At a Glance
- Tasks: Design and build cloud-native AI platform infrastructure using AWS and Databricks.
- Company: Award-winning B2B consultancy leading in enterprise AI innovation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Join a dynamic team focused on scalable and secure AI solutions.
- Why this job: Make a real impact on cutting-edge generative AI products and work with industry leaders.
- Qualifications: Experience in platform engineering, Kubernetes, and Terraform is essential.
The predicted salary is between 60000 - 80000 £ per year.
Join an award-winning B2B consultancy at the forefront of enterprise AI, building and owning the cloud-native platform infrastructure that powers production-grade conversational and generative AI products at scale.
The role is a platform and infrastructure engineering role - not a data science or ML engineering position. You'll own the runtime, infrastructure, and operational layers that RAG pipelines, LLM orchestration, vector search, and evaluation workflows run on, across AWS and Databricks. The focus is on building scalable, observable, secure, and cost-efficient platform infrastructure that enables AI engineering teams to ship and operate AI products reliably in production.
What you’ll do:
- Design, build, and operate cloud-native AI platform infrastructure across AWS (Lambda, API Gateway, DynamoDB, S3, CloudWatch) and Databricks.
- Deploy and operate containerised services on Kubernetes using Terraform for infrastructure-as-code.
- Own and scale vector search infrastructure (OpenSearch, Algolia, AWS Bedrock Knowledge Bases) and embedding pipelines.
- Build and maintain CI/CD pipelines for inference services, retrievers, ingestion workflows, and RAG components.
- Implement observability across AI workloads using CloudWatch, MLflow, and OpenTelemetry - covering latency, throughput, cost, and system health.
- Apply secure-by-design principles including IAM, encryption, network controls, and audit logging.
- Work closely with AI engineers to translate prototypes and proof-of-concepts into production-ready, well-architected platform components.
What we’re looking for:
- Proven experience in platform, infrastructure, or software engineering roles delivering production-grade systems on AWS.
- Strong hands-on Kubernetes experience, specifically with EKS (Elastic Kubernetes Service) and ECS (Elastic Container Service) in production environments.
- Strong Terraform experience for infrastructure-as-code, provisioning and managing cloud infrastructure at scale.
- Experience operating containerised services, managing CI/CD pipelines, and owning observability and reliability.
- Familiarity with vector databases or search infrastructure (OpenSearch, Algolia) is a strong advantage.
- Python proficiency for scripting, automation, and deploying production services.
- Solid grasp of distributed systems, cloud-native architecture, microservices, and API design.
- Ownership mindset — comfortable operating autonomously across reliability, performance, cost, and security.
Why join?
You’ll own the foundational platform infrastructure behind a growing suite of generative AI products, working directly with senior AI and engineering leaders. This is a deep technical ownership role with long-term architectural impact, within an organisation investing heavily in AI at scale.
AI Platform/ DevOps Engineer. Job in London Move Collective Jobs employer: Broughton Group
Join an innovative B2B consultancy in London that is at the cutting edge of enterprise AI, offering a dynamic work culture that fosters collaboration and creativity. With a strong focus on employee growth, you will have the opportunity to take ownership of critical platform infrastructure while working alongside industry leaders in AI and engineering. The company provides a supportive environment with competitive benefits, ensuring that you can thrive both personally and professionally as you contribute to impactful AI solutions.
