Systems : Develop and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring. More ❯
Systems : Develop and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring. More ❯
Systems : Develop and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring. More ❯
Systems : Develop and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring. More ❯
Systems : Develop and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring. More ❯
Systems : Develop and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring. More ❯
City of London, London, Finsbury Square, United Kingdom
The Portfolio Group
Systems : Develop and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring. More ❯
London, England, United Kingdom Hybrid / WFH Options
AltFi Ltd
TCP/IP stack knowledge, Encryption expertise, TLS, DTLS, ECC, PKI/Certificates Identity & Access Management: AD/LDAP Preferred Qualifications: Experience with AI technologies and services (e.g., OpenAI, Bedrock, etc.) Expertise in the security of Gen AI models, including multi-modal models Experience with the security of automation built around Gen AI inputs and outputs Knowledge with AWS More ❯
e.g. data and model versioning, model deployment CI/CD, MLFlow/DVC) Cloud platform experience, especially from an ML standpoint (AWS preferred) Statistical testing experience Experience with AWS Bedrock Experience with C# Containerization via Docker. Awareness of basic data science and generative AI methods. Exposure to generative AI application frameworks like LangChain, LlamaIndex, SmolAgents and griptape. What's More ❯
#Design #Infrastructure AWS Technical Lead #AWS #Technical #Lead #Python #Tech #Design #Infrastructure Job Description The AWS Technical Lead will bring a wealth of experience in cloud computing, particularly with Amazon Web Services (AWS), to guide the technical direction of our AWS projects. This role demands collaboration with development and operations teams to ensure the successful execution of cloud-based … Jira & Confluence. Experience working on Migration/Modernisation projects. Understanding of networking concepts and protocols. Experience with multi-cloud environments. Exposure to AI/ML and Generative AI/Amazon Bedrock. AWS Certified Solutions Architect – Associate/Professional (Must). #AWS #Technical #Lead #Python #Tech #Design #Infrastructure Work Environment The work environment is collaborative and fast-paced, with a More ❯
related. Required technical skills: Coding proficiency in Python, and front-end development experience with Javascript/React. Proficiency development with services such as AWS Lambda, Step Functions, DynamoDB, AppSync, Bedrock, SageMaker, and CloudWatch. Proficiency in developing and integrating with REST-based or GraphQL-based APIs. Proficiency in developing infrastructure-as-code deployment solutions such as AWS CloudFormation or AWS More ❯
London, England, United Kingdom Hybrid / WFH Options
NiCE
devops experience useful (kubectl, helm, etc.) Cloud platform experience, especially from an ML standpoint (AWS preferred) Statistical testing experience Basic AWS resource management, including microservice deployment. Experience with AWS Bedrock Experience with C# Containerization via Docker. Awareness of basic data science and generative AI methods. Exposure to generative AI application frameworks like LangChain, LlamaIndex, SmolAgents and griptape. What’s More ❯
cloud platforms such as AWS, GCP, or Azure Understanding of API integration and deploying solutions in cloud environments Familiarity or hands-on exposure to generative AI ecosystems (e.g., OpenAI, Bedrock, Hugging Face) LLMs & Emerging Tech Awareness Awareness of large language models (LLMs) and a strong enthusiasm for staying current with advancements in generative AI and applied machine learning Communication More ❯
track record of delivering projects using agile methodologies (Scrum, Kanban, etc.) Nice to have Hands-on experience with AI and Machine Learning , including model development, deployment, and inference using Amazon SageMaker and AmazonBedrock Benefits: Annual Bonus, 30 days holiday + bank holidays, Private Healthcare, Life Assurance + much more. Please feel free to reach me on More ❯
Software Development Manager- Finance AI and ML Dev, PXT Finance - ML Forecasting and Core Engineering Amazon Finance Tech team leads innovation to combine data-driven finance with the AI approach driving accuracy, next gen forecasting capabilities, speed, efficiency, and reliability by exploring new techniques in ML and AI and building full stack services in AWS. This AI-First Finance … with AI/ML experience will manage a two-pizza development team in Bangalore. The team will build innovative AI-driven big data solutions to support and forecast critical Amazon Financial work flows and processes, handling tons of data daily through GenAI-driven NLP queries. This SDM will be part of the Finance tech organization and will be responsible … enable Finance decision makers to quickly build and launch operating plans and cyclical financial workflows in a cost-effective way. This hands-on position requires broad engineering competence in Amazon Cloud and AI Stack such as AmazonBedrock, Sagemaker, EC2, Lambda, Dynamo DB along with Java,Python full-stack expertise and a good understanding of the scalable More ❯
track record of delivering projects using agile methodologies (Scrum, Kanban, etc.) Nice to have Hands-on experience with AI and Machine Learning , including model development, deployment, and inference using Amazon SageMaker and AmazonBedrock Benefits: Annual Bonus, 30 days holiday + bank holidays, Private Healthcare, Life Assurance + much more. Please feel free to reach me on More ❯
a trajectory to success? Are you familiar with security best practices and compliance standards for AI applications? Do you want to be part of the team helping to establish Amazon Web Services as a leading technology AI platform? Would you like to be part of a team that genuinely focuses on understanding what's best for the customer and … also be valued within as a technical expert? Amazon Web Services is looking for a skilled and motivated Professional Services Data Scientist to help accelerate our growing Data and AI business in the UK and work with our public sector customers. We need passionate, experienced consultants to help our citizens and the community benefit from the AI revolution. Candidates … guide customers deconstruct ambiguity. Responsibilities include: Expertise: Collaborate with field sales, pre-sales, training and support teams to help partners and customers learn and use AWS services such as Bedrock, Sagemaker, and other data services. Experience in architecture, software design and operations in hybrid environments as well as complex projects at scale. Solutions: Demonstrated consulting skills, ideally through previous More ❯
cover all domains fully but should be able to show strong capability in their core areas: Cloud Data Platforms Azure Synapse Analytics, Microsoft Fabric, Azure Data Lake, Azure SQL Amazon Redshift, AWS Athena, AWS Glue Google BigQuery, Google Cloud Storage, Dataproc Artificial Intelligence & Machine Learning Azure OpenAI, Azure Machine Learning Studio, Azure AI Foundry AWS SageMaker, AmazonBedrock … Hugging Face Data Engineering & Big Data Azure Data Factory, Azure Databricks, Apache Spark, Delta Lake AWS Glue ETL, AWS EMR Google Dataflow, Apache Beam Business Intelligence & Analytics Power BI, Amazon QuickSight, Looker Studio Embedded analytics and interactive dashboarding solutions Cloud Architecture Azure App Services, Virtual Machines, Functions, Kubernetes AWS EC2, Lambda, EKS, S3 Google Compute Engine, GKE, Cloud Run More ❯
infrastructure. Key Responsibilities: Lead development of our Python-based AI orchestration application deployed via containerised services with python engineers and your seld Manage our multi-modal LLM strategy including AmazonBedrock integration and self-hosted model deployment Optimise vector indexing, retrieval systems, and embedding pipelines for document processing Implement advanced prompt engineering, token management, and model evaluation frameworks … technologies: Laravel/PHP, Vue.js/Nuxt, Python Proven track record with cloud platforms (AWS preferred, but multi-cloud experience valued) Experience with LLM deployment strategies - both managed services (Bedrock, OpenAI) and self-hosted solutions Understanding of vector databases, embedding systems, and retrieval architectures Technical Expertise: Containerisation (Docker) and orchestration platforms (Kubernetes, ECS, or equivalent) Database design across SQL More ❯
infrastructure. Key Responsibilities: Lead development of our Python-based AI orchestration application deployed via containerised services with python engineers and your seld Manage our multi-modal LLM strategy including AmazonBedrock integration and self-hosted model deployment Optimise vector indexing, retrieval systems, and embedding pipelines for document processing Implement advanced prompt engineering, token management, and model evaluation frameworks … technologies: Laravel/PHP, Vue.js/Nuxt, Python Proven track record with cloud platforms (AWS preferred, but multi-cloud experience valued) Experience with LLM deployment strategies - both managed services (Bedrock, OpenAI) and self-hosted solutions Understanding of vector databases, embedding systems, and retrieval architectures Technical Expertise: Containerisation (Docker) and orchestration platforms (Kubernetes, ECS, or equivalent) Database design across SQL More ❯
infrastructure. Key Responsibilities: Lead development of our Python-based AI orchestration application deployed via containerised services with python engineers and your seld Manage our multi-modal LLM strategy including AmazonBedrock integration and self-hosted model deployment Optimise vector indexing, retrieval systems, and embedding pipelines for document processing Implement advanced prompt engineering, token management, and model evaluation frameworks … technologies: Laravel/PHP, Vue.js/Nuxt, Python Proven track record with cloud platforms (AWS preferred, but multi-cloud experience valued) Experience with LLM deployment strategies - both managed services (Bedrock, OpenAI) and self-hosted solutions Understanding of vector databases, embedding systems, and retrieval architectures Technical Expertise: Containerisation (Docker) and orchestration platforms (Kubernetes, ECS, or equivalent) Database design across SQL More ❯
