11 of 11 Permanent Amazon Bedrock Jobs in Central London

engagement skills. Ability to work in ambiguous, fast-moving environments with minimal oversight. Experience in financial services or regulated industries. Familiarity with AWS AI/ML toolsets such as Amazon Bedrock, SageMaker, Jumpstart, POD, Kendra, and Lambda. Exposure to DevOps tools and practices such as Terraform, Ansible, and CI/CD pipelines. Understanding of data privacy, compliance, and More ❯

world applications Knowledge of authentication, secret management, networking, and model access governance Bonus Points For: Kong API Gateway, Kong Mesh, Flux CD AWS stack: EC2, EKS, S3, SQS, DynamoDB, Bedrock RESTful API development with FastAPI, microservices, Terraform, GitOps workflows Prompt evaluation tools such as Promptfoo SQL and NoSQL experience: MySQL, PostgreSQL, MongoDB, Cassandra Exposure to RAG patterns and vector More ❯

reliability and stability. Develop secure and scalable Python applications and RESTful APIs (FastAPI, Django REST Framework). Integrate AI services and foundation models from providers such as Azure AI , Amazon Bedrock , and Google Vertex AI . Work with vector databases and retrieval mechanisms to enhance accuracy and context. Collaborate with data, design, and engineering teams to improve model More ❯

Ensure AI solutions are ethical, scalable, and reliable in production. Your skillset Proven experience designing and scaling enterprise-grade AI/ML systems. Expertise with cloud AI stacks (AWS Bedrock, SageMaker, Azure OpenAI, Azure ML). Strong skills in Python, FastAPI, CI/CD, MLOps, and LLM orchestration. Leadership experience across multidisciplinary AI teams. Strategic mindset — able to bridge More ❯

Ensure AI solutions are ethical, scalable, and reliable in production. Your skillset Proven experience designing and scaling enterprise-grade AI/ML systems. Expertise with cloud AI stacks (AWS Bedrock, SageMaker, Azure OpenAI, Azure ML). Strong skills in Python, FastAPI, CI/CD, MLOps, and LLM orchestration. Leadership experience across multidisciplinary AI teams. Strategic mindset — able to bridge More ❯

Ensure AI solutions are ethical, scalable, and reliable in production. Your skillset Proven experience designing and scaling enterprise-grade AI/ML systems. Expertise with cloud AI stacks (AWS Bedrock, SageMaker, Azure OpenAI, Azure ML). Strong skills in Python, FastAPI, CI/CD, MLOps, and LLM orchestration. Leadership experience across multidisciplinary AI teams. Strategic mindset — able to bridge More ❯

ideal but not essential; this is a role for a builder first, leader second . Tech Snapshot Languages: Python 3.11+, TypeScript Frameworks: FastAPI, SQLAlchemy, Alembic Infrastructure: AWS (IAM, SES, Bedrock) Architecture: Event-driven, API-first, AI-integrated pipelines Databases: PostgreSQL Why This Role Step up from Senior Engineer to Lead Engineer in a venture-backed AI startup. Shape the More ❯

to spend your time on: Building and productionising LLM-based features and GenAI workflows. Using frameworks like LangChain, PyTorch, and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker, or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/CD and model monitoring to cost and performance optimisation. … Machine Learning Engineer. A strong grounding in Python, with hands-on experience building and shipping AI/ML or LLM-driven products. Experience with cloud ML platforms (AWS SageMaker, Bedrock, Vertex AI, etc.). Familiarity with LangChain or similar orchestration frameworks. A solid understanding of MLOps and how to take models from concept to production. A collaborative mindset - you More ❯

to spend your time on: Building and productionising LLM-based features and GenAI workflows. Using frameworks like LangChain, PyTorch, and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker, or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/CD and model monitoring to cost and performance optimisation. … Machine Learning Engineer. A strong grounding in Python, with hands-on experience building and shipping AI/ML or LLM-driven products. Experience with cloud ML platforms (AWS SageMaker, Bedrock, Vertex AI, etc.). Familiarity with LangChain or similar orchestration frameworks. A solid understanding of MLOps and how to take models from concept to production. A collaborative mindset - you More ❯

to spend your time on: Building and productionising LLM-based features and GenAI workflows. Using frameworks like LangChain, PyTorch, and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker, or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/CD and model monitoring to cost and performance optimisation. … Machine Learning Engineer. A strong grounding in Python, with hands-on experience building and shipping AI/ML or LLM-driven products. Experience with cloud ML platforms (AWS SageMaker, Bedrock, Vertex AI, etc.). Familiarity with LangChain or similar orchestration frameworks. A solid understanding of MLOps and how to take models from concept to production. A collaborative mindset - you More ❯

the Centre of Excellence’s reference architecture for Copilot and Agentic AI, supporting multi-tenant, multi-region deployments. b. Align CoPilot and adjacent AI frameworks (Google Vertex AI, AWS Bedrock, ServiceNow Agentforce) with HCLTech’s global transformation goals. 2. Executive & Client Advisory a. Advise C-suite and board-level stakeholders on CoPilot-driven business cases, ROI models, and adoption … Mastery: Hands-on expertise with Microsoft 365 CoPilot, Copilot Studio, Azure OpenAI Service, Cognitive Services, and Graph APIs. • Multi-Vendor Integration: Proven track record integrating Google Vertex AI, AWS Bedrock, and ServiceNow Agentforce into large-scale solutions. • Stakeholder Management: Exceptional executive presence, with experience advising public-sector and Fortune-level clients. • Governance & Compliance: Deep understanding of GDPR/UK More ❯