llm 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 scales, we are seeking an experienced AI Architect / Engineer to act as the senior technical authority shaping how we design and deliver next-generation AI solutions. This is a role for someone who has moved beyond building individual models to architecting entire systems: agentic platforms, LLM-powered applications, and the production infrastructure that makes them dependable at enterprise scale.
You will sit at the intersection of strategy and delivery, operating across multiple client engagements simultaneously. In the early phases you will shape solutions, validate technical approaches, and translate ambiguous business problems into robust, deployable architectures. As engagements mature, you will provide the technical oversight that keeps delivery teams aligned to the original design intent. Your influence will be felt in pre-sales conversations, solution blueprints, and the technical standards that define how our practice builds.
This is a hands on architectural role, not a purely advisory one. We expect you to remain close to the code, to prototype where it accelerates a decision, and to set a credible technical example for the engineers and data scientists you guide.
Required skills &amp; experience:<ul><li>
Lead end-to-end solution architecture for AI and LLM-based systems, spanning data, integration, infrastructure, and deployment.</li><li>
Design agentic architectures and multi-agent orchestration patterns, defining how LLMs, tools, APIs, and retrieval layers interact reliably.</li><li>
Shape early-stage engagements (scoping, solutioning, estimation, and pre-sales) turning client ambition into deliverable technical plans.</li><li>
Provide technical validation and quality oversight across several concurrent projects, mitigating risk before it reaches delivery.</li><li>
Define LLM integration and prompting strategies, including RAG, fine-tuning, evaluation, and guardrailing approaches.</li><li>
Establish MLOps and LLMOps practices that ensure solutions are observable, testable, and production ready.</li><li>
Set architectural standards, reusable patterns, and reference implementations that raise the quality bar across the practice.</li><li>
Partner with Responsible AI colleagues to embed safety, security, and governance into solution designs from the outset.</li></ul> 

Qualifications 
To qualify for this role, you must have:
<ul><li>Minimum 5 years in AI architecture or AI engineering, ideally 10+, with a track record of production deployments.</li><li>
Deep expertise in LLMs, agent frameworks (e.g. LangGraph, AutoGen, Semantic Kernel), API design, and orchestration.</li><li>
Strong cloud engineering experience.</li><li>
Proven MLOps / LLMOps capability &mdash; CI/CD for models, monitoring, evaluation, and cost optimisation.</li><li>
Hands-on software engineering background (Python and modern tooling) underpinning your architectural decisions.</li><li>
Comfort managing multiple engagements at once, with pragmatic judgement on trade-offs and delivery risk.</li></ul>
Ideally, you&rsquo;ll also have, but not essential:<ul><li>
Experience in consulting, professional services, or pre-sales environments.</li><li>
Exposure to enterprise-scale, regulated AI deployments (financial services, public sector, healthcare).</li><li>
Familiarity with vector databases, knowledge graphs, and advanced retrieval techniques.</li><li>
Relevant cloud or AI certifications.</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:
You will be a founding technical voice in a practice that is investing decisively in AI. The work is varied, intellectually demanding, and commercially significant, you will shape solutions that reach production, not slideware. You will have the autonomy to define how we build, the support of a collaborative multidisciplinary team, and a clear platform to grow into a practice-leading technical figure.</div>

AI Architect / Engineer (Agentic AI & LLM Architecture)

Octopus Energy

<div>
 
 About the role
 
 
 
 Octopus was founded with a mission to use technology to accelerate us towards a low-carbon future. That&rsquo;s why we created Kraken - our own technology platform from scratch which now serves over 70 Million households and is a core reason why Octopus is the number one energy supplier in the UK. We do it by hiring clever, curious, and self-driven people, enabling them with modern tools and infrastructure and giving them lots of autonomy.
 
 
 
 
 We have been using GenAI in live, customer-facing environments since 2022, including one system that creates tens of thousands of high-quality emails for our Energy Specialists, combining our deep knowledge of the energy industry and the Octo communication style with customer-specific data from Kraken.
 
 
 
 
 We are now looking for a Senior AI Engineer. You will build and scale the systems that allow Octopus teams to use Generative AI models (LLMs, RAG, agents). You will be hands-on, working with a cross-functional team to build out flagship AI projects, and the platforms that enable others to succeed with Generative AI.
 
 
 
 
 You&rsquo;ll work on developing solutions that genuinely move us closer to Net Zero in a company passionate about building great technology to change the way customers use energy. You&rsquo;ll have wide open problems to solve, so you&rsquo;ll need to be comfortable with ambiguity, figuring out an approach and validating it fast.
 
 
 
 
 
 
 What you&rsquo;ll do
 
 
 <ul>
 
 <li>
 
 
 
 Design and Develop AI Platform Services:
 
 Build reusable, scalable services that expose GenAI models, knowledge retrieval pipelines, and agent workflows to application teams.
 
 
 </li>
 
 <li>
 
 
 
 Knowledge Base Development:
 
 Build and maintain knowledge retrieval systems. Process heterogeneous documents like pdfs and build embedding pipelines that extract, chunk and embed into embedding models.
 
 
 </li>
 
 <li>
 
 
 
 AI Readiness:
 
 Process content from unstructured documents and make it AI ready: Optimize their structure, clear up text ambiguity, and embed rich machine-readable metadata.
 
 
 </li>
 
 <li>
 
 
 
 AI Ops, evals and observability:
 
 Set up framework for monitoring and evaluating AI output quality (relevance, accuracy, safety, drift, cost) and platform observability (latency, cost, usage).
 
 
 </li>
 
 <li>
 
 
 
 Centre of Excellence:
 
 Act as a centre of excellence for the whole business in the technical side of AI and LLMs usage, setting best practices and accelerating adoption.
 
 
 </li>
 
 <li>
 
 
 
 Governance and Guardrails:
 
 Create governance layers for implementing PII redaction, prompt filtering etc.
 
 
 </li>
 
 
 </ul>
 
 
 
 
 
 What you&rsquo;ll need
 
 
 <ul>
 
 <li>
 
 
 
 Deep GenAI &amp; RAG Expertise:
 
 2+ years of hands-on experience building and productionizing LLM applications, with deep technical knowledge of vector databases (e.g., Qdrant, Weavite, Pinecone, pgvector) and orchestration layers (e.g., LangGraph, LlamaIndex). Comfortable working with heterogeneous documents like pdfs. Experience working with re-ranking models.
 
 
 </li>
 
 <li>
 
 
 
 Production-Grade Asynchronous Python:
 
 Strong software engineering fundamentals with deep experience in asynchronous programming (asyncio, FastAPI) to handle highly concurrent, I/O-bound LLM and database calls.&nbsp;
 
 
 </li>
 
 <li>
 
 
 
 Advanced Context Engineering:
 
 Proven experience solving production RAG challenges such as context window management, metadata filtering and semantic routing. Experience leveraging coding harnesses like Claude code.
 
 
 </li>
 
 <li>
 
 
 
 Modern Software Practices:
 
 Mastery of Git, automated testing and CI/CD pipelines. Experience working with cloud platforms like AWS.
 
 
 </li>
 
 <li>
 
 
 
 Comfort with Ambiguity:
 
 Ability to rapidly prototype an approach, validate it with metrics, and pivot fast in a fast-moving environment.
 
 
 </li>
 
 
 </ul>
 
 
 
 It would be great if you had
 
 
 
 <ul>
 
 <li>
 
 
 
 GraphRAG Experience:
 
 Familiarity with Knowledge Graphs (e.g., Neo4j) and ontologies to enhance standard vector RAG with highly structured, interconnected corporate data.
 
 
 </li>
 
 <li>
 
 
 
 Local/Open-Weight Model Deployment:
 
 Experience deploying and fine-tuning open-weight models (like Llama 3 or Mistral) via frameworks like vLLM or Ollama to optimize token costs and privacy.
 
 
 </li>
 
 <li>
 
 
 
 Prompt Caching &amp; Cost Optimisation:
 
 Practical experience implementing semantic caching layers to drastically reduce LLM API billing and response latency.
 
 
 </li>
 
 
 </ul>
 
 
 
 
 
 
 
 
 
 💚 Why else you'll love it here 💚
 
 
 
 
 
 &bull;
 
 💰 Wondering what the salary for this role is?&nbsp;
 
 Just ask us! On a call with one of our recruiters it's something we always cover as we genuinely want to match your experience with the correct salary. The reason why we don't advertise is because we honestly have a degree of flexibility and would never want salary to be a reason why someone doesn't apply to Octopus - what's more important to us is finding the right octofit!
 
 
 &bull; 🎉&nbsp;Octopus Energy Group is a&nbsp;
 
 unique culture
 
 . An organisation where people learn, decide, and build quicker. Where people work with autonomy, alongside a wide range of amazing co-owners, on projects that break new ground. We want your hard work to be rewarded with perks you actually care about! We were recently named the UK's top company to work for, and we ranked in the top ten in the Sunday Times Best Places to Work 2024. Our Group CEO, Greg has recorded&nbsp;a podcast about our culture&nbsp;and how we empower our people. We&rsquo;ve also been placed in the&nbsp;top 10 companies for senior leadership
 
 
 &bull; 🎁&nbsp;Visit our UK perks hub -&nbsp;Octopus Employee Benefits
 
 
 
 
 
 
 
 If this sounds like you then we'd love to hear from you. 🚀
 
 
 
 
 
 
 
 P.S. Our process usually takes up to 4 weeks, but we&rsquo;ll always do our best to flex around what works for you. Along the way, you&rsquo;ll chat with our recruitment team and your Recruiter will help you throughout different stages. Got any burning questions before then? Drop us a message at talent@octoenergy.com and we&rsquo;d love to help!
 
 
 
 
 
 
 Are you ready for a career with us? We want to ensure you have all the tools and environment you need to unleash your potential.&nbsp;Need any specific accommodations?&nbsp;Whether you require specific accommodations or have a unique preference, let us know, and we'll do what we can to customise your interview process for comfort and maximum magic!
 
 
 
 
 
 
 
 Studies have shown that some groups of people, like women, are less likely to apply to a role unless they meet 100% of the job requirements. Whoever you are, if you like one of our jobs, we encourage you to apply as you might just be the candidate we hire. Across Octopus, we're looking for genuinely decent people who are honest and empathetic. Our people are our strongest asset and the unique skills and perspectives people bring to the team are the driving force of our success. As an equal opportunity employer, we do not discriminate on the basis of any protected attribute. Our commitment is to provide equal opportunities, an inclusive work environment, and fairness for everyone.
 
 
 
 
 Where necessary, we sometimes use AI tools to help with parts of our hiring process, like reviewing applications or assessing responses.
 
 
 We&rsquo;re lucky to receive a huge amount of interest, so these tools help our recruiters manage that volume, not replace them. Ultimately, every hiring decision (for example, whether to progress your application or not) is always made by a real person in our Talent team.
 
 
 If you&rsquo;d like to know more about how we use your data, you can reach out to us via email at talent@octoenergy.com. We&rsquo;re happy to help!
 
</div>

Senior AI Engineer

Jack & Jill

<div>
 
 This is a job that Jill, our AI Recruiter, is recruiting for on behalf of one of our customers.
 
 
 
 She will pick the best candidates from Jack's network.
 
 
 The next step is to speak to Jack.
 
 
 
 Job Title
 
 
 
 AI Engineer
 
 
 
 Salary
 
 
 
 Not Disclosed
 
 
 
 Company Description
 
 
 
 StackOne is a $24M VC-funded AI Integration Gateway backed by GV and Workday Ventures. They provide builders of SaaS platforms and AI Agents with a unified toolkit to orchestrate hundreds of enterprise-grade integrations, combining a real-time architecture with 25,000 pre-mapped actions across 200 connectors.
 
 
 
 Job Description
 
 
 
 As an AI Engineer at StackOne, you will build the future of agentic integrations by delivering end-to-end AI products. Reporting to the CTO, you'll work with AI researchers to develop specialized LLMs for tool-calling, ensuring precision and reliability in agentic execution while maintaining high-performance inference pipelines and retrieval systems.
 
 
 
 Location
 
 
 
 London, UK
 
 
 
 Why this role is remarkable
 
 
 
 <ul>
 <li>
 Work at the frontier of AI R&amp;D, building specialized LLMs designed for tool-calling and agentic execution rather than just general-purpose applications.
 </li>
 <li>
 Join a high-growth startup backed by elite investors like GV and Workday Ventures, scaling a platform that already powers thousands of integrations.
 </li>
 <li>
 Collaborate with a world-class veteran engineering team from industry leaders like Google, Microsoft, and Coinbase in a culture built on shipping and ownership.
 
 
 </li>
 </ul>
 
 What You Will Do
 
 
 
 <ul>
 <li>
 Design and deploy full-stack features including inference pipelines, embeddings, and retrieval systems across AWS and Cloudflare.
 </li>
 <li>
 Implement cutting-edge tool-calling and Model Context Protocol (MCP) patterns to enable one-click agent integrations with any tool.
 </li>
 <li>
 Develop and maintain high-quality open-source and internal TypeScript and Python packages to accelerate the developer ecosystem.
 
 
 </li>
 </ul>
 
 The ideal candidate
 
 
 
 <ul>
 <li>
 Professional experience shipping production-grade applications using Generative AI and LLMs like GPT or Anthropic.
 </li>
 <li>
 Expert proficiency in TypeScript and Python with a proven track record of building scalable systems on AWS, GCP, or Cloudflare.
 </li>
 <li>
 Strong background in full-stack engineering with experience publishing SDKs, CLIs, or complex packages in a fast-paced environment.
 
 
 </li>
 </ul>
 
 Who are Jack &amp; Jill?
 
 
 
 Ok, I'll go first. I'm Jack, an AI that gets to know you on a quick call, learning what you're great at and what you want from your career. Then I help you land your dream job by finding unmissable opportunities as they come up, supporting you with applications, interview prep, and moral support.
 
 
 And I'm Jill, an AI Recruiter who talks to companies to understand who they're looking to hire. Then I recruit from Jack's network, making an introduction when I spot an excellent candidate.
 
 
 
 How does this work?
 
 
 
 <ul>
 <li>
 Jack's an AI agent for job searching and career coaching. He works for you.
 </li>
 <li>
 Jill is the AI recruiter working for the company. She recruits from Jack's network.
 </li>
 <li>
 If it's a match and the company wants to meet you, they'll make the intro. In the meantime, if you'd like, Jack will send you excellent alternatives.
 
 
 </li>
 </ul>
 
 We never post fake jobs
 
 
 
 This isn't a trick. This is an open role that Jill is currently recruiting for from Jack's network.
 
 
 Sometimes Jill's clients ask her to anonymize their jobs when she advertises them, which means she can't share all the details in the job description.
 
 
 We appreciate this can make them look a bit suspect, but there isn't much we can do about it.
 
 
 Give Jack a spin! You could land this role. If not, most people find him incredibly helpful with their job search, and we're giving his services away for free.
 
 
</div>

AI Engineer at StackOne

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

Bluefish AI

<div>About the Position

As a Staff AI Engineer, you&rsquo;ll serve as a technical leader for our LLM-powered products at the forefront of marketing and advertising technologies. You&rsquo;ll own critical architectural decisions, set quality bars, and lead multi‑team initiatives that drive measurable outcomes.

As our Staff AI Engineer, you will lead the vision and execution of our data platform and LLM-powered products. You&rsquo;ll own critical architectural decisions across data pipelines, model integration, model deployment and evals: turning high-level product and business requirements into robust, scalable data products that drive measurable outcomes for our Fortune 500 customers. This role spans data backend and ML engineering: from the reliability and cost efficiency of our pipelines to the outcome and performance of LLM-enabled features. You&rsquo;ll raise the bar for data literacy across the department, craft and collaboration.

You&rsquo;ll be accountable for the health, cost, and evolution of key data product and data platforms, partnering closely with full-stack engineers, product, design, and devops to deliver outcomes our customers can trust.

This role presents an exciting opportunity to shape the future of AI-driven technologies and make meaningful contributions to real-world applications.

The role is linked with our location in London, but we are flexible about hybrid or remote work in The United Kingdom.

What You&rsquo;ll Be Doing
<ul>
<li>Lead end-to-end architecture for data platforms and pipelines: scraping, data extraction, transformation, storage, serving, and ML/LLM integration, balancing performance, reliability, security, and cost.</li>
<li>Incrementally scale pipelines and systems: design safe rollout plans and north star data-quality metrics to handle customer and traffic growth without impacting production.</li>
<li>Translate business goals into actionable data products: assess high-level requirements, carve clear problem spaces, draft crisp RFCs, and sequence work into deliverable projects for the team.</li>
<li>Establish and enforce engineering standards: testing strategy, evals, observability, data contracts, and security practices across services. Think through short-term and long-term goals to come up with fast go-to-market products, while planning ahead for productization.</li>
<li>Up‑level the org: lead architecture reviews, codify patterns, mentor Senior Engineers, and multiply impact through documentation, code reviews, and pairing.</li>
<li>Startup‑ready: flexible, comfortable with ambiguity and constant change; proactive about process, documentation, and reliability without over‑engineering.</li>
<li>Lead the collaboration and define how AI engineers work cross-functionally with software engineers, devops, product managers and designers, to conceptualize and shape innovative and impactful solutions. Provide mentorship to junior team members and cultivate a culture of collaboration and innovation.</li>
<li>Ship meaningful experiments: prototype data/ML capabilities, evaluate feasibility and ROI, and make pragmatic calls on productionalizing with an eye on operating costs and risk.</li>
</ul>
Qualifications
<ul>
<li>8+ years building and operating production data systems, including leading cross-cutting architectural changes, and deploying LLMs in real‑world scenarios at scale.</li>
<li>Deep experience Python and modern service architectures; strong system design and data modeling fundamentals.</li>
<li>Extensive experience with training and deploying machine learning models, particularly within the NLP/LLM domain. Proficiency in Python. Familiarity with infrastructure as code, CI/CD, and cloud infrastructure.</li>
<li>Fluency in operational maturity: SLOs, on‑call/incident practices, and observability.</li>
<li>Strong analytical and problem-solving abilities, with a bias towards action and outcomes. Experience with data preprocessing, feature engineering, and model evaluation techniques.</li>
<li>Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. Demonstrated leadership experience, with the ability to guide and inspire a team.</li></ul> 


About Bluefish:

Bluefish believes that AI represents the next major chapter of the internet &ndash; and that consumers will increasingly use AI to consume information and media online. On this new AI internet, brands will need new tools and technologies to tell their stories to consumers online &ndash; and a new marketing ecosystem will be created around AI. Bluefish is building the platform that helps brands engage consumers on this new AI channel, with powerful enterprise tools to manage AI brand safety and engage consumers with thoughtful and personalized AI marketing experiences.

The Bluefish team is a tight-knit group of mar-tech industry veterans who previously helped build foundational ad-tech platforms now owned by Meta and Microsoft. Bluefish, the leading AI marketing platform for the Fortune 500, recently announced a $43 million Series B growth financing co-led by Threshold Ventures and NEA with participation from multiple enterprise investors including Amex Ventures, TIAA Ventures, Salesforce Ventures, and continued participation from Bloomberg Beta. We are a globally distributed team, with business operations based in New York City and engineering based in Europe and New York.

Why Bluefish &amp; Our Values:
<ul>
<li>Unique opportunity to join on the ground floor of a fast-moving startup building at the center of AI</li>
<li>Tackle challenging and abstract problems while disrupting the $300BN legacy mar-tech industry</li>
<li>Join an experienced high-performing team where you will have immediate ownership and impact</li>
<li>Experience a true meritocracy with significant career growth upside as the business scales</li>
</ul>
Our Values:
<ul>
<li>Demonstrated grit and resourcefulness - you find creative solutions, adapt quickly, and aren&rsquo;t afraid to roll up your sleeves in a fast-paced, evolving environment.</li>
<li>Thoughtful and strategic thinker with the ability to anticipate needs, ask the right questions, and deliver insights that truly drive value.</li>
<li>Proven ability to collaborate across functions and roles, fostering open communication and shared ownership of outcomes.</li>
<li>Commitment to craftsmanship - you take pride in delivering high-quality work, paying attention to the small details while keeping the big picture in mind.</li>
<li>Self-starter with a proactive mindset and a strong sense of accountability - able to drive projects forward independently while staying aligned with team goals.</li>
<li>Comfortable navigating ambiguity and learning new tools, processes, or technologies to get the job done.</li></ul></div>

Staff AI Engineer

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)

Few&Far

<div>
 
 🚨
 
 Senior Data Engineer | Outside IR35 Contract | Up to &pound;525/day | London (1 day onsite)
 
 🚨
 
 
 
 
 
 I'm working with a growing business that's looking for a Senior Data Engineer to join on an initial 6-12 month contract.
 
 
 
 
 
 💰
 
 Up to &pound;525 per day
 
 
 
 📍
 
 London - 1 day per week onsite
 
 
 
 📄
 
 Outside IR35
 
 
 
 ⚡
 
 1-stage interview process
 
 
 
 
 
 
 This is a fantastic opportunity to play a key role in modernising a cloud-based data platform while helping to future-proof the company's infrastructure and mentoring junior engineers as they continue to develop.
 
 
 
 
 
 You'll be working on:
 
 
 ✅ Modernising data lake &amp; data warehouse architecture
 
 
 ✅ Designing, building and optimising ETL/ELT pipelines
 
 
 ✅ Deploying and supporting production ML systems, including forecasting models, LLM-powered and agentic workflows
 
 
 ✅ Enhancing an AWS-native data platform (S3, Redshift, RDS, Athena, SageMaker &amp; Lambda)
 
 
 ✅ Writing high-performance SQL and production-quality Python
 
 
 ✅ Improving platform reliability, monitoring and CI/CD
 
 
 ✅ Collaborating with stakeholders to deliver scalable data solutions
 
 
 ✅ Mentoring junior engineers through code reviews and best practices
 
 
 
 
 
 
 Tech Stack:
 
 
 
 ☁️ AWS
 
 
 🐍 Python
 
 
 🗄️ SQL
 
 
 🔄 Airflow (AWS)
 
 
 📊 Looker (nice to have)
 
 
 
 
 
 I'm keen to speak with Data Engineers who have:
 
 
 ✔️ Strong experience building production-grade data pipelines
 
 
 ✔️ Advanced SQL and Python skills
 
 
 ✔️ Experience deploying and supporting ML models in production
 
 
 ✔️ AWS cloud experience and a solid understanding of DevOps/platform engineering
 
 
 
 
 
 If you're available soon or know someone who could be a great fit, please apply below or share this job post!
 
</div>

Senior Data Engineer

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