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artificial intelligence engineer Jobs in Manchester

artificial intelligence engineer

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ai engineers

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automation engineer

Adria Solutions Ltd

<div>
 <p>
  AI Engineer (Agentic AI) &ndash; Applied AI in Production
 </p>
 <p>
  <br/>
 </p>
 <p>
  We&rsquo;re looking for a
  <strong>
   hands-on AI Engineer
  </strong>
  to build real-world AI systems that deliver measurable impact across customer journeys and internal operations. This role is all about turning emerging AI capabilities-LLMs, agentic systems, ML models, workflows, and AI services-into robust, production-ready solutions.
 </p>
 <p>
  <br/>
 </p>
 <p>
  What You&rsquo;ll Do
 </p>
 <ul>
  <li>
   Design, build, and integrate AI applications into end-to-end workflows.
  </li>
  <li>
   Embed agentic AI into customer and operational processes with reliability, resilience, and safe fallback behavior.
  </li>
  <li>
   Collaborate with Product, Engineering, Data, and Operations to take AI solutions from concept to production.
  </li>
  <li>
   Establish best practices for orchestration, testing, monitoring, and operational safeguards.
  </li>
  <li>
   Evaluate emerging AI capabilities and translate them into practical, high-value implementations.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  What We&rsquo;re Looking For
 </p>
 <ul>
  <li>
   Strong software engineering background (Python), with experience delivering production AI or ML-integrated systems.
  </li>
  <li>
   Hands-on experience with LLMs, AI services, or agentic AI frameworks.
  </li>
  <li>
   Practical understanding of AI production concerns: latency, resilience, observability, safety, and maintainability.
  </li>
  <li>
   Systems thinker who collaborates effectively across teams and communicates clearly.
  </li>
  <li>
   Passion for applied AI and agentic systems, with a focus on turning capabilities into tangible outcomes.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Bonus if you have:
  </strong>
  AWS AI/ML experience, building autonomous workflows, regulated industry exposure, or contributions to the AI community.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Join us and help shape the future of AI-driven systems in a fast-moving, hands-on environment.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Interested? Please Click Apply Now
 </p>
 <p>
  <br/>
 </p>
 <p>
  AI Engineer (Agentic AI) &ndash; Applied AI in Production
 </p>
</div>


Artificial Intelligence Engineer

Gambling.com Group

<div><p>Gambling.com Group (Nasdaq: GAMB) is a multi-award winning provider of marketing and sports data services looking for exceptional talent interested in the fast-paced, high-growth online gambling industry. The company operates a portfolio of renowned websites and brands &ndash; including flagship site Gambling.com and sports betting site Bookies.com as well as iGaming-focused sites Casinos.com, BonusFinder.com and Freebets.com.</p>
<p>
In addition to its marketing operations, Gambling.com Group provides sports data services through consumer subscription platforms like OddsJam and RotoWire, along with B2B services through OpticOdds. These offerings deliver real-time data, actionable insights, and technology driven tools to both consumers and enterprise partners.</p>
<p>
As the first and only online gambling affiliate publicly traded in the U.S., Gambling.com Group has earned recognition as a leader in its field &ndash; most recently winning Affiliate of the Year at the 2025 EGR Operator Awards.</p>
<p>
Are you ready to take the next step in your career?</p>
<p><b>
Functions and Scope</b></p>
<p><b>
This is an AI engineering role embedded in a commercial function. The primary output of this role is agents and automated workflows &mdash; built, owned, and iterated on by you. Commercial knowledge informs what gets built. The building is the job.</b></p>
<p><b>
Commercial Operations &amp; Optimisation</b></p>
<ul>
<li>Support the commercial function in commercially optimising vertical site performance to drive revenue across all channels &mdash; doing so primarily by identifying where AI agents and automated workflows can replace or accelerate manual commercial processes, and then building them.</li>
<li>Act as the primary operational owner of commercial operational processes across all verticals,which in practice means owning the AI and automation layer that powers those processes, not just the processes themselves.</li>
<li>Conduct ongoing competitor analysis, develop new commercial process and agentic workflow ideas, and collaborate with product and marketing teams to drive operational improvements,using AI tooling to run analysis at scale, generate workflow concepts, and prototype solutions faster than traditional approaches allow.</li>
<li>Collaborate with commercial leadership to set, manage, and monitor BAU processes, KPIs, and OKRs across the commercial operations function,building AI-assisted reporting and monitoring infrastructure so that performance visibility is automated, not manual.</li>
<li>Leverage AI to enhance internal software and tooling to build effective, transparent internal processes across commercial operations,this is not a peripheral responsibility, it is the core mechanism through which this role delivers value. You are expected to be actively building, not just recommending.</li>
</ul>
<p><b>Workflow Architecture &amp; Process Design</b></p>
<ul>
<li>Identify inefficiencies and bottlenecks across commercial operations and design structured solutions,your default answer to an inefficiency is an agent or an automated workflow, with manual process redesign as the fallback where automation is not yet viable.</li>
<li>Own the design and deployment of operational workflows that reduce manual effort and improve output quality and consistency across the commercial team ,from initial architecture through to live deployment, with measurable reduction in human effort as the success metric.</li>
<li>Develop and maintain playbooks and performance standards for all commercial workflows, including documentation of how each AI agent or automated workflow is expected to behave, what good output looks like, and where human review is required.</li>
<li>Coordinate with sales and commercial leadership on operational prioritisation and workflow sequencing,translating commercial priorities into a build roadmap for agents and automations, and managing that roadmap actively.</li>
</ul>
<p><b>Agent &amp; Automation Development</b></p>
<p><b>
This is the core of the role. You will be building AI agents. Not scoping them for others to build, not advising on them, not reviewing them after the fact &mdash; designing, building, deploying, and iterating on them yourself, end to end. If you have not built and shipped an AI agent in a professional context, this role is not the right fit.</b></p>
<ul>
<li>Lead the identification and scoping of agentic automation opportunities across commercial operations,this means proactively finding problems worth solving with AI, not waiting to be briefed. You are expected to surface opportunities, make the case for them, and own the build.</li>
<li>Own and build the full development lifecycle for commercial agents across all commercial operations,from problem definition and workflow brief through to prompt architecture, tool integration, testing, deployment, and post-launch iteration. You are the builder, not the commissioner.</li>
<li>Ensure quality, accuracy, and commercial alignment of all automated outputs, establishing QA standards and performance benchmarks for every agent you deploy, and holding yourself accountable for what those agents produce at scale.</li>
<li>Iterate on agent performance post-deployment based on commercial data, stakeholder feedback, and operational signals,treating deployed agents as live products that require ongoing maintenance and improvement, not finished projects.</li>
</ul>
<p><b>Quality Assurance &amp; Reporting</b></p>
<ul>
<li>Establish and oversee QA processes across all commercial operations workflows,including designing the human review layer that sits alongside AI-driven outputs, defining what requires sign-off before going live, and building the infrastructure to enforce that consistently.</li>
<li>Generate, analyse, and present operational KPI reports to senior stakeholders,using AI-assisted tooling to automate data aggregation and surface anomalies, so that your contribution at the reporting layer is insight and recommendation, not manual data pulling.</li>
<li>Monitor workflow and agent performance, surfacing actionable recommendations to commercial leadership on a regular basis, including honest assessment of where agents are underperforming, where outputs are drifting from expected standards, and what needs to be rebuilt or retired.</li>
<li>Operate as the internal expert on AI-enabled tools including Claude, Lovable, and others,not as a power user, but as the person who understands these platforms deeply enough to build production-grade commercial workflows on top of them, apply rigorous judgement to their outputs, and teach others how to work alongside them effectively.</li>
</ul>
<p><b>Key requirements</b></p>
<p><b>
Essential experience</b></p>
<ul>
<li>Experience in a commercial operations, revenue operations, or similar ops role,ideally within a digital media, affiliate, or multi-vertical online business</li>
<li>You have built AI agents and shipped them into a live production environment,this is the baseline requirement for this role, not an aspiration. If your experience is limited to using AI tools, prompting chatbots, or working within workflows someone else built, this role is likely beyond where you are right now</li>
<li>Demonstrable, end-to-end ownership of the agent development lifecycle, from identifying the commercial problem, writing the workflow brief, designing the prompt architecture, integrating tools, testing, deploying, and iterating post-launch. You were the builder, not the person who commissioned or reviewed someone else's build</li>
<li>Experience with AI platforms and tools such as Claude, Lovable, n8n, or equivalent, with specific, named examples of what you built on them, what it did, and how you measured whether it was working</li>
<li>Track record of designing and documenting operational processes, playbooks, and performance standards,including documentation of how agents are expected to behave, what good output looks like, and where human review is required</li>
<li>Experience establishing QA frameworks for AI-generated or automated outputs, setting performance benchmarks, monitoring for drift or failure, and iterating on agent behaviour based on real-world results</li>
<li>Comfortable owning and reporting on KPIs and OKRs, with experience building automated reporting infrastructure rather than pulling data manually</li>
</ul>
<p><b>You must be able to demonstrate, with specific examples, that you have:</b></p>
<ul>
<li>Built and deployed at least one AI agent in a professional context and can walk through exactly what it did, how you built it, where it failed, and what you did to fix it</li>
<li>Designed prompt architecture for a production workflow,not just written prompts, but structured them as part of a repeatable, scalable agent build</li>
<li>Integrated AI agents with external tools, platforms, or data sources as part of a live commercial or operational workflow</li>
<li>Identified a commercial or operational problem, translated it into an agent build brief, built the solution yourself, and measured the outcome</li>
<li>Established and enforced QA standards for automated outputs, including defining what human review is required and building the process to ensure it happens consistently</li>
<li>Iterated on a deployed agent based on performance data or stakeholder feedback, treating it as a live product, not a finished project</li>
</ul>
<p>Candidates who cannot provide concrete, specific examples of building and shipping agents will not progress past the application stage. This is a builder role,your portfolio of what you have built is the application.</p>
<p><b>
Skills &amp; capabilities</b></p>
<ul>
<li>Prompt architecture and agent design,able to structure AI instructions for production-grade reliability, not just one-off outputs</li>
<li>Tool integration,comfortable connecting AI agents to external platforms, APIs, data sources, and internal tooling as part of a live workflow build</li>
<li>Commercial judgement,able to prioritise build decisions based on revenue impact and business context, identifying which automation opportunities are worth the investment</li>
<li>Process design instinct,able to map a commercial problem, identify the automation opportunity within it, and design a structured agent-based solution</li>
<li>Strong cross-functional communication,able to translate between commercial stakeholders who define the problem and technical counterparts who support the infrastructure</li>
<li>Rigorous approach to AI output review ,understanding that what an agent produces at scale is your responsibility, and building QA into every deployment accordingly</li>
</ul>
<p><b>Behaviours we're looking for</b></p>
<ul>
<li>You have shipped things,your instinct is to build a working version, get it into a live environment, and improve it from there rather than designing indefinitely</li>
<li>You treat deployed agents as live products,you monitor them, catch when they drift, and fix them without being asked</li>
<li>You apply structured commercial thinking to what you build,you're not building for technical elegance, you're building to remove manual effort and drive revenue outcomes</li>
<li>You are honest about the limits of what you've built,you know where your agents are reliable and where they require human oversight, and you design for that honestly</li>
<li>You communicate proactively with commercial leadership when something isn't working, an underperforming agent that goes unreported is a failure of this role, not just a technical issue</li>
</ul>
<p><b>Nice to have</b></p>
<ul>
<li>Experience in the affiliate, igaming, media, or performance marketing sectors</li>
<li>Familiarity with competitor analysis methodologies in a commercial context</li>
<li>Exposure to product or engineering teams in a workflow or tooling capacity</li>
<li>Experience building agents that operate across multiple tools or platforms simultaneously,multi-step, multi-tool agent architectures rather than single-task automations</li></ul><br>
<p><br>
<b>A note for applicants:</b> If your experience with AI is limited to using consumer tools, prompting chatbots, or working within workflows someone else built, this role is likely a step beyond where you are right now. We are looking for someone who has built agents, shipped them into a live environment, watched them fail, fixed them, and made them better. That experience is the baseline, not the ceiling</p>
<p>
Perks &amp; Benefits</p>
<ul>
<li>Comprehensive private Healthcare Insurance</li>
<li>Flexible work environment and home office available</li>
<li>Home office allowance</li>
<li>Gym &amp; Leisure Allowance</li>
<li>All the hardware and software you need to be successful</li>
<li>Regular company events and social outings, activities, Spot Awards and a Monthly Social Club</li>
<li>Access to courses for Personal and Career Development</li>
<li>Company Paid Volunteer Day</li></ul></div><p></p>

Commercial Operations Engineer

Maxwell Bond

<div>
 <p>
  <strong>
   AI Systems Engineer
  </strong>
 </p>
 <p>
  <strong>
   Location:
  </strong>
  Hybrid (Manchester)
 </p>
 <p>
  <strong>
   Salary:
  </strong>
  &pound;60,000 - &pound;75,000
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   The Opportunity
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  This is a great opportunity for an experienced Software Engineer with hands-on experience building AI-powered products and systems.
 </p>
 <p>
  <br/>
 </p>
 <p>
  This is not a traditional Machine Learning or Data Science role. You won't be training foundation models or developing new LLM architectures. Instead, you'll be focused on designing and building the software systems that leverage modern AI technologies to solve real-world business problems.
 </p>
 <p>
  <br/>
 </p>
 <p>
  You'll work on AI-native products, intelligent workflows, retrieval systems, agentic architectures and automation platforms, helping shape the next generation of AI-powered software.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What You'll Be Doing
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Designing and building AI-powered applications and services
  </li>
  <li>
   Developing intelligent workflows and agentic systems
  </li>
  <li>
   Integrating LLMs into production software products
  </li>
  <li>
   Building retrieval, context and memory systems
  </li>
  <li>
   Designing robust APIs and backend services
  </li>
  <li>
   Evaluating AI performance, reliability and quality
  </li>
  <li>
   Implementing monitoring, testing and fallback mechanisms for AI-driven features
  </li>
  <li>
   Working closely with engineering leadership to define best practices for AI-native development
  </li>
  <li>
   Contributing to architectural decisions across a modern cloud-based platform
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Experience and Skills
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Essential
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Strong commercial experience as a Software Engineer, Backend Engineer or Full Stack Engineer
  </li>
  <li>
   Experience building applications that utilise Large Language Models (LLMs)
  </li>
  <li>
   Experience designing and delivering production-grade software systems
  </li>
  <li>
   Strong understanding of software architecture and system design principles
  </li>
  <li>
   Experience working with cloud platforms (AWS, Azure or GCP)
  </li>
  <li>
   Strong programming skills in TypeScript, Python or similar modern languages
  </li>
  <li>
   Experience integrating external APIs and services
  </li>
  <li>
   Ability to make pragmatic technical decisions and communicate trade-offs
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Highly Desirable
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Experience building AI agents or agentic workflows
  </li>
  <li>
   Experience with Retrieval Augmented Generation (RAG)
  </li>
  <li>
   Experience working with vector databases and semantic search
  </li>
  <li>
   Knowledge of context management and memory architectures
  </li>
  <li>
   Experience evaluating and testing AI outputs in production environments
  </li>
  <li>
   Experience designing AI-assisted automation systems
  </li>
  <li>
   Exposure to frameworks and tooling within the modern AI ecosystem
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Who This Will Suit
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  This role would suit someone who has moved beyond simply using AI tools in their development workflow and has experience building software products that actively leverage AI capabilities. You may currently be working as:
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Senior Software Engineer
  </li>
  <li>
   Backend Engineer
  </li>
  <li>
   Full Stack Engineer
  </li>
  <li>
   AI Systems Engineer
  </li>
  <li>
   Applied AI Engineer
  </li>
  <li>
   Platform Engineer with AI experience
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  Most importantly, you'll be excited by the challenge of building reliable, scalable software systems that incorporate AI as a core part of the product experience.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Why Apply?
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Work on genuinely innovative AI-native products
  </li>
  <li>
   Influence technical direction and architecture
  </li>
  <li>
   Join a team investing heavily in modern AI technologies
  </li>
  <li>
   Solve complex engineering challenges at scale
  </li>
  <li>
   Opportunity to help shape the future of AI-enabled software development
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  They are committed to moving quickly on this with interview slots available.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Please apply today.
 </p>
</div>


ConnexAI

<div>
 <p>
  <strong>
   Build Low Latency Conversational AI Systems
  </strong>
 </p>
 <p>
  We are building real-time conversational AI systems built on top of large language models, speech AI, and agentic workflows. Our platform combines ASR, LLMs, and TTS into production-grade AI systems used globally across enterprise environments where latency, reliability, and scalability matter.
 </p>
 <p>
  <br/>
 </p>
 <p>
  We are hiring a Machine Learning Engineer to build low-latency production systems for our LLM team. This role is centred around writing scalable code that enables real-time conversational AI to perform reliably under heavy production workloads.
 </p>
 <p>
  <br/>
 </p>
 <p>
  You&rsquo;ll work closely with our LLM and speech teams to solve challenges around inference speed, concurrency, request handling, GPU performance, distributed systems, and real-time response streaming.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What you&rsquo;ll do
  </strong>
 </p>
 <ul>
  <li>
   Build and optimise low-latency LLM systems for real-time conversational AI
  </li>
  <li>
   Write production-grade Python code focused on performance, scalability, and reliability
  </li>
  <li>
   Design systems capable of handling large volumes of concurrent real-time requests
  </li>
  <li>
   Solve engineering challenges around batching, request scheduling, queue management, streaming responses, and distributed workloads
  </li>
  <li>
   Improve inference speed, GPU memory usage, and overall system responsiveness
  </li>
  <li>
   Deploy and optimise open-source LLMs using tooling such as vLLM, TensorRT-LLM, Triton, SGLang, CUDA, or similar technologies
  </li>
  <li>
   Build scalable orchestration layers and ML pipelines around LLM systems, including RAG and agentic workflows
  </li>
  <li>
   Develop backend inference services and APIs for production AI systems
  </li>
  <li>
   Productionise new model capabilities and features for real-world customer use cases
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What we&rsquo;re looking for
  </strong>
 </p>
 <ul>
  <li>
   Strong experience writing production-grade software for machine learning systems
  </li>
  <li>
   Strong Python engineering skills
  </li>
  <li>
   Experience building low-latency or highly concurrent systems
  </li>
  <li>
   Strong problem-solving ability and enjoyment of building systems from the ground up
  </li>
  <li>
   Experience with distributed systems, parallel workloads, and performance optimisation
  </li>
  <li>
   Experience working with inference tooling such as vLLM, TensorRT, Triton, CUDA, ONNX, or similar technologies
  </li>
  <li>
   Experience building scalable backend services or ML systems used in production
  </li>
  <li>
   Understanding of real-time systems and performance-focused engineering
  </li>
  <li>
   Strong communication skills and ability to work closely with engineers and researchers
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Why this role?
  </strong>
 </p>
 <p>
  You&rsquo;ll work on designing and building low-latency conversational AI systems capable of serving large volumes of concurrent real-time requests. The role focuses on solving difficult engineering challenges around inference speed, reliability, concurrency, GPU performance, and scalable production AI systems.
 </p>
 <p>
 </p>
</div>


Machine Learning Engineer

C-Serv

<div><p>Most engineers get to use large language models. You will get to build the systems that run them in production, at scale, under real latency and reliability constraints, for one of the most recognised names in application security and traffic management.</p><p>
Our client is expanding its AI Core group and is looking for a Senior or Staff AI &amp; ML Engineer in the UK. This is hands-on, build-focused work at the centre of how the business turns generative AI from a prototype into a dependable product. You will design and ship multi-agent systems, retrieval-augmented generation pipelines, anomaly detection, fine-tuned models, and the real-time inference layer that serves them.</p><p>
If you want ownership over a serving stack rather than a single notebook, and you want your work measured by what holds up in production rather than what demos well, this is the seat.</p>
What you will own<ul><li>Building and shipping generative AI features end to end: from model selection and fine-tuning through to the inference path that serves them.</li><li>Designing multi-agent and RAG architectures, and anomaly detection, that are accurate, observable, and cost-aware at scale.</li><li>Owning the real-time inference layer on Triton and TensorRT, optimising for latency, throughput, and GPU efficiency.</li><li>Standing up the surrounding microservices in Python and FastAPI, containerised and orchestrated for reliability.</li><li>Setting the technical bar: making architecture decisions, raising code quality, and mentoring engineers around you.</li><li>Partnering with research and product teams to take ideas from experiment to a service customers depend on.</li></ul><b><br>
Requirements</b><ul><li><br>
5 to 10 years of relevant experience, including a proven track record as a technical lead who mentors others.</li><li>Strong, current Python engineering, with production services built and shipped (FastAPI or similar).</li><li>Genuine hands-on GenAI depth: LLMs, RAG, agentic or multi-agent workflows, anomaly detection, and fine-tuning (for example LoRA or PEFT).</li><li>Real-time inference experience with NVIDIA Triton and TensorRT, with real attention to latency, throughput, and cost.</li><li>A microservices mindset, with services built in Python and FastAPI, containerised and orchestrated for reliability.</li><li>Solid grounding in Docker and Kubernetes, and large-scale distributed systems on a major cloud.</li><li>Right to work in the UK. We welcome applications from all backgrounds and are committed to equal opportunity.</li></ul>
Nice to have<ul><li>Experience with vLLM or other serving frameworks alongside Triton and TensorRT.</li><li>Experience in security, networking, or other high-reliability domains.</li><li>Big-data tooling (Spark, Databricks, Snowflake) and modern MLOps practice.</li></ul>
What you will get<ul><li>A genuine build mandate inside an established AI Core team, not a proof-of-concept that never ships.</li><li>Fully remote working anywhere in the UK, built around delivery rather than presence.</li><li>Competitive salary, strong benefits, and clear scope to grow into staff and principal-level influence.</li><li>The backing of C-Serv throughout: a delivery partner that runs a real quality filter and looks after its people, end to end.</li></ul><b><br>
Benefits</b><ul><li><br>
Fully remote working anywhere in the UK, built around delivery rather than presence.</li><li>A clear path to grow into staff and principal-level technical influence.</li><li>Full support from C-Serv across the hiring process and beyond, with full-cycle accountability.</li><li>A values-led, woman-owned delivery partner built on empathy, integrity, collaboration, and growth.</li></ul></div>

AI/ML Engineer

<div><p>We&rsquo;re seeking a future team member for the role of <b>Java Full Stack Engineer </b><b>with AI-driven development exposure </b>to join our Conventional Trust Platform team. This role is located in <b>Manchester </b>.
</p><p>In this role, you&rsquo;ll make an impact in the following ways:
</p><ul><li><div>Define and execute the enterprise Java full stack technology strategy, aligned with business transformation goals.
</div></li><li><div>Champion AI driven development practices (e.g., AI-assisted coding, automated testing, remediation, and code quality).
</div></li><li><div>Drive modernization initiatives including cloud migration, microservices, event-driven architectures, and API-led platforms.
</div></li><li><div>Establish best practices for secure, scalable, and resilient application design.
</div></li><li><div>Oversee end-to-end delivery of complex platforms across backend (Java) and frontend technologies.
</div></li><li><div>Ensure high-quality engineering outcomes using CI/CD, automation, and DevSecOps practices.
</div></li><li><div>Lead large-scale programs focused on velocity, reliability, and cost efficiency.
</div></li><li><div>Drive backlog prioritization, technical debt reduction, and vulnerability remediation<br>
</div></li></ul><div></div><p>To be successful in this role, we&rsquo;re seeking the following:
</p><ul><li><div>Senior full stack engineer with Bachelor's degree in computer science or a related discipline, or equivalent work experience required; advanced degree preferred
</div></li><li><div>Strong hands-on experience with Python, ML frameworks, and LLM/GenAI tooling.
</div></li><li><div>Strong hands-on experience with AI Development tools like Claude CLI, Windsurf
</div></li><li><div>Solid understanding of the ML lifecycle; exposure to model risk or governance is a plus.
</div></li><li><div>Strong Java development skills, including experience with multi-threaded and mission critical applications
</div></li><li><div>Strong Exposure and knowledge of front end technologies such as React and Angular
</div></li><li><div>Ability to solve ambiguous problems with scalable, innovative solutions.
</div></li><li><div>Clear communicator who can influence cross-functional partners.
</div></li><li><div>Excellent collaboration and communication skills, able to engage effectively with engineers, architects, and executives.</div></li></ul></div>

Specialist, Full-Stack Engineer

The Co-Operative Bank

<div><div><ul><div><div><div><h2 class="jobSectionHeader"><b>About the role</b></h2></div><b>
</b></div></div><div><div><div><div><p>We have <b>5 x Data Engineer</b> opportunities, working in our Data and Analytics Delivery department. The Data Engineers will join the group on a 12-month fixed term contract to focus on the migration and integration of data into our new ecosystem.</p>
<p>
The Data Engineer will be designing, developing and testing quality data engineering solutions and will look to challenge and improve our processes, tools and approach. The person in post will undertake review and assurance activity, providing other team members with guidance on design, build and test activity.</p>
<p>
Adhering to standard driven code development, the Data Engineer will deliver solutions that meet business needs in a timely manner and will take responsibility for the testing of their solution, including the analysis of requirement, designs of test cases &amp; scripts, preparing test data and creating and executing tests to ensure effective and accurate deliverables.</p>
<p><i>
We operate on a team led</i><b><i> </i></b><i>hybrid approach with at least 1 day a week in the Coventry or Manchester office.</i></p>
<p><b>
Our benefits include:</b></p>
<ul>
<li>28 days holiday a year plus bank holidays and a holiday buy/sell scheme</li>
<li>Annual discretionary bonus scheme</li>
<li>Personal pension with matched contributions</li>
<li>Life assurance (6 times annual salary)</li></ul><br>
<p></p>
<p><i>
We reserve the right to close this advert early if we receive a high volume of suitable applications</i></p><br>
</div></div></div></div><div><div><div><h2 class="jobSectionHeader"><b>About you</b></h2></div><b>
</b></div></div><div><div><div><div><p>You&rsquo;ll either have a Data Engineering related qualification and/or extensive Data Development experience in a commercial or Agile environment.
</p><p>To be successful in this role it&rsquo;s essential that you will:</p>
<ul>
<li>Have significant experience of <b>AWS</b>, Python, SQL, Git<b> </b>and PySpark</li>
</ul>
<p>Desirable experience needed will be:</p>
<ul>
<li>SISS or SAS experience</li>
<li>Quality Assurance and Test Automation experience</li>
<li>Experience of Database technologies</li>
<li>Experience in Financial Services organisation</li></ul><br>
<br>
</div></div></div></div><div><div><div><h2 class="jobSectionHeader"><b>About us</b></h2></div><b>
</b></div></div><div><div><div><div><p>In 2025, Coventry Building Society purchased The Co-operative Bank. Bringing together our purpose-led building society with the UK&rsquo;s original ethical bank was the start of an exciting journey.</p>
<p>
Trusted by over four million people, we&rsquo;re a mutually owned business free from shareholders, and with our combined experience of almost 300 years, our ethics and dedication will continue to guide us. Together, we have shared values and an ethical approach towards our members, customers and colleagues.</p>
<p>
We&rsquo;re officially recognised as a &lsquo;Great Place to Work&rsquo; and our benefits go beyond basic pay, with a discretionary bonus scheme, a culture of reward and recognition and comprehensive support for wellbeing.</p>
<p>
We&rsquo;re serious about equality, of race, age, faith, disability, and sexual orientation and we celebrate diversity. By working together, we know you&rsquo;ll build more than just a career with us.</p>
<p><b>
Flexibility and why it matters</b></p>
<p>
We understand the need for flexibility, so wherever possible, we&rsquo;ll consider alternative working patterns. Have a chat with us before you</p></div></div></div></div></ul></div></div><p></p>

Data Engineer - AWS

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