Tesco★3.5 (25k)· London

You will work with Java, Spring Boot, Kafka, Apache Flink, Apache Beam, NoSQL databases, Redis, and Apache Camel. The Tesco Personalisation team builds real-time, low-latency services for recommendations, offers, and experimentation across web, mobile, and in-store channels using streaming data and ML.

Lead 6-7 engineers on core ML infrastructure for a systematic quant fund: distributed model training, LLM hosting/fine-tuning, and scalable deployment. Use Python with working knowledge of C++/Java. Own technical direction for real-world, high-stakes systems.

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.

Google★4.3 (6.2k)· London

Manage engineers building Google’s Learning Platforms within the Global Business Organization, which powers Google’s ecosystem of products and services for customers and partners. Work with back-end languages (Java, Python, Golang, C++) and front-end (JavaScript, TypeScript, HTML, CSS), plus ML model fine-tuning and evaluation.

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.

Work with Nvidia GB200 72NVL CX8 and AMD MIxxx architectures, coding in C, C++, C#, Java, JavaScript, or Python to benchmark, profile, and debug GPU clusters. You will help build foundational models powering Microsoft’s personalized AI assistant, Copilot, spanning training and inference infrastructure, model architecture, and data curation.

Build production-grade generative AI systems using Python, LlamaIndex, LangChain, LangGraph for RAG pipelines and agentic workflows at an award-winning B2B consultancy. Emphasizes evaluation for correctness and reliability, with hands-on technical leadership and mentoring.

White & Case★4.0 (120)· London

Works with Python, JavaScript, MCP, agentic AI frameworks, LLMs, and cloud platforms (Azure, AWS) to architect and deploy AI tools. As technical lead of the Applied AI Lab, the role oversees design, development, testing, and deployment of AI solutions to support legal practice and firm-wide innovation. Manages and develops a multidisciplinary team of legal engineers.

ByteDance★3.8 (238)· London

Embedded in customer environments, you will rapidly develop and debug AI applications using Prompt Engineering, Fine-Tuning, RAG, and Agent frameworks like LangGraph or CrewAI, integrating with cloud service APIs/SDKs. You will build production-grade Agent systems, evaluation pipelines, and observability frameworks. This role is with ByteDance, the company behind products such as TikTok.

You will work with Python, JavaScript, Model Context Protocol (MCP), agentic AI frameworks, LLMs, and cloud platforms (Azure, AWS). As technical

ByteDance★3.8 (238)· London

Embedded in customer environments, this role rapidly develops and debugs AI applications (Prompt Engineering, RAG, Agent systems) using cloud architecture, Vibe Coding, and frameworks like LangGraph or CrewAI. The BytePlus team builds production-grade Agent systems integrated with customers’ APIs and data systems.

Develop and debug AI applications in production, using Vibe Coding, Prompt Engineering, RAG, and Agent frameworks like LangGraph or CrewAI. You will build prototypes and production-grade Agent systems within customer environments, integrating with their APIs and data systems. You’ll design cloud architectures and create observability frameworks for accuracy and latency.

Build agentic workflows in Python with LangGraph or LangChain, vector databases, and LLMs for a real-time AI Tutor and AI Creator. You will own production systems end to end, optimizing for cost, latency and reliability at scale, while mentoring a small team.

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.

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.

You'll develop Conveo's AI-powered consumer and B2B research platform using React, TypeScript, Node.js, PostgreSQL, and AWS/GCP infrastructure, with exposure to LLM APIs and prompt engineering. The role spans full-stack development—from API design to frontend implementation—plus direct customer interaction to translate research needs into technical solutions. You'll work autonomously on feature ownership within a small, high-performing engineering team at this Y Combinator-backed startup.

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.

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 high-throughput data pipelines, deploy LLMs and ML models, and develop AI tooling working with Python, Spark, Databricks, Airflow, Kafka, KDB, AWS/GCP/Azure, and Kubernetes. The role supports a global investment firm where technology drives performance, building data platforms and AI systems directly used by Portfolio Managers to uncover alpha.