Lead, coach, and mentor engineers using Java and JavaScript frameworks. The client is a healthcare provider building modern, scalable products to deliver world-class patient experiences across the UK as part of a digital transformation.

Glasswall★0.0· London

Lead a small team of DevSecOps and Software Assurance Engineers, owning product security posture, threat modelling, and security tooling (SAST, DAST, SCA). Drive DevSecOps strategy, embed security into the SDLC, and champion agentic AI adoption using tools like Claude Code or CoPilot. This is a hands-on leadership role at a file protection company, reporting to the CTO.

Google★4.3 (6.2k)· London

Work with Python, Java, Go, C or C++, large language models, prompt development, and conversational AI frameworks. As an AI Solutions Deployment Manager on the Google Cloud Consulting Professional Services team, you guide customers through their cloud journey and help deliver agentic AI solutions for Google’s most strategic global clients.

You'll lead a 6-7 person team owning core ML infrastructure—distributed model training, LLM hosting/fine-tuning, and scalable deployment—using Python heavily with working C++/Java, at a top systematic quant fund. This hands-on engineering manager role drives ML into high-stakes production systems.

Manage a team of Data Engineers building scalable data pipelines and cloud-based data platforms using Python, SQL, and Azure/AWS/GCP. You will design robust ETL/ELT processes, data models, and warehouses, enforcing CI/CD and Git best practices.

Wells Fargo★3.6 (48k)· London

You'll work with Python, SQL, cloud and DevOps practices, AI/ML and Large Language Models, plus Axiom ControllerView on the Enterprise Functions Technology team. The role enhances and supports regulatory reporting platforms used by Wells Fargo's Finance Controllers organization.

Lead squads building core product features for AI agent management, including LLM proxies, MCP server orchestration, and A2A protocol governance. Leverage API and event management platforms and champion AI-assisted development tools (Cursor, AI code review, automated testing). Gravitee delivers a platform for governing APIs, events, and AI agents.

Lead engineering squads building core product features for AI agent management, including LLM proxies, MCP server orchestration, and A2A protocol governance. The role involves working with AI-assisted development tools (Cursor, AI code review, automated testing) to create infrastructure that secures and governs autonomous AI agents. Gravitee provides an API and event management platform trusted by global enterprises.

Works with Java, integration patterns, CI/CD, observability, and cloud-native services, building reusable build kits, connectors, and platform services. As Engineering Manager in Integration at Sainsbury's Tech, leads a multi-skilled engineering team creating common integration capabilities that standardize how integrations are built, deployed, and operated across the retail business.

Engineering Manager at Gravitee, working with API/event management platforms, LLM proxies, MCP, A2A protocol, and AI-assisted tools like Cursor. The squad builds core product features to secure and govern AI agent ecosystems. Gravitee delivers a platform for Any API, Any Event, and Any AI Agent.

NatWest Group★3.7 (1.2k)· London

Leading a team building cloud-hosted, event-driven microservices at NatWest Boxed, you will manage software and quality engineers across empowered squads while working with AWS, Google Cloud Platform, Java, Python, JavaScript, ReactJS, AngularJS, Kafka, Hadoop, PostgreSQL, Snowflake, and GitLab.

Lead a team building scalable cloud-hosted systems using Java, Python, ReactJS, AWS, and Google Cloud Platform. This engineering manager role owns technical stewardship for product mission teams within NatWest Boxed, a high-performing product engineering organisation. Direct reports include software and quality engineers across empowered squads.

You will work with Python (FastAPI), AWS, LLMs (OpenAI, Gemini, Anthropic), RAG, agentic workflows, MCP servers, and CI/CD pipelines. This player-coach role leads a squad building AI-driven solutions for BCG’s internal products and processes, delivering GenAI applications while cultivating engineering talent.

Deloitte★3.9 (14k)· London

Work with Python, CI/CD, PyTorch, MLFlow, FastAPI, Azure (Fabric, Data Factory, ML Studio, Synapse, Cosmos), and LLM tools (RAG, embeddings). You will lead end-to-end AI/ML projects for Deloitte’s Tax & Legal Data and AI Studio, delivering analytics and AI-driven client solutions.

You will lead a data engineering squad working with cloud-native technologies (AWS, GCP), event streaming (Kafka), and data-mesh tooling, using Python or Go and infrastructure-as-code (Terraform, Crossplane). The team owns NatWest Boxed’s data platform to enable business units to ingest, manage, and leverage data for strategic requirements. You will guide a high-performing engineering squad.

FDM Group★2.9 (270)· London

Lead multiple cross-functional engineering teams for a banking/lending technology programme at a financial services client. Oversee ~20 engineers across 3-4 feature teams using Java, Spring Boot, React/React Native, and cloud-based solutions. Drive DevOps, CI/CD, secure coding, and platform modernisation.

AWS, Kubernetes/EKS, Java, Go, TypeScript. Owns a process orchestration platform end-to-end, managing the engineering roadmap, vendor upgrades, and internal improvements across consuming teams. Stays hands-on with code and architecture.

You will work with AI/LLM technologies, ecommerce platforms, CRM/sales tooling, marketing/omnichannel systems, and data engineering. You lead the commercial technology stack powering ecommerce, sales, marketing, and customer systems, including integrating an AI platform. The team of about 15 spans web engineering, data engineering, and CRM administration.

BNY★3.5 (5.5k)· London

Lead AI solution development on BNY’s ELIZA platform, working with LLMs/NLP, agentic systems, and retrieval architectures. You will set technical direction across pods, mentor juniors, and contribute to the AI Hub’s standards and reference architectures.

Lead security tooling including SIEM, EDR, and vulnerability management, and own the ISO 27001 and SOC 2 certification programmes. Acting as the primary client-facing security contact, you will manage due diligence and standardised questionnaires (SIG, CAIQ) for AccessFintech’s capital markets platform. You will report to the CTO and work across engineering, product, and operations teams.

Sainsbury’s★3.5 (16k)· London

You will work with Java, integration patterns, CI/CD, observability, and cloud-native services to build reusable build kits, common components, and platform services. Your team delivers integration capabilities that standardise how integrations are built, deployed, and operated, reducing repeated engineering effort and accelerating delivery across Sainsbury’s Tech.

Quantspark★0.0· London

Lead a small team of data and AI engineers using Python (Flask/Django), Pandas, and React.js on containerised, cloud-based systems (AWS/Azure). QuantSpark is a data and AI consultancy of around 50 people building working systems for clients across financial services, retail, manufacturing, and more.

FDM Group★2.9 (270)· London

Senior Engineering Manager leading ~20 engineers across 3-4 feature teams, working with Java, Spring Boot, React/React Native, AWS, DevOps, CI/CD, SonarQube, Veracode, Jira, and Confluence. The role delivers critical banking and lending technology programmes, including platform modernisation and large-scale migration.

Boston Consulting Group★4.2 (537)· London

You will work hands-on with Python (FastAPI), LLMs (OpenAI, Gemini, Anthropic), cloud-native development on AWS, and CI/CD pipelines. As a player-coach in an AI/ML squad at Boston Consulting Group, you will build and deliver GenAI products leveraging RAG, agentic workflows, and MCP servers. You will lead and mentor a team of engineers, acting as both a contributor and architect.

Build and lead a Forward Deployed Engineering unit from a founding cohort of 8-12 to a 100+ person team, using Domain-Adapted and Small Language Models, LLM fine-tuning, RAG, agentic workflows, MLOps, and evaluation frameworks. Deploy AI systems for regulated clients in priority sectors like data centres and energy, defining the operating model and owning productivity metrics.