Infosys★3.8 (17k)· London

You will architect CI/CD pipelines using the Harness platform (CI, CD, STO, Chaos Engineering, CCM, AI Agents), Kubernetes, Terraform, Helm, OPA, and cloud services. As a Harness SME, you drive DevOps transformations, migrating enterprise teams from legacy tool chains and implementing DevSecOps governance.

Work with Python, LLMs, RAG pipelines, vector databases, Hugging Face Transformers, LangChain, PyTorch, and Docker to build production AI systems. Design, develop, and deploy AI-powered solutions such as conversational AI, document intelligence, and backend services for the Global Analytics team.

Lovable★4.0 (43)· London

Uses Go, Rust, TypeScript; AWS, Azure, Google Cloud, Cloudflare; Kubernetes, Terraform, Temporal, OTEL, CI/CD; PostgreSQL, ClickHouse, Firestore, Spanner, BigQuery. Builds the platform for Lovable Enterprise enabling secure, cloud-agnostic deployment, defining architecture for sandboxing, networking, encryption, identity, and mentoring engineers.

Salesforce★4.2 (1.5k)· London

Success Architect works with Agentforce, Data Cloud, Salesforce Clouds, and data platforms like Snowflake, Databricks, AWS. They drive customer success by optimizing technical architecture for data unification and AI-driven automation, enabling personalized engagement and real-time decision-making.

A Senior AI Engineer at Stakemate will use agent frameworks (LangGraph, LlamaIndex, Semantic Kernel, ADK), RAG, Python, cloud services (Azure/GCP/AWS), and SQL to move AI from experiments to production. They will shape the platform and architecture for a live betting product at a fast-growing social sports betting startup.

You will work with agent frameworks (LangGraph, LlamaIndex, Semantic Kernel, ADK), RAG pipelines, vector stores, Python, SQL, and a major cloud (Azure AI Foundry, GCP, or AWS). You will take AI agents from proof-of-concept to production within Stakemate’s live sports betting product, setting the governance and standards for the company’s AI estate. Reporting to the CTO, you will shape the platform and architecture as the company scales.

You will work with C++, Python, Linux, machine-learning libraries, Google Cloud, Airflow, InfluxDB, and Grafana. This role builds data engineering and prediction tools for systematic equity trading, developing software for quantitative research, maintaining data pipelines, and implementing large-scale computation and serialization frameworks.

Design, build and deploy production Generative AI applications, LLM-powered solutions and agentic frameworks using Python, LangChain, LangGraph, and OpenShift. You will automate enterprise workflows with intelligent agents, working with PostgreSQL and pgvector as part of Citi’s COO-Technology team building scalable AI for global operations. This is an Individual Contributor Staff Engineer role.

Build and maintain scalable data pipelines (BigQuery, Cloud Composer, Airflow, Dataflow, Spark, Flink, dbt) on GCP for AI/ML experiences. Use Docker/k8s, Terraform, SQL, shell scripting, and monitoring tools (Monte Carlo, Looker, NewRelic, Splunk). Collaborate with product engineering, data science, and business teams.

Google★4.3 (6.2k)· London

Google Cloud AI offerings (Vertex AI, Gemini), modern multi-agent systems (LangGraph, CrewAI). This role drives Gemini Enterprise adoption by industrializing AI excellence, moving licenses to activated, and ensuring production-grade deployment of AI agents and workflows. It leads the GE Accelerator efforts.

As an Enterprise Sales Engineer, you will use Neo4j and the Cypher query language, Terraform for IaC, REST APIs, Apache Kafka/Confluent, plus Python, JavaScript, React and Go. You will be a trusted technical advisor, guiding enterprise customers through deploying the client’s platform for secure, governed AI, and will partner with Sales, Customer Success and Partner teams. The listing does not specify team size.

Deloitte★3.9 (14k)· London

You will use Figma, React, TypeScript, and HTML/CSS to design and front-end code AI-powered agentic experiences, including conversational interfaces and agent-orchestration workflows for clients. The team reimagines how users interact with intelligent platforms, developing trust-centered, multi-step AI interactions. You will manage design workstreams and mentor junior designers and front-end developers.

Moody's★3.6 (589)· London

You will work with Python, TypeScript, Java, or Go; cloud platforms (AWS, GCP, Azure); Docker, Kubernetes, PostgreSQL, MongoDB, Redis, vector databases; and build AI applications using LLMs, RAG, prompt engineering, and AI agents. The Innovation team builds next-generation internal and external products powered by large language models, AI agents, machine learning, and natural language processing.

You'll work with frontend (TypeScript, React, Angular, Vue, Next.js, Tailwind), backend (Python, Node.js, Java/Spring, C#/.NET), databases (SQL, NoSQL, vector databases), LLM frameworks, and cloud platforms (Azure, AWS, GCP) including Docker and CI/CD. QuantumBlack, an AI division of McKinsey, builds industry-shaping products and tools across diverse industries by pairing software engineers, AI engineers, and data scientists with client leadership. As a Senior Software Engineer, you'll lead architecture design, mentor teams in engineering excellence and Agile practices, and drive technology decisions on scalable solutions.

You'll build scalable data infrastructure for AI applications using Python, SQL, Spark, dbt, LangChain, and cloud platforms (AWS, Azure, GCP), working with data pipelines, embeddings, vector search, and LLMOps tools like Terraform and LangSmith. QuantumBlack, McKinsey's AI division, develops next-generation AI systems and enterprise solutions for clients across industries. You'll collaborate with Data Scientists and ML Engineers in cross-functional Agile teams based in London, supporting the firm's AI adoption and complex problem-solving at scale.

Pipedrive★4.2 (5)· London

Lead a growing team of Applied Scientists and AI/ML Engineers at Pipedrive, a cloud-based CRM platform serving over 100,000 companies. You'll own the technical strategy for AI/ML solutions working with structured CRM data and unstructured content, designing autonomous agentic workflows using LangGraph, RAG architectures, vector databases, and LLMOps infrastructure. The role requires 8+ years of applied ML/AI experience in production environments, deep expertise in modern AI engineering, cloud infrastructure (AWS/GCP), and distributed systems, with proven ability to lead and scale technical teams.

Build with Python, Go, or Java on the backend, and React/TypeScript on the frontend, using PostgreSQL and non-relational stores, with Docker, Kubernetes, and cloud infrastructure (AWS, GCP, Azure). This role owns full-stack delivery of the B2B product—a campaign, device management, and insights platform for retail and brand partners—along with API design and distributed systems. The team includes engineers, product, and platform groups, working closely with the Head of B2B Product.

DeepL★3.8 (4)· London

You will work with C#, Python, and JavaScript to build full-stack features on the Media Translation team, which develops DeepL’s core translation products—including the consumer web translator, Enterprise Customization Hub, and multimedia localization flows.

You'll work with Python and/or TypeScript, using full-stack JavaScript or backend Python. The role is a founding engineer at a stealth AI company backed by a £100M bootstrapped founder with three successful exits.

Lead engineers use Java, C#/.NET, Python, TypeScript, JavaScript, React, Go, Ruby, Scala, R, and SQL; Git, MacOS/Linux, and CI/CD; and AI-assistive tools. They lead multi-client software consultancy engagements, building and delivering production agentic systems and ML-powered features. The team is typically one to two clients per year.

Deloitte★3.9 (14k)· London

You will work with large language models, prompt engineering, retrieval-augmented generation, orchestration frameworks, and cloud platforms (Azure, AWS, GCP). As a GenAI Solution Design lead in Deloitte's AI Scaling & Transformation team, you design enterprise-grade GenAI solutions for Security & Justice clients in regulated environments. This Senior Manager role involves overseeing delivery across multiple workstreams and leading mentoring delivery teams.

Palantir★3.9 (37)· London

You’ll work with Java, C++, Python, TypeScript, JavaScript, Kubernetes, Cassandra, Chromium, and open-source tools. As a new-grad infrastructure engineer, you’ll contribute to the shared infrastructure behind Palantir Foundry, Gotham, and Apollo—platforms deployed at key public- and private-sector institutions—as well as to Rubix and Mission Manager for sensitive environments. Teams are small, focused on backend, developer, frontend, or storage infrastructure, or on production infrastructure including a Kubernetes-based PaaS, Apollo, and Signals.

Palantir★3.9 (37)· London

Interns work with Python, Java, C++, TypeScript/JavaScript, LLM workflows, and cloud infrastructure. They embed with customers to build custom applications and production solutions for high-stakes problems, such as predicting wildfire risks or optimizing global supply chains.

Palantir★3.9 (37)· London

You'll use Java, Go, and TypeScript alongside open-source tools like Cassandra, Spark, Elasticsearch, React, and Redux with Gradle and GitHub. You'll contribute to Palantir Gotham, Apollo, or Foundry—data platforms deployed across critical institutions.

Palantir★3.9 (37)· London

You will work with Python, Java, C++, TypeScript/JavaScript, LLM workflows, and cloud infrastructure. As a Forward Deployed Engineer, you embed with customers to solve mission-critical problems by deploying software and AI into their high-stakes operations. You own projects end-to-end in small, high-trust teams.