ai systems engineer

Accenture

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

AI Native SW Engineering Specialist

<div><div><div>Job ID: R0057440</div>
</div><div><div><div><div><div>Location</div>
<div>London, Middlesex</div>
</div></div></div><div></div><div><div><div><div>Hours/week</div>
<div>37.5 hrs/week</div>
</div></div></div><div></div><div><div><div><div>Payrate range</div>
<div>Unknown</div>
</div></div></div></div><div><div>We don&rsquo;t just believe in better. We make it happen.
Better content. Better products. And better careers. 
Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, Sky Stream to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. 
 
Role/Team overview
We are seeking an AI Operations Engineer to join our Group AI Engineering team and play a key role in keeping our autonomous AI systems running reliably across Sky. You&rsquo;ll work with cutting-edge AI technologies, from large language models to multi-agent architectures, ensuring the agentic solutions already in production stay secure, performant, observable, and cost-effective.
This is a hands-on engineering role within a forward-thinking team driving AI adoption at enterprise scale. Where the build teams take solutions from prototype to launch, you&rsquo;ll own what happens next: maintaining live agentic systems, acting as the frontline support and point of contact for the stakeholders who depend on them, and continuously improving the reliability, security, and efficiency of the platform in production.
What you&rsquo;ll do
<ul><li>Keep existing agentic and multiagent AI solutions reliable, secure, and performant in production as usage and requirements evolve.
</li></ul><ul><li>Act as the point of contact for AI system issues, triaging, diagnosing, and resolving incidents while keeping stakeholders informed throughout.
</li></ul><ul><li>Own monitoring, observability, and quality across the AI estate, going beyond uptime to track health signals specific to agents, such as output quality, model and prompt regressions, and guardrail or tool call failures.
</li></ul><ul><li>Drive FinOps for AI workloads by tracking, attributing, and optimising the cost of LLM usage, compute, and cloud infrastructure to keep solutions efficient at scale.
</li></ul><ul><li>Manage and improve the underlying infrastructure across a stack including Python, AWS, Postgres, and Cloud Foundry and/or Kubernetes, applying sound operational and DevOps practices.
</li></ul><ul><li>Identify and remediate security vulnerabilities across the AI estate, patching dependencies and resolving scan findings so systems stay compliant with Sky's security standards and agentic AI governance.
</li></ul><ul><li>Support and maintain low code automation built in Copilot Studio and Power Automate, ensuring these flows stay reliable, governed, and integrated cleanly with the wider AI platform.
</li></ul><ul><li>As this is a production operations role, on-call cover may be required in the future to keep critical AI systems running reliably outside core hours.
</li></ul>Essential criteria:
<ul><li>Solid software engineering experience in Python, with a good understanding of Agile delivery in large scale enterprise environments.
</li></ul><ul><li>Experience supporting or operating production systems, ideally AI driven or data intensive, with strong monitoring, observability, and distributed systems diagnosis skills.
</li></ul><ul><li>Practical experience with cloud (particularly AWS), relational databases such as Postgres, and familiarity with container orchestration or PaaS such as Kubernetes and Cloud Foundry.
</li></ul><ul><li>Direct experience with low code automation in Copilot Studio and Power Automate, including configuring, troubleshooting, and supporting flows and their integrations.
</li></ul><ul><li>Strong communication and stakeholder management skills, comfortable being the calm point of contact during incidents and translating technical issues for business audiences.
</li></ul><ul><li>Practical experience keeping systems secure, managing dependencies, remediating vulnerabilities, and working to enterprise security standards.
</li></ul>Desirable skills and experience:
<ul><li>Exposure to LLM or agentic AI systems, FinOps cost management, or AI governance and responsible AI controls. 
</li></ul>Benefits and perks
There's one thing people can't stop talking about when it comes to life at Sky: the perks. Here&rsquo;s a taster:
<ul><li>Free Sky TV or NOW package, including Sky Sports and Sky Cinema
</li></ul><ul><li>Pension package with up to 9% employer contribution
</li></ul><ul><li>Private healthcare with mental health support
</li></ul><ul><li>Aviva Digital GP and dental insurance
</li></ul><ul><li>Discounts on Sky products, including Sky Mobile, Sky Broadband, Sky Glass and Sky Protect
</li></ul><ul><li>Sharesave and Tech schemes
</li></ul><ul><li>A range of Sky VIP rewards and experiences 
</li></ul>How you&rsquo;ll work
We've adopted a hybrid working approach to give more flexibility on where and how we work. The hybrid working expectations for this role are 2 days in the office per week. The role is available in our Osterley or Livingston office.
Your office base
Osterley
 Our Sky Group HQ. Equipped with state-of-the-art technology and workspaces, there&rsquo;s plenty of space to see your big ideas come to life. Here you&rsquo;ll find 13 subsidised restaurants and cafes. You can re-energise at our gym, catch the latest films at our cinema, get your car washed and even get pampered at our beauty salon. 
Our Osterley Campus is just a 10-minute walk from Syon Lane train station, or you can get one of our free shuttle buses from Osterley, Gunnersbury and Ealing Broadway stations. Plus, there&rsquo;s free onsite parking available for cars, motorbikes and bicycles.
Livingston Watermark
Sky Watermark is our central site for Livingston, sitting between Glasgow and Edinburgh. With vibrant office spaces, chill-out areas, and an onsite canteen, it&rsquo;s a great place to work and connect. 
The nearest train station is Livingston North. A Sky shuttle bus runs between the station and campus every 20 minutes throughout the day. Plus, there&rsquo;s onsite parking available for cars, motorbikes and bicycles.
Who we are
We&rsquo;re Sky, a leading media and entertainment company who connect millions with entertainment, sports, news and arts through innovative products and services. Working with us means you&rsquo;ll be bringing the joy of a better experience to more people, every day. All so we can do better and deliver better for our customers, colleagues and society. 
We&rsquo;re an equal opportunity employer and value diversity at our company. We're a Disability Confident Accredited Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need as early as you can. 
Just so you know: if your application is successful, we&rsquo;ll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer. 
To be eligible for this role you are required to have the appropriate right to work in the UK. Please be aware Sky does not offer sponsorship for this position. 
To find out more about working with us, search #LifeAtSky on social media.</div></div></div>

AI Operations Engineer (Python)

C-Serv

<div>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.
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.
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.
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> 
Requirements<ul><li> 
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> 
Benefits<ul><li> 
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

Bloomberg

<div>
 Location
 
 
 London
 
 
 Business Area
 
 
 Engineering and CTO
 
 
 Ref #
 
 
 10049302
 
 
 
 Description &amp; Requirements
 
 
 
 Bloomberg&rsquo;s Engineering AI department has 400+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products. At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 35 million financial instruments searchable, discoverable, and actionable across the global capital markets.
 
 
 Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions.
 
 
 Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most.
 
 
 We are looking for Senior ML Platform Engineers with strong expertise and passion for building platforms for (Gen) AI applications.
 
 
 As a Senior ML Platform Engineer, you will have the opportunity to create a more cohesive, integrated, and managed AI development life cycle to enable the building and maintenance of our AI systems. Our teams make extensive use of open source technologies such as, Kubernetes, Kubeflow, KServe, Argo, Buildpacks, and other cloud-native MLOps technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact and sustainability of open source.
 
 
 
 Join the AI Group as a Senior ML Platform Engineer and you will have the opportunity to:
 
 
 
 <ul>
 <li>
 Architect, build, and diagnose multi-tenant AI platform systems
 </li>
 <li>
 Work closely with AI application teams to design seamless workflows for continuous model training, inference, and monitoring
 </li>
 <li>
 Work with AI experts to understand workflows, pinpoint, and resolve inefficiencies, and to inform the next set of features for the platforms
 </li>
 <li>
 Collaborate with open-source communities and AI application teams to build a cohesive MLOps experience
 </li>
 <li>
 Design CI/CD automation frameworks that incorporate regulatory requirements
 </li>
 <li>
 Develop cloud-native deployment patterns for AI systems across environments
 </li>
 <li>
 Troubleshoot and debug user issues
 </li>
 <li>
 Provide operational and user-facing documentation
 
 
 </li>
 </ul>
 
 We are looking for a Senior ML Platform Engineer with:
 
 
 
 <ul>
 <li>
 Proven years of experience working with an object-oriented programming language (Python, Go, etc.)
 </li>
 <li>
 Experience designing cloud-native, distributed platforms
 </li>
 <li>
 Strong knowledge of Kubernetes, Argo, and container orchestration technologies
 </li>
 <li>
 Previous experience with modern CI/CD tools and GitOps workflows
 </li>
 <li>
 Familiarity with implementing automation for model development lifecycles
 </li>
 <li>
 A proactive mentality and ability to collaborate with peers, stakeholders, and management
 </li>
 <li>
 A Degree in Computer Science, Engineering, Mathematics, or similar field of study or equivalent work experience
 </li>
 <li>
 An understanding of Computer Science fundamentals such as data structures and algorithms
 
 
 </li>
 </ul>
 We give back to the technology community and you can read more about our outreach at:
 
 
 If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.
 
 
 Discover what makes Bloomberg unique - watch our for an inside look at our culture, values, and the people behind our success.
</div>

Senior ML Platform Engineer - Artificial Intelligence

LiveKit

<div><h2 class="jobSectionHeader">About LiveKit</h2>
LiveKit is building the infrastructure layer for the agentic era of computing. Our platform gives developers everything they need to build, test, deploy, scale, and observe AI agents in production. Founded in 2021, LiveKit powers voice and agentic AI applications for OpenAI, Salesforce, Spotify, Meta, and tens of thousands of other developers, collectively facilitating billions of calls each year.<h2 class="jobSectionHeader">
About This Role</h2>
LiveKit is seeking a Forward Deployed Engineer (FDE) to work directly with customers building real-time communication and voice AI applications on the LiveKit platform.
This role sits at the intersection of engineering, architecture, and customer implementation. Forward Deployed Engineers partner closely with customers to design systems, prototype solutions, and solve complex technical challenges as teams move from experimentation to production.
You'll work alongside customers' engineering teams to help them successfully deploy and scale applications built on LiveKit &mdash; designing architectures, building integrations, debugging production issues, and developing reference implementations that demonstrate best practices.
This is an ideal role for engineers who enjoy solving real-world problems in real customer environments. You'll collaborate closely with Product and Engineering to surface insights from customer implementations and help shape the future of the LiveKit platform.
Your mission: make it seamless for developers to build and scale real-time audio, video, and AI applications on LiveKit.<h2 class="jobSectionHeader">
You'll Thrive Here If You:</h2><ul><li>
are obsessed with helping developers succeed</li><li>
are known as the go-to person for solving tricky technical issues</li><li>
work hard and can move fast without sacrificing quality</li><li>
care deeply about polish, detail, and clear communication</li><li>
are a fast learner, frequently picking up new tools, systems, and skills</li></ul><h2 class="jobSectionHeader">
What You'll Do</h2><ul><li>
Work directly (remotely or on-site when necessary) with customer engineering teams to design and implement real-time applications built on LiveKit</li><li>
Design scalable architectures for voice AI, real-time media, and developer platform use cases</li><li>
Build prototype integrations, reference implementations, and sample applications to accelerate customer development</li><li>
Help customers navigate SDKs, APIs, infrastructure, and deployment strategies for production systems</li><li>
Debug and troubleshoot complex technical issues in production environments</li><li>
Lead technical workshops and architecture sessions with developers and product teams</li><li>
Translate customer needs into technical insights that inform product and platform development</li><li>
Partner with Product and Engineering to improve developer experience, documentation, and tooling</li><li>
Contribute code, examples, or improvements to LiveKit's open-source ecosystem when helpful</li><li>
Act as a trusted advisor helping customers successfully launch and scale applications on LiveKit</li></ul><h2 class="jobSectionHeader">
Who You Are</h2><ul><li>
Strong engineering background with 5+ years of experience in backend or infrastructure engineering</li><li>
Proficient in one or more programming languages such as Go, Python, Node, Rust, or C++</li><li>
Comfortable working across APIs, SDKs, distributed systems, and cloud infrastructure</li><li>
Experience building or integrating developer platforms or real-time systems</li><li>
Able to quickly understand complex systems and debug issues in real-world environments</li><li>
Strong communicator who can collaborate directly with customer engineering teams and internal product teams</li><li>
Comfortable operating in fast-paced, low-process environments where ownership and initiative matter</li><li>
Excited to work hands-on with customers solving complex technical implementation challenges</li></ul><h2 class="jobSectionHeader">
Nice to Have</h2><ul><li>
Experience with WebRTC, real-time media systems, or telephony/SIP infrastructure</li><li>
Familiarity with voice AI, conversational agents, or AI infrastructure</li><li>
Experience working in customer-facing engineering roles such as Solutions Engineer, Field Engineer, or Forward Deployed Engineer</li><li>
Experience contributing to open-source projects or developer ecosystems</li><li>
Previous experience building with or integrating LiveKit</li></ul><h2 class="jobSectionHeader">
Our Commitment to You</h2><ul><li>
An opportunity to build something truly impactful to the world</li><li>
Contribute to open source alongside world-class engineers</li><li>
Competitive salary and equity package</li><li>
Health, dental, and vision benefits</li><li>
Flexible vacation policy</li></ul>
LiveKit is an equal opportunity employer and does not discriminate on the basis of any characteristic protected by applicable law. If you require a reasonable accommodation during the application or interview process, please contact recruiting@livekit.io.
Compensation Range: &pound;126K - &pound;185K</div>

Forward Deployed Engineer

Software Engineer, AI Native Development

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

Explore 355+ Ai systems engineer in London this July. Find roles across top companies and apply now to boost your career.