machine learning engineer

data engineer

ai engineer

senior software engineer

software engineer

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

Percepta

<div>
 
 Who We Are
 
 
 
 Percepta&rsquo;s mission is to
 
 transform critical institutions with applied AI.
 
 We care that industries that power the world (e.g. healthcare, manufacturing, energy) benefit from frontier technology.
 
 
 To make that happen, we embed with industry-leading customers to drive AI transformation. We bring together:
 
 
 <ul>
 <li>
 Forward-deployed expertise in engineering, product, and research
 </li>
 <li>
 Mosaic, our in-house toolkit for rapidly deploying agentic workflows
 </li>
 <li>
 Strategic partnerships with Anthropic, McKinsey, AWS, companies within the General Catalyst portfolio, and more
 
 
 </li>
 </ul>
 Our team is a quickly growing group of Applied AI Engineers, Embedded Product Managers and Researchers motivated by diffusing the promise of AI into improvements we can feel in our day to day lives.
 
 
 Percepta is a direct partnership with General Catalyst, a global transformation and investment company.
 
 
 
 About The Role
 
 
 
 We&rsquo;re hiring
 
 Applied AI Engineers
 
 who will work directly with customer executives, operators, and technical teams to define and deliver high-impact AI systems. We are excited to build out our European presence, and you will be on the front lines of helping to define our strategy and success in the region. We don't build prototypes or laboratory projects- you&rsquo;ll design, build, and ship production-grade AI agents and workflows that drive millions in business value for customers.
 
 
 
 Our Applied AI Engineers
 
 
 
 <ul>
 <li>
 Shape the AI vision: Collaborate with customer stakeholders to define their long-term AI strategy and transformation roadmap.
 </li>
 <li>
 Identify high-leverage use cases: Work backwards from the long-term vision to surface and prioritize specific AI applications that connect our ambition to measurable business value.
 </li>
 <li>
 Ship real products: Rapidly build and deploy AI solutions that work in the wild, with real users and real data.
 </li>
 <li>
 Advance our core product: Encode the lessons from our customer engagements in our Mosaic product, consistently contributing new features, patterns, and abstractions.
 
 
 </li>
 </ul>
 
 What We&rsquo;re Looking For
 
 
 
 <ul>
 <li>
 AI-nativeness: You're excited about the potential for AI to transform businesses and want to play a hands-on role in bringing frontier technology into critical institutions.
 </li>
 <li>
 Being generative and collaborative: You love constantly jamming on new &ldquo;what if&rdquo; ideas with teammates and partners.
 </li>
 <li>
 Extreme ownership: You&rsquo;re willing to jump in and love being the one on the hook. You aren&rsquo;t going to wait to be pointed at a task&mdash;you&rsquo;re going to identify what you think we should do next, and then do it.
 </li>
 <li>
 Execution excellence and speed: You can build stuff in messy environments and know how to get code written and shipped quickly. You can hold the balance of speed and quality and know when to push the pace vs. when to slow down.
 </li>
 <li>
 Customer-obsession and respect: You&rsquo;re motivated by understanding customer pain points and iterating directly with end users to deliver wins quickly.
 
 
 </li>
 </ul>
 
 Bonus if you have
 
 
 
 <ul>
 <li>
 Hands-on experience with LLM tooling (LangGraph, Mastra, Agents SDK, etc).
 </li>
 <li>
 Built and deployed production LLM-powered systems (tool use, RAG pipelines, multi-step agents, human-in-the-loop, etc).
 </li>
 <li>
 Strong technical foundations in Python/TypeScript, cloud deployment (AWS/GCP/Azure) and DevOps tooling.
 </li>
 <li>
 Prior startup or founding engineer experience, balancing craft, ownership, and speed.
 
 
 </li>
 </ul>
 We&rsquo;re working against an incredibly ambitious mission. It won&rsquo;t be easy, but it will likely be the most fulfilling work of your career. If this excites you, let's chat, even if you don't meet all of the qualifications above.
 
 
 
 Our Values
 
 
 
 
 Dream bigger:
 
 We have the unique privilege of taking on the most ambitious problems and we should chase them with optimism, responsibility, and genuine belief that we can make it happen. We have to embrace the hard things when no one else will.
 
 
 
 Heart in the game:
 
 What we're doing matters and we have to give a shit. Internally, that means fixing badness when you find it. Externally, it means honoring the trust our customers place in us with their most important problems. This isn&rsquo;t a 9-5, nor is it a job we&rsquo;re ever going to monitor your hours. We promise to put work in front of you that matters and in return, we ask you to promise to care.
 
 
 
 Win for the customer:
 
 Everyone is an engineer and the job of an engineer is to deliver outcomes, not outputs. Everything we do&mdash;the products we build, the partnerships we launch, the strategy we set&mdash;exists to make our customers successful. Delivery is the strategy.
 
 
 
 Make the call:
 
 Organizations are only as strong as the pace at which they make decisions. Everyone at Percepta should feel empowered to commit and shape the ambiguity in front of them. But "make the call" cuts both ways: make the decision
 
 and
 
 make the phone call. High-agency decision-making only works with high-bandwidth communication and we commit to never operate in silos.
 
 
 
 Intensity with kindness:
 
 We believe in excellence in execution, candor in feedback, ruthlessness in prioritization, and survivalist urgency. We also believe you don't need to be an asshole to deliver on any of this. The trust built through shared kindness and vulnerability is what makes the intensity sustainable.
</div>

Applied AI Engineer - Europe

Xcede

<div>
 
 
 
 Senior AI Engineer
 
 
 
 
 
 London (Hybrid, typically 1 day per week, but this will occasionally vary slightly)
 
 
 
 
 
 
 
 
 Opportunities at this level in AI are exceptionally rare. Join one of the true global leaders in the space.
 
 
 
 
 
 
 
 We&rsquo;re lucky enough to be partnering with one of the world's leaders in Applied AI. They're building the most important solutions at the forefront of commercial Generative AI deployment and answering the global demand for useful, tangible AI products.
 
 
 
 
 
 The business designs and delivers production-grade AI systems for large, market-leading clients across various industries, including financial services, retail, healthcare, travel, gaming, and critical infrastructure. Their teams work directly with globally recognised brands to build scalable AI applications that solve real operational problems, not proof-of-concept demos.
 
 
 
 
 
 This is a highly technical, engineering-led environment focused on shipping real-world AI systems into production. The culture is fast-moving, collaborative, and deeply product-minded, with strong emphasis on ownership, experimentation, and engineering quality.
 
 
 
 
 
 The company is entering a major phase of international growth and investment, with significant backing, ambitious hiring plans, and access to some of the most advanced AI capabilities currently available in the market.
 
 
 
 
 
 
 The Role
 
 
 
 As a Senior AI Engineer, you&rsquo;ll work within small, high-performing delivery teams designing, building, and deploying enterprise-grade AI applications powered by Large Language Models and modern AI tooling.
 
 
 
 
 
 You&rsquo;ll operate across the full delivery lifecycle from solution architecture and orchestration through to deployment, optimisation, monitoring, and client adoption. Projects are highly hands-on and often involve agentic systems, retrieval architectures, multimodal workflows, and real-time AI applications deployed into complex enterprise environments.
 
 
 
 
 
 This role combines strong software engineering with applied AI delivery. You&rsquo;ll be expected to contribute technically, communicate directly with clients, and help shape engineering best practices internally.
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 
 <ul>
 <li>
 Design and build production-grade AI applications using LLMs and modern AI frameworks
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Develop scalable backend systems, APIs, orchestration layers, and microservices to support enterprise AI deployments.
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Work across the full AI lifecycle including architecture, deployment, monitoring, evaluation, optimisation, and maintenance
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Build and deploy agentic workflows, RAG systems, multimodal applications, and AI-powered automation tools
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Collaborate directly with enterprise stakeholders to understand business problems and translate them into technical solutions
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Contribute to technical leadership across projects, including mentoring engineers and improving internal engineering standards
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Work closely with cross-functional teams across engineering, product, delivery, and client environments
 </li>
 </ul>
 
 
 
 
 
 What We&rsquo;re Looking For
 
 
 
 
 
 <ul>
 <li>
 Strong software engineering foundations, particularly in Python
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Experience building and deploying production AI/ML systems in enterprise environments
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Hands-on experience with Large Language Models and modern AI application architectures
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Strong understanding of backend engineering, APIs, microservices, distributed systems, and cloud-native development
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Experience with technologies/frameworks such as LangChain, LangGraph, vector databases, Docker, Kubernetes, Azure, AWS, or GCP
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Ability to design scalable, maintainable systems with strong engineering and operational awareness
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Strong communication skills and confidence operating in client-facing environments
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Comfortable working in fast-paced, high-ownership engineering teams
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Experience across the full lifecycle of AI delivery from ideation through to production deployment is highly desirable
 </li>
 </ul>
 
 
 
 
 
 Desirable Experience
 
 
 
 
 
 <ul>
 <li>
 Agentic AI systems and orchestration frameworks
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 RAG architectures and evaluation frameworks
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Real-time or voice-enabled AI systems
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Production monitoring, guardrails, latency optimisation, and cost optimisation
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Previous experience in consulting or highly collaborative delivery-focused environments
 </li>
 </ul>
 
 
 
 
 
 
 
 If this role interests you and you would like to find out more (or find out about other roles), please apply here or contact us via niall.wharton@Xcede.com (feel free to include a CV for review).
 
</div>

Senior 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

Kinarden Search

<div>
 
 An exciting opportunity has arisen within a global consultancy's new and growing Data Science and AI team working on a range of machine learning, analytics and model validation projects.
 
 
 This role will suit individuals with experience in data science, machine learning or applied AI who are looking to work across a variety of complex business and technology challenges.
 
 
 
 
 
 
 The opportunity:
 
 
 <ul>
 <li>
 Developing and validating machine learning models
 </li>
 <li>
 Supporting the review and assessment of AI and data science solutions
 </li>
 <li>
 Working with large and complex datasets to generate meaningful insights
 </li>
 <li>
 Collaborating with technical and non-technical stakeholders
 </li>
 <li>
 Contributing to the development of innovative AI and analytics capabilities
 </li>
 </ul>
 
 
 
 
 
 Key requirements:
 
 
 <ul>
 <li>
 Strong Python skills (essential)
 </li>
 <li>
 Experience developing and validating machine learning models
 </li>
 <li>
 Knowledge of machine learning frameworks and statistical modelling techniques
 </li>
 <li>
 Exposure to LLMs, Generative AI or Agentic AI
 </li>
 <li>
 Experience with cloud platforms such as Azure or AWS desirable
 </li>
 <li>
 Strong communication and stakeholder management skills
 </li>
 </ul>
 
 
</div>

Data Scientist

CABINET OFFICE

No10 AI Engineer

Station

<div>
 
 
 Python Engineer
 
 
 
 
 
 
 
 (AI / LLM Focus)
 
 
 
 
 
 
 London (Hybrid) | 🚀 Fintech Scale-Up
 
 
 
 
 
 We&rsquo;re partnering with a fast-growing fintech company in London that&rsquo;s redefining how financial data is leveraged through cutting-edge AI. They&rsquo;re now looking for a Python Engineer with strong experience in AI and Large Language Models (LLMs) to help build intelligent, scalable products used by thousands of customers.
 
 
 
 
 
 This is a high-impact role where you&rsquo;ll work closely with product, data, and engineering teams to bring AI-driven features into production.
 
 
 
 
 
 
 What you&rsquo;ll be doing:
 
 
 <ul>
 <li>
 Designing and building scalable backend systems using Python
 </li>
 <li>
 Developing and integrating LLM-powered features into core products
 </li>
 <li>
 Working with modern AI frameworks (e.g. OpenAI, LangChain, Hugging Face)
 </li>
 <li>
 Collaborating with data scientists to productionise models
 </li>
 <li>
 Improving system performance, reliability, and scalability
 </li>
 <li>
 Contributing to architectural decisions in a growing engineering team
 </li>
 </ul>
 
 
 
 
 
 What they&rsquo;re looking for:
 
 
 <ul>
 <li>
 Strong experience with Python in a production environment
 </li>
 <li>
 Hands-on experience with LLMs or applied AI (prompt engineering, fine-tuning, RAG, etc.)
 </li>
 <li>
 Experience building APIs and backend services
 </li>
 <li>
 Solid understanding of cloud platforms
 </li>
 <li>
 Ability to work in a fast-paced, product-driven environment
 </li>
 </ul>
 
 
 
 
 
 Why join?
 
 
 <ul>
 <li>
 Work on genuinely impactful AI products in fintech
 </li>
 <li>
 Strong engineering culture with a focus on innovation
 </li>
 <li>
 Backed by top-tier investors
 </li>
 <li>
 Competitive salary + meaningful equity
 </li>
 <li>
 Flexible hybrid working in London
 </li>
 </ul>
 
 
</div>

Python Developer

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