth, not tutorial level</li><li>
Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs</li><li>
RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering</li><li>
LLMOps fundamentals: eval harness design, prompt versioning, and production observability</li><li>
Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm)</li><li>
Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience</li><li>
Quality of experience is weighted over years, a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure</li></ul></div>

AI Native SW Engineering Specialist

Google

<div><h3 class="jobSectionHeader">Minimum qualifications:</h3><ul>
<li>Bachelor&rsquo;s degree or equivalent practical experience. 
</li>
<li>2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree. 
</li>
<li>1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).</li>
<li>1 year of experience with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.</li>
<li>Experience with core GenAI concepts (e.g., LLM, Multi-Modal, Large Vision Models) and text, image, video, or audio generation.</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>Master's degree or PhD in Computer Science or a related technical field.</li>
<li>2 years of experience with data structures and algorithms.</li>
<li>Experience in solving customer problems by navigating ambiguous requirements to deliver effective technical solutions and tangible business outcomes.</li>
<li>Experience in Vertex AI, BigQuery, Cloud Storage, Dialogflow.</li>
<li>Experience in prompt development, model evaluation, and the creative application of Artificial Intelligence (AI).</li>
<li>Ability to be flexible and resilient in dynamic environmentsto take ownership and respond to urgent business or customer issues.</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

In this role, you will be at the forefront of applying Google's Generative AI to solve real-world issues for our customers. You will act as a specialized software developer embedded with key accounts, working to build, deploy, and optimize sophisticated AI agents on our customer engagement suite (CES) platform. You will bridge the gap between our core product engineering teams and customer needs, directly accelerating customer success and shaping the future of our AI products.
The Cloud Applied AI (AAI) powers business growth with Gemini Enterprise. Our portfolio includes Gemini Enterprise for Customer Experience (Shopping Agent, CX Agent Studio, Agent Assist, Vertex AI Search - Commerce, Customer Experience Insights), along with other vertical and domain packaged solutions. We enable high adoption and speed to value by building solutions that are quickly deployed, delivering new 0-to-1 capabilities with startup agility. Team members operate at the forefront of AI, collaborating directly with model builders with unprecedented speed. Join us to work on cutting-edge projects and shape the future of AI in a fast-paced, collaborative, and impactful environment.</div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Partner directly with select, customers to understand their business issues. Design, co-develop, debug, and deploy custom conversational AI agents and solutions to accelerate their time to value.</li>
<li>Act as a high-level problem solver, empowered to write bespoke code, develop custom tooling, and contribute directly to the core product codebase to resolve critical customer issues. 
</li>
<li>Be able to systematize your learnings from customer engagements by creating reusable tools, building documentation and accelerators, and establishing best practices that can be used across the organization. 
</li>
<li>Serve as a critical feedback loop to our core Product and Engineering teams. Synthesize firsthand insights from the field to influence product strategy and identify gaps. 
</li>
<li>Act as a subject matter expert, providing technical guidance and best practices to customers on agent improvement, performance tuning, CI/CD pipelines, and production readiness.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Software Engineer, Agent Building, Applied AI, Google Cloud Platform

Voxquill

<div>I'm looking for our founding engineer!
 
The person who takes a live, paying fintech product and makes it truly ours.
We build receipt-and-proof automation for the self-employed: the app quietly finds your receipts (email, bank feeds, camera roll, texts), sorts them, matches them to your bank transactions, and produces accountant-ready exports. It's live on iOS and Android, it's SOC 2 certified, and people are paying for it. The model works.
I need one person who treats this codebase as theirs, ships fast, and owns the platform end-to-end. This is a founding engineer role with a real path to CTO.
Your first job is to take the keys.
 
Move the platform off the agency's Azure into ours, take custody of production, and the headline deliverable.
 
Build the automated test suite this codebase never had, with a CI/CD pipeline where a green build genuinely means &quot;safe to ship.&quot; Then you own the roadmap.
How we build matters as much as what we build.
 
We are not rebuilding an IT shop of tickets and manual QA.
 
Terrapin runs as an AI-native pod: Claude Code and agents do the repetitive work and produce tested, PR-ready changes; you own architecture, review, security, and the hard 20%.
 
AI gives you the velocity, your tests and pipeline are what keep that velocity from turning into breakage!
We want to ship multiple times a week and almost never break anything, and hold our SOC 2 line the whole way. If that model excites you rather than worries you, you're the person.
This is genuinely full-stack.
 
Strong .NET / C# backend on Azure, real ownership of infra, security, and DevOps, and polished mobile (React Native + Expo, iOS and Android); Because the app is the product. Testing isn't someone else's job here. It's the core discipline.
The kind of person whose teammates would describe as:<ul><li>
an owner, not a ticket-taker</li><li>
obsessive about shipping quality fast</li><li>
calm owning production for a product with real money moving through it</li><li>
someone who builds automation instead of doing the same thing twice</li><li>
security-minded by instinct, not as an afterthought</li></ul>
What you'd bring:<ul><li>
Senior+ .NET / C# backend, PostgreSQL, solid API design</li><li>
Real Azure ownership: App Services, networking, Key Vault, identity, CI/CD (Azure DevOps or similar)</li><li>
Strong React Native + Expo mobile, with genuine UI/UX taste</li><li>
Test automation and CI/CD as a way of life &mdash; you write the tests with the code</li><li>
Hands-on building with Claude Code / agent tooling, and doing it safely in a SOC 2 world</li></ul>
Bonus points: fintech / payments background, Plaid experience, or applied LLM work.
And the reason the right engineer will actually stay: receipts are just the wedge. We're building toward a verifiable, tamper-evident record of an economic event. Proof that banks, insurers, and AI agents can consume directly. Stripe is a payment rails. We're building proof rails.
You'd work directly with me every day &mdash; 18+ years in fintech and payments, two exits behind me &mdash; so you own the engineering but never carry the hard architecture, security, or product calls alone.
The details:
 
UK or EU-remote(temporarily), with solid overlap to UK hours and business trips.
We're genuinely open to strong candidates across both. Being open to relocating to the UK down the line is a plus, but not a day-one requirement.
 
Competitive base plus real founding-level equity.
One hard line: you build quality in through tests and CI/CD. We're deliberately leaving the manual-testing, hope-it-works world behind, and a dev who treats testing as optional isn't the hire. Everything else, we can talk about.
If you want founder-level ownership, a CTO trajectory, and an AI-native way of building, and owning a live fintech platform from week one lights you up, let's talk.
Apply and tell me about something you shipped that you're proud of, and one thing you broke and how you made sure it never happened again.</div>

Founding Engineer (Full Stack); Patch to CTO

<div><h3 class="jobSectionHeader">Minimum qualifications:</h3><ul>
<li>Bachelor&rsquo;s degree or equivalent practical experience. 
</li>
<li>5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.</li>
<li>5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field. 
</li>
<li>5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>Master&rsquo;s degree or PhD in Engineering, Computer Science, or a related technical field. 
</li>
<li>5 years of experience with data structures and algorithms.</li>
<li>3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google&rsquo;s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

In this role, you will be at the forefront of applying Google's Generative AI to solve real-world issues for our customers. You will act as a specialized software engineer embedded with key accounts, working to build, deploy, and optimize sophisticated AI agents on our Customer Engagement Suite (CES) platform. You will bridge the gap between our core product developing teams and customer needs, directly accelerating customer success and shaping the future of our AI products.
The Cloud Applied AI (AAI) powers business growth with Gemini Enterprise. Our portfolio includes Gemini Enterprise for Customer Experience (Shopping Agent, CX Agent Studio, Agent Assist, Vertex AI Search - Commerce, Customer Experience Insights), along with other vertical and domain packaged solutions. We enable high adoption and speed to value by building solutions that are quickly deployed, delivering new 0-to-1 capabilities with startup agility. Team members operate at the forefront of AI, collaborating directly with model builders with unprecedented speed. Join us to work on cutting-edge projects and shape the future of AI in a fast-paced, collaborative, and impactful environment.</div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Partner directly with customers to understand their business issues. Design, co-develop, debug, and deploy custom conversational AI agents and solutions to accelerate their time to value.</li>
<li>Systematize learnings from customer engagements by creating reusable tools, building documentation and accelerators, and establishing best practices across the organization.</li>
<li>Act as a high-level problem solver, empowered to write bespoke code, develop custom tooling, and even contribute directly to the core product codebase to resolve critical customer issues. 
</li>
<li>Lead the design and implementation of solutions in specialized ML areas, optimize ML infrastructure, and guide the development of model optimization and data processing strategies. 
</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Software Engineer, Applied AI, Agent Building, Google Cloud Platform

Applied Computing

<div>Applied Computing was founded in 2024 to build Orbital, a physics-informed foundation model for energy operations. We&rsquo;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&rsquo;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&rsquo;ve raised over $32 million, including one of the largest seed rounds for an 
AI company in the UK. We&rsquo;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<ul><li>Orbital ships with high-quality dashboards and interfaces that users rely on daily</li><li>Core APIs and services provide stable, well-documented contracts for AI, data, and automation features</li><li>Frontend and backend codebases are modular, well-structured, and easy to extend</li><li>Releases are frequent, reliable, and backed by strong CI/CD pipelines</li><li>Features scale from one deployment to many without site-specific rework or bespoke</li></ul>
engineering<div>
Requirements 
<ul><li>Strong software engineering fundamentals (data structures, algorithms, complexity)</li><li>Solid understanding of system design patterns and architectural trade-offs</li><li>Strong proficiency in JavaScript / TypeScript</li><li>Experience building complex applications in React or Svelte</li><li>Ability to design reusable UI components and frontend architecture</li><li>Python for APIs, orchestration, and data integration</li><li>Backend experience with Node.js, FastAPI, Express, or similar frameworks</li><li>Experience designing and maintaining API-driven systems</li><li>Experience building containerised microservices using Docker and Kubernetes</li><li>Familiarity with distributed systems and event-driven architectures</li><li>Experience with message brokers such as Kafka or RabbitMQ</li><li>Comfortable working in Linux environments for debugging and performance tuning</li><li>Hands-on experience with AWS (EKS, S3, IAM, CloudWatch, networking fundamentals)</li></ul></div><div> 
Product &amp; Engineering Mindset 
<ul><li>Comfortable operating in a fast-moving product environment with evolving</li></ul>
requirements 
<ul><li>Strong collaboration skills across AI, infra, and product teams</li><li>Bias toward reliability, resilience, and long-term maintainability</li><li>Ability to design systems that scale across customers, sites, and industrial verticals</li><li>Comfortable shipping on a bi-weekly release cadence</li></ul></div><div> 
What This Role Is Not 
<ul><li>Not a pure frontend or UI-only role</li><li>Not infrastructure-only or DevOps-focused</li><li>Not a research or modelling role</li><li>Not a one-off project engineer; this role builds core platform primitives</li></ul></div><div>
1. Full Stack Product Development 
<ul><li>Build features across the product stack: data access, backend services, APIs, and UI</li></ul>
layers 
<ul><li>Develop backend logic that exposes:</li></ul>
o Time-series forecasts 
o Physics-based model outputs 
o LLM and agent outputs 
As stable product features</div><ul><li>
Create internal tools and workflows that support multiple engineering and operational use cases without custom deployments</li><li>
Ensure all application layers meet strict standards for:</li></ul>
o Reliability 
o Security 
o Observability 
o Performance 
Across cloud and on-prem environments<div> 
2. Platform &amp; Microservices Architecture 
<ul><li>Design and implement containerised microservices running in Kubernetes clusters</li><li>Create shared services and libraries that enable reuse across Orbital verticals</li><li>Define API boundaries and service contracts that allow AI and infra layers to evolve</li></ul>
independently</div><div>
3. Core Platform Engineering 
<ul><li>Collaborate with Product, AI Research, ML Engineering, and Infra teams on:</li></ul>
o Product requirements 
o Long-term platform architecture 
<ul><li>Build interface layers that expose inference, physics-based reasoning, and optimisation</li></ul>
as first-class platform capabilities 
<ul><li>Implement abstractions for:</li></ul>
o Data ingestion 
o Inference orchestration 
o Scheduling 
o Monitoring and health checks 
<ul><li>Establish design patterns and engineering standards that unify the Orbital ecosystem</li></ul></div><div> 
4. Software Engineering Excellence 
<ul><li>Write clean, modular, maintainable code across frontend and backend systems</li><li>Set up and improve CI/CD pipelines for:</li></ul>
o Automated testing 
o QA 
o Rapid, safe releases 
<ul><li>Participate in code reviews and architectural discussions</li><li>Leverage modern agentic coding tools to increase velocity while maintaining</li></ul>
correctness and readability</div>
Benefits
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</div>

Staff Software Engineer

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