Work with Azure, Terraform, Azure DevOps, container platforms, and AI agents to build and automate cloud infrastructure. You will design deployment pipelines, observability, and engineering tooling that enable rapid delivery of both AI-powered and traditional cloud-native applications.

EXL Service★3.7 (2k)· London

You will work with Python, FastAPI, LLM frameworks (prompt engineering, RAG, agentic systems), and cloud AI platforms (Azure OpenAI/AWS Bedrock/Claude) on Kubernetes. As a Sr. AI Architect & Client Partner at EXL, a data and AI services company, you will design and deliver production-grade Generative and Agentic AI systems for enterprise clients, converting ambiguous mandates into secure, scalable solutions while shaping deals and reusable IP.

This role develops generative AI applications using Java, Python, React or Angular, LangChain, LlamaIndex, Hugging Face, Docker, Kubernetes, and AWS, with tools like GitHub Copilot. You will build scalable, AI-powered solutions for Citi’s global finance operations.

Lead a hands-on founding engineering role building AI agents for data privacy compliance at Pyxos. Own the control plane, agent architecture, model-abstraction layer, telemetry, evaluation harnesses, and expert knowledge system using LLMs, multi-step agentic workflows, and CI/CD pipelines. You will work with a production system serving enterprise customers, hiring a deliberately small team as the most senior technical leader reporting to the CEO.

You will work with Python, SQL, OpenAI, Azure OpenAI, LangChain, RAG architectures, vector databases (Pinecone, FAISS, Azure AI Search), Azure, AWS, Databricks, and CI/CD tools. As part of Finalto’s AI Innovation team, you will design and deliver AI-powered workflows—such as document processing, bank statement parsing, and news summarisation—that replace manual processes across the business.

AXIS Capital★5.0 (1)· London

You will work with Python, Azure AI services (Azure OpenAI, Azure AI Search), Git, LangChain, Semantic Kernel, and MLOps tools for model versioning, deployment, and monitoring. As deputy to the Head of Data Science & AI Delivery, you lead the day-to-day execution of AI delivery across strategic projects and use cases for AXIS Capital, a specialty insurance and reinsurance provider. You directly manage and contribute hands-on to technical design, code reviews, and solution delivery for a growing team of Data Scientists and AI Engineers.

bp★3.8 (5.2k)· London

You will work with Python, Java, Azure, LLMs, vector DBs, and RAG patterns, using tools like LangChain, Haystack, and Hugging Face. As part of bp's AI organization, you will design and deploy scalable, production-grade AI applications such as conversational bots and AI-powered search for the oil and energy sector.

U.S. Bank★3.5 (12k)· London

Work with CI/CD (GitLab, Jenkins, Harness), Terraform, AWS (ECS/EKS, Lambda, S3, IAM), Docker, Kubernetes, OpenTelemetry, CloudWatch, and Python/Bash. You own the deployment, operations, and reliability of the AI‑SDLC platform as it transitions from local execution to a centralized, hosted enterprise service.

At Axon Labs you will own production infrastructure across multi-region cloud and latency-sensitive environments using AWS, Python, C++, Kubernetes, Terraform, CI/CD, PostgreSQL, TimescaleDB, Kafka, Redis, low-latency messaging, Grafana, Prometheus, and Loki. The company is a systematic trading and research lab that builds decision engines running in live markets, with multiple strategies already in production across venues.

The role involves Python, FastAPI, Docker, Kubernetes, CI/CD, MLOps tools (MLflow, Weights & Biases), and workflow orchestration (Airflow, Prefect, Kubeflow) for deploying and monitoring ML models in production. You'll build and maintain ML infrastructure, pipelines, and observability for an edge computing environment at a company scaling its ML platform.

You will work with Python, Java, Azure, LLMs, vector DBs, RAG, and frameworks like LangChain, Haystack, Hugging Face, and Crew AI. The AI organization builds and deploys scalable, production-grade AI-powered applications for business value within the oil and energy/HR technology sector.

Build and manage CI/CD pipelines (GitLab/Jenkins/Harness), infrastructure as code (Terraform), and AWS cloud services (ECS/EKS, Lambda, S3) with Docker and Kubernetes for the AI‑SDLC platform. Ensure platform reliability, monitoring (OpenTelemetry, CloudWatch), and operational support, while driving the centralized, hosted enterprise service through automation and security compliance. This role is within the team at Elavon, a U.S. Bank subsidiary building tailored payment solutions.

bp★3.8 (5.2k)· London

Design, develop and maintain production-grade AI applications using Python, Java, microservices, AWS/Azure/GCP, CI/CD, LLMs, vector DBs, RAG, and tools like LangChain, Haystack, Hugging Face, Weaviate, and LlamaIndex. The team builds scalable AI-powered applications—including conversational bots, AI search, unstructured data processing, and generative BI—to solve high-priority business problems.

Citi★3.9 (21k)· London

Build and scale AI-powered financial systems using Java, Spring, React/Angular, Python, FastAPI, Docker, and GitHub Copilot within Citi’s global tech environment. You will design generative AI agents, LLM workflows, and RAG pipelines while working on enterprise microservices, mobile, or front-end development. This role is for an individual contributor on an agile team.

You'll work with Python, FastAPI, PydanticAI, Langgraph, Langchain, React, AWS or GCP, and containerization/infrastructure-as-code to build production AI systems. The role involves full-stack development—front and back-end—for a FinTech firm's internal AI Centre of Excellence, delivering GenAI solutions including chatbots, assistants, and workflow automation across the enterprise. The team is expanding and expects to triple headcount this year.

Productionise GenAI and agentic systems using Python, FastAPI, LangGraph, LangChain, or similar frameworks, along with Docker, GitHub, CI/CD, and AWS. You will design APIs and backend components that integrate LLMs with tools and data sources, bridging the gap between prototypes and production systems for the energy and commodity market intelligence provider Argus Media. As a senior member of the Data Science team, you will mentor colleagues and set engineering standards.

Work with Python, TypeScript, LLMs, RAG pipelines, agent architectures, MCP, eval frameworks, CI/CD, and cloud (AWS/GCP preferred). You will join a small pod to deliver end-to-end AI client engagements—building prototypes, MVPs, and integrating into enterprise environments.

Fitch Ratings★3.8 (136)· London

You'll build ML/AI solutions using Python, FastAPI, PyTorch/TensorFlow, LangChain, LangGraph, and React/TypeScript within cloud-based microservices architectures. The agile team delivers software products for Fitch's BMI business, which provides data-driven market insights and risk analysis to customers globally. You'll design full-stack enterprise applications, implement GenAI features with LLM integration, and establish development best practices across the product suite.

FDM Group★2.9 (270)· London

The role involves Python, Java, microservices, CI/CD, cloud (AWS/Azure/GCP), LLMs, vector DBs, RAG, AI agents, and frameworks like LangChain, Haystack, Hugging Face, Weaviate, LlamaIndex, Crew AI, AutoGen. The team builds scalable AI-powered applications (conversational bots, AI search, unstructured data processing, GenBI) for a client in the energy sector.

Build and operate a Kubernetes-native cloud platform for GPU inference workloads, using Python or Go. You'll lead technical designs, own areas like request routing and adaptive scheduling, and implement optimizations such as speculative decoding and KV-cache reuse, working with Prometheus, Grafana, and OpenTelemetry.

Deloitte★3.9 (14k)· London

You will work with Python, JavaScript, Kafka, Azure, Kubernetes, Terraform, Helm, LangChain, PySpark, Databricks, and ADLS. You will design, develop, and deploy production-grade GenAI and machine learning systems for the GenAI team within Deloitte’s Data & AI organisation.

Circadia Health's ML Ops Engineer will work with Apache Airflow, AWS (Batch, EC2, S3, IAM, CloudWatch), MLflow, Docker, Python, Git, SQL, Snowflake, and edge devices. You own the ML infrastructure and pipelines for a clinical monitoring platform that identifies early signs of clinical deterioration using predictive models in cloud and edge environments.

You will work with Python, LLMs, GenAI architectures, RAG, embeddings, vector search, AI agents, LangChain, LlamaIndex, LangGraph, Semantic Kernel, AutoGen, Docker, Git, CI/CD, and Azure/AWS/GCP. You build and deploy production-ready GenAI and agentic AI solutions for clients, including RAG architectures and intelligent assistants. You are an individual contributor on multidisciplinary client teams, co-creating solutions from ambiguity to execution.

You will work with Python, Kubernetes, LangChain, LangGraph, DSPy, LlamaIndex, OpenAI, and Anthropic to build and operate scalable services, APIs, and cloud-native infrastructure. You will design and deploy an enterprise AI platform for a leading investment firm, enabling secure consumption of Generative AI and autonomous systems across the business.

CMC Markets★3.8 (26)· London

You will work with Python, PyTorch, containers, model serving frameworks, and cloud infrastructure. You’ll own the reliability and scalability of machine-learning systems, building data pipelines, CI/CD, and monitoring for production models. This is a hands-on engineering role focused on making ML systems dependable at scale.