applications 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

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

SQLI

<div>
 
 We Elevate. Digitally.
 
 
 
 
 SQLI is a European leader in digital transformation and customer experience, helping major international brands drive growth through technology. From strategy to implementation, we design and deliver high-performance architectures and engaging digital experiences by combining advanced technologies, proven methodologies, and deep technical expertise.
 
 
 
 
 With 2,200 people across 12 countries, we&rsquo;re looking for passionate individuals who share our values: Creative Spirit, Commitment, and Forward Thinking.
 
 
 
 
 
 
 Job Description
 
 
 
 
 
 
 About the role
 
 
 
 
 
 
 The AI Engineer is the build engine of our AI practice. You turn business requirements into working AI solutions, fast, using coding agents and frontier models, then take the ones that prove their worth into production with the security, compliance, and reliability that enterprise clients demand.
 
 
 
 
 This is not a model-training role. We are not building or fine-tuning models from scratch. You build agentic workflows and LLM-powered applications on top of frontier models, wire them into real enterprise systems, and make them safe to run.
 
 
 
 
 You will work as part of the delivery team alongside consultants, business analysts, and architects. The consultant carries the client relationship and the architect owns the hard architectural calls. You own the build and you make real engineering decisions, not just execute someone else&rsquo;s spec. You are proactive about spotting better ways to build, and trusted to deliver without close supervision.
 
 
 
 
 
 
 What you will do
 
 
 
 
 
 <ul>
 <li>
 
 Use coding agents to prototype AI solutions quickly against real client requirements, so the team can validate value before committing to a full build
 
 
 
 </li>
 <li>
 
 Build, deploy, and maintain LLM-powered applications and agents that align with enterprise architecture principles and standards, with evaluation, monitoring, and token tracking in place from day one
 
 
 
 </li>
 <li>
 
 Set up MCP connectors and permissions against client systems, taking real care over data handling, access control, and what an agent is and is not allowed to do
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Build production solutions that meet client security requirements and European data protection obligations, including GDPR. This is not optional and not an afterthought
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Collaborate with consultants, business analysts, and architects to break business requirements down into solutions that are feasible, maintainable, and safe
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Create reusable AI assets and accelerators for the practice, including skills, plugins, and MCP servers that make future engagements faster
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Support Data &amp; AI teams with best practices around AI-assisted development, documentation, and automation, and coach less experienced colleagues on agentic build patterns and security standards
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Document deployment, upgrade paths, and maintenance so SQLI and our clients can own what you build after handover
 
 
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 
 
 
 <ul>
 <li>
 
 Proven experience with AI-assisted development. You have shipped something real with Claude or another agent platform, not just followed tutorials
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Strong TypeScript and/or Python for agentic glue code, custom MCP work, and evaluation
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience building RAG applications
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Hands-on with creating and using agent plugins, skills, and MCP servers for repeatable agentic workflows
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Skilled at engineering the prompts and context that let agents do work as autonomously as is safe and sensible
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Solid grasp of security, access control, and data protection (including GDPR) when building systems that act against real client data with real permissions
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience setting up CI/CD pipelines and automation
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Able to take a prototype through to a production-grade build, not just one or the other
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Strong collaboration and communication skills, ideally from an agency or consulting setting
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Proactive and autonomous, able to spot opportunities, make sound engineering decisions, and own delivery rather than wait to be told how to build
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Business-level English, able to understand business requirements directly from clients and communicate clearly in calls and in writing
 
 
 
 </li>
 </ul>
 
 
 
 Nice to have
 
 
 
 
 
 <ul>
 <li>
 
 Familiar with Microsoft Azure, particularly Azure AI infrastructure, as our primary cloud for production AI
 
 
 
 </li>
 <li>
 
 Hands-on with Anthropic&rsquo;s managed agent infrastructure (Claude managed agents, the agents API)
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Prior work on evaluation methods for LLM outputs
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience in e-commerce, or from an AI, agentic, or workflow automation background
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Comfortable presenting technical work and learnings to a non-engineering audience
 
 
 
 
 
 </li>
 </ul>
 
 Additional Information
 
 
 
 
 
 
 How we will work together
 
 
 
 
 
 
 You will report into the Data &amp; AI service line leadership and work as part of client delivery teams across the service line and the wider SQLI group. The role is primarily billable client work. You will occasionally join client sessions for technical depth, but the consultant carries the relationship. We are looking for someone who can own technical decisions on the build, not only execute, with room to grow toward an AI Architect track as the practice scales.
 
 
 
 
 
 
 How to apply
 
 
 
 
 
 
 Send a short note covering:
 
 
 
 <ol>
 <li>
 
 One thing you have built recently with Claude Code or a Claude-based agent, with a link if possible
 
 
 
 </li>
 </ol>
 <ol>
 <li>
 
 How you would take an agent that touches real client systems from a quick prototype to something safe to run in production
 
 
 
 </li>
 </ol>
 <ol>
 <li>
 
 Your notice period and earliest start date
 
 
 
 </li>
 </ol>
 
 
 Why you&rsquo;ll love working at SQLI?
 
 
 
 
 <ul>
 <li>
 A flexible remote working policy: 3 days per week
 </li>
 <li>
 Continuous learning opportunities and certifications to support your development
 </li>
 <li>
 Personalised support: career follow-up, diverse projects, and strong team collaboration
 </li>
 <li>
 Regular rituals: internal communications on tech and AI topics, internal events, and meet-ups
 </li>
 </ul>
</div>

AI Engineer

Talan

<div>Company Description 
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI). 
Job Description 
As our AI practice grows, we are looking for a capable, hands-on AI Engineer to help build and deliver the solutions at the heart of our client work. Coming from a data science background, you are equally comfortable applying proven machine-learning techniques to traditional analytics problems and working with the latest generative AI (large language models, retrieval-augmented generation, and agent-based applications). You enjoy building, you write dependable code, and you turn well-defined designs into working software.
This is a delivery-focused role that sits a level below our Lead Data Scientists. You will own meaningful workstreams within a project rather than the whole engagement, working to an architecture and plan shaped by more senior colleagues. In return, you will gain breadth across modern AI, exposure to real client problems,
You will also be a supportive presence within the team, helping your peers solve problems, sharing what you learn, and giving day-to-day guidance to graduate and junior resources working alongside you.
Required skills &amp; experience:<ul><li>
Build, test, and deploy AI and machine learning components within client projects to the standards and designs set by senior colleagues.</li><li>
Develop GenAI and LLM-based features (prompting, retrieval-augmented generation, and simple agentic workflows) alongside more traditional ML models.</li><li>
Deliver classical data science tasks (data preparation, feature engineering, model training, and evaluation) on projects that call for them.</li><li>
Translate solution designs into clean, well-documented, production-minded code.</li><li>
Contribute to model evaluation, testing, and monitoring.</li><li>
Support and guide very junior and graduate resources, reviewing their work and helping them grow.</li><li>
Help peers unblock technical problems and share knowledge across the team.</li><li>
Take part in client and team discussions and communicate your work clearly.</li></ul> 

Qualifications 
To qualify for this role, you must have:
<ul><li>Typically, 2&ndash;4 years' experience in data science, machine learning, or AI engineering.</li><li>
Solid grounding in core data science and machine learning.</li><li>
Practical experience with LLMs and generative AI, including prompting and RAG.</li><li>
Familiarity with how AI agents are built and orchestrated.</li><li>
Strong Python and common data/ML libraries; good engineering habits.</li><li>
Clear communicator and collaborative team player.</li></ul>
Ideally, you&rsquo;ll also have, but not essential:<ul><li>
Exposure to cloud AI platforms, Azure a plus.</li><li>
Experience practicing MLOps and LLMOps.</li><li>
Early experience mentoring junior colleagues.</li><li>
Interest in consulting and client-facing delivery.</li></ul>
You must be:<ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul>
#TalanUK #LI-HB1 
Additional Information 
Compensation &amp; Benefits Package:<ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul>
Why join:
This is a role built for momentum, working across the full spectrum of modern AI, learning from senior architects and leads on real engagements, with genuine responsibility from day one and a clear path into a leadership track.</div>

AI Engineer (LLMs, Agents & Applied Data Science)

Houseful

<div>6 months Initial Contract - Must work from the UK
Alto Software Group (ASG) is a leading B2B SaaS platform serving the UK property industry. We power thousands of estate agency branches and support a significant proportion of UK housing transactions each year.
We are building a data-driven, operationally efficient platform business. AI will be a structural lever in improving internal productivity, reducing operational cost, and enhancing customer experience.
This is a hands-on delivery role responsible for building the automations and AI integrations that embed AI into how we operate.
The Role
We are hiring a contract AI Engineer to build, deploy and maintain AI-enabled automations across our core systems stack. Working with the Principal Engineer and the Head of AI Operations, you will take prioritised automation opportunities from design through to production.
You will deliver against an internal AI roadmap spanning Customer Operations, Marketing, Finance, Education and Training to:<ul><li>Automate high-volume, manual administrative workflows</li><li>Build AI-enabled workflows in Salesforce, Zendesk, HubSpot, Zuora and Thrive LMS</li><li>Turn the Mission Control data platform into an engine for event-triggered automation</li><li>Reduce operational overhead and improve reporting speed and accuracy</li></ul>
Core ResponsibilitiesAutomation Build &amp; Integration<ul><li>Build and maintain automation pipelines using n8n, Zapier/Make and direct LLM API integrations (OpenAI/Anthropic)</li><li>Develop API and webhook integrations across Salesforce, Zendesk, HubSpot, Zuora and Thrive LMS</li><li>Implement workflows such as ticket summarisation, tagging, routing and AI triage</li></ul>
AI Engineering<ul><li>Design and implement RAG pipelines and vector database integrations over internal knowledge</li><li>Develop, test and version prompts; evaluate and improve output quality</li><li>Build event-triggered automations and AI-enabled reporting on Mission Control</li></ul>
Quality, Security &amp; Handover<ul><li>Apply sound engineering standards: error handling, logging and monitoring of automations in production</li><li>Ensure GDPR-compliant, secure handling of customer and company data</li><li>Document solutions clearly and hand over to internal teams for ongoing operation</li></ul>
What Success Looks Like (First 6 Months)<ul><li>Priority automation workflows live, stable and monitored in production</li><li>Measurable reduction in manual effort in targeted workflows</li><li>Reliable integrations across the core systems stack</li><li>Clear documentation enabling internal teams to operate and extend what you build</li></ul>
Required ExperienceTechnical<ul><li>Proven delivery of LLM-based automation in production environments</li><li>Strong experience with automation platforms (n8n, Make or Zapier)</li><li>Proficiency in Python and SQL</li><li>Strong API and webhook integration capability</li><li>Experience working with OpenAI/Anthropic APIs and prompt engineering</li><li>Experience building RAG pipelines and working with vector databases</li><li>Experience automating CRM (Salesforce) and support (Zendesk) environments preferred</li></ul>
Delivery<ul><li>Experience operating in B2B SaaS or similar fast-moving environments</li><li>Track record of delivering as a contractor: scoping, building and handing over cleanly</li><li>Comfortable working with non-technical stakeholders to refine requirements</li></ul>
Personal Attributes<ul><li>Delivery-focused and pragmatic</li><li>High agency and accountability</li><li>Structured, with strong attention to reliability and security</li><li>Comfortable working in ambiguity</li><li>Clear communicator with technical and non-technical audiences</li></ul>
Why This Role Matters
AI will be a structural margin lever for ASG. The automations you build will directly reduce operational cost, increase capacity without incremental headcount, and embed AI as core operational infrastructure rather than experimentation.</div>

AI Engineer (Contract)

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

Xelix

<div>
 
 About Us
 
 
 
 At Xelix, we work with some of the world&rsquo;s largest companies to automate and strengthen their financial controls. Our AI solutions redefine how Accounts Payable teams operate &ndash; moving from manual processes to automated, intelligent workflows.
 
 
 Xelix is a fast-paced scale-up &ndash; things move fast and expectations are high. We raised our Series B with Insight Partners in June 2025 and are expanding aggressively. We have a team
 
 150
 
 talented people pulling together to achieve our goals. Everyone is trusted to take ownership, move fast and have a meaningful impact. We prioritise personal and professional growth, keep things fun, and love to celebrate a milestone together.
 
 
 In this role you&rsquo;ll grow, be challenged and help shape the future of Xelix. If you&rsquo;re excited about building something special with us, we&rsquo;d love to hear from you.
 
 
 
 About The Role
 
 
 
 We are hiring an AI Engineer to join our growing AI Engineering team. You&rsquo;ll design and build production AI systems &mdash; combining machine learning, large language models, and strong engineering &mdash; to solve real problems across documents, email, and financial data.
 
 
 We focus on building systems that work reliably in production, not just prototypes. We use modern AI tools extensively in our workflow, enabling engineers to operate at a higher level &mdash; focusing on system design, product thinking, and solving complex problems.
 
 
 
 What You'll Be Doing
 
 
 
 <ul>
 <li>
 AI Systems &amp; Agents: design and build production AI systems &mdash; including agent-based workflows, tool use, and multi-step reasoning.
 </li>
 <li>
 Model Development &amp; Adaptation: develop and improve models across text, vision, and structured data, including fine-tuning and hybrid ML + LLM approaches.
 </li>
 <li>
 LLM Platform Work: work with hosted and self-hosted models, contributing to decisions around model selection, performance, and cost.
 </li>
 <li>
 Production Engineering: write clean, maintainable Python and contribute to scalable, observable systems.
 </li>
 <li>
 Evaluation &amp; Iteration: design evals, measure performance rigorously, and improve systems using real-world feedback.
 </li>
 <li>
 AI-Assisted Development: use modern AI coding tools to move faster while maintaining high standards.
 </li>
 <li>
 Collaboration: work closely with product and engineering teams to deliver high-impact features.
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Bring
 
 
 
 <ul>
 <li>
 Experience: 2&ndash;5 years building and shipping ML or AI-powered systems into production.
 </li>
 <li>
 Strong Engineering Skills: clean, testable Python; solid software design; experience working in production environments.
 </li>
 <li>
 AI/ML Breadth: experience with either traditional ML (e.g. gradient boosting) and/or LLM systems (prompting, tool use, evals, agents).
 </li>
 <li>
 Systems Thinking: ability to reason about trade-offs (accuracy, latency, cost, reliability) and design accordingly.
 </li>
 <li>
 Data Skills: SQL, pandas, and experience working with messy real-world data.
 </li>
 <li>
 AI-Native Workflow: comfortable using AI-assisted coding tools effectively.
 </li>
 <li>
 Curiosity &amp; Ownership: proactive in exploring new approaches and improving existing systems.
 </li>
 <li>
 Collaboration: strong cross-functional working style.
 
 
 </li>
 </ul>
 
 What We Offer In Return
 
 
 
 💰 Competitive salary of &pound;65,000 to &pound;75,000 depending on experience
 
 
 🏝️ 27 days of annual leave (including 3 days Christmas closing) which increases up to 3 days based on tenure, with the option to roll over, buy or sell up to 3 days
 
 
 🏡 Hybrid working with two days a week from our dog-friendly Hoxton office
 
 
 💪 On-site gym and cycle to work scheme
 
 
 🛍️ Employee discount at over 100 retailers
 
 
 🏥 Comprehensive private medical &amp; dental cover with Vitality
 
 
 🍼 Enhanced parental leave pay
 
 
 📚 Learning &amp; development culture &ndash; &pound;1,000 personal annual budget
 
 
 🌍 We&rsquo;re carbon-neutral and are working towards ambitious carbon reduction goals
 
 
 🎯 Lots of team socials &amp; activities
 
 
 ☀️ Annual team retreat
 
 
 
 Want to learn more?
 
 
 
 <ul>
 <li>
 About us
 </li>
 <li>
 Xelix blog
 </li>
 <li>
 Xelix news
 </li>
 <li>
 Xelix glassdoor
 
 
 </li>
 </ul>
 We believe that people from diverse backgrounds, with different identities and experiences make our company and product better. No matter your background, we'd love to hear from you! And if you have a disability, please let us know if there's any way we can make the interview process better for you - we're happy to accommodate!
 
 
 If you're a recruiting agency - we have an existing list of agencies we work with if required and we are not currently planning on expanding the list. Neither the Talent team nor hiring managers or the Support team will respond to cold outreach.
 
 
 This is a full-time position, with standard working hours from 9:00 AM to 6:00 PM, Monday through Friday.
 
 
 
 Interview Process
 
 
 
 While the exact process may vary slightly depending on the role, our typical interview stages are:
 
 
 <ul>
 <li>
 Introductory Call &ndash; A short Teams conversation with a Talent Partner to discuss your background and the opportunity.
 </li>
 <li>
 Hiring Manager Interview &ndash; A 30&ndash;45 minute Teams meeting to explore your experience and fit for the team.
 </li>
 <li>
 Technical Task or Presentation &ndash; A role-relevant exercise to demonstrate your skills and approach.
 </li>
 <li>
 Final On-site Interview &ndash; An in-person meeting with our senior leadership team and co-founders at our office.
 
 
 </li>
 </ul>
 We strive to make the process clear, efficient, and respectful of your time.
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