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.

Lovable★4.0 (43)· London

Build enterprise deployments using Go, Rust, and TypeScript on AWS, Azure, and Google Cloud, with Kubernetes, Terraform, and Temporal. You will build the platform that allows large customers to run Lovable securely and at scale across every major cloud provider.

You will work with Azure (AI Foundry, AI Search, Cosmos DB, API Management, observability), Langfuse, Datadog, LiteLLM, MCP gateways, contemporary AI models, agent harnesses (Claude Code, Codex, GitHub Copilot), OpenTelemetry, LangChain, LangGraph, and Azure document-processing services. The team builds and experiments with AI agents and retrieval-augmented generation (RAG) systems at LSEG, a global financial markets infrastructure and data company. The role is at the Manager career stage.

LSEG★3.7 (402)· London

Work with Azure (AI Foundry, AI Search, Cosmos DB, APIM, observability), Langfuse, Datadog, RAG, vector databases, LiteLLM, MCP, contemporary AI models, Claude Code, Codex, GitHub Copilot, OpenTelemetry, LangChain/LangGraph, and Azure AI Document Intelligence. The role is within LSEG, a global financial markets infrastructure and data business. This is

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'll build Python-based backend services and data pipelines with Docker, Kubernetes, and Terraform, integrating enterprise systems like SAP and Oracle ERP while handling multi-terabyte datasets. Magentic develops agentic AI systems for supply chain and procurement workflows, targeting enterprise customers with end-to-end feature ownership from architecture through deployment and iteration.

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.

Lightning AI seeks AI Platform Support Engineers to support ML engineers running large-scale training and inference workloads on Kubernetes and GPU platforms. You'll diagnose distributed PyTorch failures, GPU orchestration issues, and infrastructure problems using tools like Prometheus and Grafana, while partnering with customer engineering teams on production reliability. Required: strong systems troubleshooting, Kubernetes experience, Linux expertise, hands-on ML infrastructure operations with PyTorch and CUDA, and excellent communication with technical customers.

Lead Cloud Engineer role: work with Terraform, Kubernetes, Amazon Bedrock, AWS, and Infrastructure as Code; architect AI-native infrastructure including Vector Databases, RAG architectures, and production-grade Agentic Workflows. The role is with an AI-native consulting partner, delivering cloud, AI, and platform engineering projects for clients such as PayPal and adidas. You will guide and mentor a team of cloud engineers.

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.

You'll work with Java, Spring, AWS Kinesis/SQS/SNS, MongoDB, Redis, PostgreSQL, GraphQL, OpenTelemetry, Datadog, and AI tools (Claude Code, Claude MPM, in-house MCP server). The Dev Platform team owns the architecture and evolution of Duetto's core Java/Spring monolith, which processes millions of hotel rate decisions daily, driving domain decomposition and platform modernisation.

Work with AWS (EC2, EKS, Lambda, S3, IAM, VPC, CDK), Terraform, Kubernetes, Docker, LLM orchestration frameworks (LangChain, Temporal), and AIOps tools like Datadog and Prometheus. As part of Goldman Sachs’ Cloud Engineering & Architecture team, you will architect and build an enterprise-grade platform enabling secure public cloud usage across the firm. This hands-on senior leadership role involves defining technical standards, driving large-scale platform initiatives, and mentoring engineers.

Goldman Sachs★3.9 (2.3k)· London

This role works with AWS (EC2, EKS, Lambda, S3, IAM, VPC, CDK), Terraform, Docker, Kubernetes, and AI tools like LangChain, Temporal, Datadog, and Prometheus. You will design, build, and operationalize enterprise-grade cloud platform capabilities for the Cloud Engineering & Architecture team, enabling Goldman Sachs engineering teams to deploy and manage services in public cloud securely.

You'll work with Python (FastAPI), Go, TypeScript, PostgreSQL, Redis, Pinecone/pgvector, AWS (ECS, Lambda, SQS), Docker, Kubernetes, Terraform, LangChain/LlamaIndex, vLLM, and Anthropic/OpenAI APIs. You'll build and optimize RAG pipelines, real-time inference APIs, and vector search infrastructure powering LLM features for 500k+ monthly active users.

Work with Terraform, Kubernetes, Vector Databases, Retrieval-Augmented Generation (RAG), Agentic workflows, OpenTelemetry, and Infrastructure as Code. As a consulting partner for clients like PayPal and adidas, you lead cloud-to-AI platform engineering, building autonomous platforms and managing AI lifecycles. You also mentor a team of cloud engineers.

Barclays★3.9 (6.9k)· London

You'll work with AWS (Amazon Bedrock, agent orchestration), Python, CI/CD for models/prompts/agents, and LLMOps/AgentOps lifecycles. You'll build and run an enterprise AI Factory within Barclays' Card Merchant Services, operationalizing GenAI and ML platforms for merchant payments—spanning acquisition, risk, fraud, and servicing—with embedded governance and observability.

You will build telemetry pipelines and dashboards using Python, Golang, Kubernetes, Prometheus, Grafana, gNMI, and SNMP across platforms including Arista EOS, NVIDIA Cumulus Linux, and Nokia SR OS. The Network Observability team designs and maintains monitoring systems for CoreWeave’s global GPU cloud network, enabling real-time anomaly detection and automated alerting.

You'll work primarily with React and TypeScript on the frontend, and Python (FastAPI/Flask) on the backend, using tools like Storybook. The Monolith AI Engineering Team builds the core platform for engineering simulation and AI workflows, aiming to become a super-intelligent AI test lab for the engineering industry.

You'll build profiling, tracing, and CLI tooling using tools like perf, Nsight, Tracy, Prometheus, Grafana, and OpenTelemetry for Callosum's heterogeneous compute infrastructure. This role owns the developer experience across the stack, turning complex low-level systems into observable, debuggable tooling for multi-agent inference workflows.

You will work with Python, FastAPI, PostgreSQL, Kafka, MQTT, and modern agentic frameworks like Pydantic AI, implementing LLM agents with RAG and multi-step workflows for a stealth-mode company building behavioural AI solutions to bring machine learning to in-store retail shopping.

Encord seeks a Senior SRE Engineer to build and operate infrastructure for its AI data platform, which indexes and curates data across the ML lifecycle. You'll optimize large-scale data pipelines on GCP and AWS using Kubernetes, manage petabyte-scale storage, define SLIs/SLOs/SLAs, and instrument services with Prometheus, Grafana, OpenTelemetry, and Datadog. You'll collaborate with backend engineers (Python, Rust) and multiple squads to drive reliability, capacity planning, and observability practices as the platform scales from hundreds to thousands of AI teams.

Lovable★4.0 (43)· London

Lovable is an AI-powered software creation platform used by millions to build applications in any language. As a founding Forward Deployed Engineer, you'll work directly with ambitious customers using React, TypeScript, Golang, and Rust alongside LLM providers (Cloudflare, GCP, AWS) to design novel AI systems, translate real-world customer needs into product features, and shape this new function across engineering, product, and research. You'll own end-to-end projects influencing core platform direction with 5+ years full-stack experience and strong architectural thinking.

G-Research★3.6 (18)· London

You'll design and operate large-scale distributed analytics platforms using Spark, Trino, Kafka, ClickHouse and Airflow across on-premises and AWS environments, with infrastructure-as-code (Terraform/Ansible), Linux, Python, and CI/CD tools like Jenkins and ArgoCD. G-Research applies scientific methods to quantitative finance research and trading, and you'll collaborate with research and engineering teams to build highly available, scalable analytics services that accelerate discovery across the firm.

G-Research★3.6 (18)· London

You'll design and operate Kubernetes-based infrastructure using Go or Python to build custom operators, GitOps pipelines (ArgoCD, FluxCD), and Infrastructure as Code (Terraform, Helm), with strong observability via Prometheus and Grafana. The platform supports G-Research's quantitative finance operations, serving GPU-intensive machine learning and ultra-low-latency trading workloads while enforcing multi-tenant security with RBAC and OPA/Gatekeeper.

G-Research★3.6 (18)· London

You'll work with OpenTelemetry, Kubernetes, cloud platforms (AWS preferred), and observability tools like Datadog and NewRelic, coding primarily in Go or Python. The Observability Engineering Team builds telemetry ingestion pipelines and standards for G-Research, a quantitative finance firm, enabling developers across the company to effectively instrument and monitor their services at scale.