DevOps / Infrastructure AI Engineer

DevOps & Cloud Infrastructure Engineer | Enterprise AI Incubator @ Large Asset Mgmt Firm

• Location: London, UK (Hybrid / Onshore EU remote flexibility considered)
• Engagement: Initial 9-month contract (Inside IR35; established precedent for permanent conversion)
• Industry: Global Asset & Investment Management
• Compensation: £800 per day (inside IR35)

About the Organisation

Our client is one of the world’s largest and most established active investment managers, stewarding trillions in global assets under management. Known for operating an exceptionally lean, high-calibre global workforce of the firm combines institutional stability with autonomous, forward-thinking innovation.

As part of an aggressive international expansion strategy across Europe and Asia, the firm has established a high-velocity AI Incubator.

Rather than relying on traditional, centralised IT models, our pod embeds directly alongside strategic business verticals (Marketing and Sales/Distribution) to design, build, and deploy production-grade, agent-enabled AI solutions from 0-to-1.

The Role

We are seeking a Senior DevOps / Cloud Infrastructure Engineer to take end-to-end ownership of cloud provisioning, landing zones, and Kubernetes deployment pipelines within the dedicated AI Incubator pod.

In the initial project stages, infrastructure automation, deployment guardrails, and environment provisioning consume up to half of the squad’s technical capacity. You will serve as the pod’s infrastructure anchor—ensuring our Python microservices and multi-agent AI runtime integrate seamlessly, securely, and ability to scale, within firm-wide platform guardrails.

This is a fast-paced environment where the learning curve is expected to be "day one". You will need to be an autonomous builder who thrives on end-to-end ownership: authoring technical design specifications, collaborating directly with engineering leadership, and delivering without waiting for rigid task queues.

Key Responsibilities:

• Cloud & IaC Provisioning: Architect, codify, and manage secure AWS infrastructure using modular Terraform / Terragrunt.
• Container Orchestration: Deploy, scale, and maintain containerised microservices and namespace configurations on Kubernetes (EKS).
• CI/CD & GitOps: Build resilient, automated CI/CD pipelines (GitHub Actions / GitLab / ArgoCD) enforcing automated testing, security scanning, and seamless promotion between environments.
• Enterprise AI & Runtime Integration: Establish secure network routing, IAM policies, and API gateway connections between pod microservices and the firm’s central AI gateway/agent runtimes.
• Observability & Reliability: Implement unified logging, metrics, and distributed tracing across workflows, model integrations, and databases using OpenTelemetry, Datadog, or Prometheus/Grafana.
• Security & Governance: Enforce strict IAM least-privilege policies, secret management, and zero-trust controls in compliance with institutional financial standards.

Candidate Profile & Core Requirements:

• Track Record & Stability: Demonstrated career stability (ideally 2+ years per tenure in recent roles) with proven experience delivering production-grade systems in enterprise or regulated environments.
• Deep Cloud & IaC Acumen: Expert-level hands-on experience provisioning and maintaining AWS platforms using Terraform.
• Production Kubernetes: Strong hands-on experience deploying, managing, and troubleshooting workloads in production Kubernetes clusters.
• Observability Champions: Practical experience instrumenting distributed tracing, latency tracking, and operational metrics (OpenTelemetry / Datadog).
• Autonomous Operating Mindset: Highly proactive and self-directing; comfortable exploring codebases, partnering with lead engineers and product managers, and driving technical design to completion independently.

Desirable / Bonus Skills:

• Exposure to modern AI engineering ecosystems, LLM gateways, vector databases, or orchestration frameworks (LangGraph, LangChain, Bedrock).
• Familiarity with PostgreSQL (Aurora), Apache Kafka, and AWS S3 storage architectures.
• Background in financial services, FinTech, or wealth management platforms.

Interview process comprises of ONE STAGE (45-60 minute tech deep dive)