AI Platform Engineer

AI Platform Engineer

Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
United States Digital Space LLC

At a Glance

  • Tasks: Design and build modern developer platforms while collaborating with diverse teams.
  • Company: Join a forward-thinking engineering consultancy focused on innovation and work-life balance.
  • Benefits: Enjoy competitive pay, flexible working options, and opportunities for professional growth.
  • Other info: Diverse and inclusive culture that values your unique perspective.
  • Why this job: Make a real impact by transforming organisations and tackling complex tech challenges.
  • Qualifications: Experience with cloud platforms, Kubernetes, and a passion for problem-solving.

The predicted salary is between 60000 - 80000 £ per year.

About Us

The company is an engineering consultancy bridging Quality Engineering, Cloud Platforms and Developer Experience. We help enterprises reliably bring high-impact digital products to market faster, cheaper, and safer, working with technology leaders facing complex business challenges. We take as much pride in our people, culture and work-life balance as we do in making better software. We are not just making better software. We are making the making of software better. Collaborative, entrepreneurial and dedicated to problem solving, we bring the step change our customers need to sustain innovation. Our values challenge us to do the best we can for the company, our customers and most importantly our team. This is an opportunity for you to build the organisation from the ground up, use your voice to drive change and help transform organisations and problem domains.

The Role

We are looking for a Platform Engineer to join client‑facing delivery teams and help design, build, and operate modern developer platforms. You will work across a range of industries and tech stacks, so adaptability matters as much as expertise. On any given engagement you might be building a golden path CI/CD pipeline, hardening a Kubernetes cluster, migrating secrets management to Vault, or running a platform engineering workshop with a client’s engineering teams. You will be expected to lead technical workstreams, pair with client engineers, and leave behind well‑documented, production‑ready infrastructure. Increasingly, our clients are asking us to help them build the foundations for AI, from model‑serving infrastructure and MLOps pipelines to safely integrating LLM APIs into existing developer workflows. You don’t need to be an ML engineer, but you should be curious about this space and comfortable building the platform layer that makes AI workloads production ready.

What You’ll Do

  • Platform & Infrastructure
    • Design and deliver internal developer platforms (IDPs) that improve developer experience and accelerate software delivery.
    • Build and maintain infrastructure‑as‑code using Terraform, Pulumi, or CDK and enforce code review and testing standards.
    • Manage and optimise Kubernetes clusters (EKS, GKE, AKS) including multi‑tenancy, networking, RBAC, and cost controls.
    • Own CI/CD pipelines end‑to‑end: from source control policies through build, test, security scanning, artefact management, and deployment.
    • Implement secrets management and certificate lifecycle automation using HashiCorp Vault or equivalent.
  • Reliability & Security
    • Embed SRE practices: SLOs, error budgets, runbooks, on‑call design, and blameless post‑mortems.
    • Integrate security tooling (SAST, DAST, dependency scanning, policy‑as‑code) into delivery pipelines.
    • Design and test disaster‑recovery strategies; automate them where possible.
    • Ensure compliance with client security standards and relevant regulatory frameworks.
  • AI & Emerging Technology
    • Design and operate infrastructure for AI/ML workloads: GPU node pools, model‑serving runtimes (Triton, vLLM, BentoML), and vector database deployments (pgvector, Weaviate, Qdrant).
    • Build and maintain MLOps pipelines model training, versioning, evaluation, and promotion to production using platforms such as Kubeflow, MLflow, or cloud‑native equivalents.
    • Integrate LLM APIs and AI agent frameworks into existing developer platforms, including prompt management, observability, cost controls, and rate‑limit guardrails.
    • Advise clients on AI readiness: data infrastructure, governance, security controls (model access policies, output filtering), and the organisational changes that sit alongside the technical work.
    • Stay current with the fast‑moving AI tooling landscape and bring relevant ideas back to the team and to clients.
  • Client Engagement
    • Lead technical discovery sessions and platform assessments with client engineering and architecture teams.
    • Translate client requirements into clear technical plans and communicate trade‑offs to both technical and non‑technical stakeholders.
    • Coach and upskill client platform and application engineers through pairing, workshops, and code review.
    • Produce high‑quality documentation, architecture decision records (ADRs), and runbooks that clients can own after the engagement.

What We’re Looking For

  • Essential
    • Solid hands‑on experience with at least one major cloud provider (AWS preferred; GCP or Azure accepted).
    • Production experience with Kubernetes and familiarity with the surrounding ecosystem (Helm, ArgoCD / Flux, Karpenter, Cilium, etc.).
    • Strong infrastructure‑as‑code skills, Terraform is the baseline; other tools are a bonus.
    • Practical experience designing or operating CI/CD systems (GitHub Actions, GitLab CI, Tekton, or similar).
    • Comfort working in Linux environments and writing automation in Python, Bash, or Go.
    • The ability to explain complex technical concepts clearly to a mixed audience.
    • A consulting mindset: you care about solving the client’s actual problem, not just delivering a deliverable.
  • Ideal (not required)
    • Hands‑on experience with AI/ML infrastructure: GPU scheduling on Kubernetes, model‑serving runtimes, or MLOps tooling (Kubeflow, MLflow, Ray, etc.).
    • Familiarity with LLM APIs (OpenAI, Anthropic, Bedrock, Vertex AI) and patterns for building reliable, observable AI‑powered applications.
    • Experience with vector databases or semantic‑search infrastructure.
    • Experience with event‑streaming platforms such as Apache Kafka.
    • Familiarity with configuration management tools (Chef, Ansible, or similar).
    • Knowledge of mainframe environments or hybrid‑cloud patterns.
    • Relevant certifications: CKA/CKAD, AWS Solutions Architect, HashiCorp Vault, etc.
    • Prior consultancy or client‑facing delivery experience.

At the company, we believe diverse perspectives lead to better outcomes, and inclusion creates the conditions for everyone to thrive. We are proud to have built a family friendly working environment and have many employees who have caring responsibilities alongside work. We welcome applications from people who require flexibility and will be happy to discuss needs on an individual basis.

We are committed to fostering a culture where all team members feel respected, supported, and empowered to do their best work. We celebrate individuality and our differences and understand that some differences may mean that you require changes made to the interview process. We are happy to cater to your needs to make the interview accessible, if this is something you require please let us know by emailing us at hr@unitedstatesdigital.space.

AI Platform Engineer employer: United States Digital Space LLC

At our engineering consultancy, we pride ourselves on fostering a collaborative and inclusive work culture that prioritises employee well-being and professional growth. As an AI Platform Engineer, you will have the opportunity to work with cutting-edge technologies across diverse industries while contributing to meaningful projects that drive innovation. Our commitment to work-life balance, flexible arrangements, and continuous learning ensures that you can thrive both personally and professionally in a supportive environment.

United States Digital Space LLC

Contact Details:

United States Digital Space LLC Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land AI Platform Engineer

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at United States Digital Space LLC or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to United States Digital Space LLC.

Tap into Online Developer Communities

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Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like United States Digital Space LLC that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace AI Platform Engineer

Cloud Provider Experience (AWS, GCP, Azure)
Kubernetes Management
Infrastructure-as-Code (Terraform, Pulumi, CDK)
CI/CD Systems (GitHub Actions, GitLab CI, Tekton)
Linux Environment Proficiency
Automation Scripting (Python, Bash, Go)
Technical Communication Skills

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at United States Digital Space LLC.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at United States Digital Space LLC and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at United States Digital Space LLC

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If United States Digital Space LLC uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.