1 to 25 of 44 Remote AWS Lambda Jobs in the South East

and deploy ML models, algorithms and agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure-as … code tools like AWS CloudFormation and Terraform to automate model deployment and system setup Project Leadership: Oversee the ML lifecycle from data preparation to model training, validation, and deployment. Make high-level design decisions on model architecture and data pipelines. Mentor junior engineers and collaborate with data scientists, ML engineers, and Software Engineering teams to ensure successful delivery of … PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWS Lambda, Athena More ❯

and deploy ML models, algorithms and agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure-as … code tools like AWS CloudFormation and Terraform to automate model deployment and system setup Project Leadership: Oversee the ML lifecycle from data preparation to model training, validation, and deployment. Make high-level design decisions on model architecture and data pipelines. Mentor junior engineers and collaborate with data scientists, ML engineers, and Software Engineering teams to ensure successful delivery of … PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWS Lambda, Athena More ❯

and deploy ML models, algorithms and agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure-as … code tools like AWS CloudFormation and Terraform to automate model deployment and system setup Project Leadership: Oversee the ML lifecycle from data preparation to model training, validation, and deployment. Make high-level design decisions on model architecture and data pipelines. Mentor junior engineers and collaborate with data scientists, ML engineers, and Software Engineering teams to ensure successful delivery of … PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWS Lambda, Athena More ❯

and deploy ML models, algorithms and agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure-as … code tools like AWS CloudFormation and Terraform to automate model deployment and system setup Project Leadership: Oversee the ML lifecycle from data preparation to model training, validation, and deployment. Make high-level design decisions on model architecture and data pipelines. Mentor junior engineers and collaborate with data scientists, ML engineers, and Software Engineering teams to ensure successful delivery of … PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWS Lambda, Athena More ❯

and deploy ML models, algorithms and agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure-as … code tools like AWS CloudFormation and Terraform to automate model deployment and system setup Project Leadership: Oversee the ML lifecycle from data preparation to model training, validation, and deployment. Make high-level design decisions on model architecture and data pipelines. Mentor junior engineers and collaborate with data scientists, ML engineers, and Software Engineering teams to ensure successful delivery of … PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWS Lambda, Athena More ❯

and deploy ML models, algorithms and agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure-as … code tools like AWS CloudFormation and Terraform to automate model deployment and system setup Project Leadership: Oversee the ML lifecycle from data preparation to model training, validation, and deployment. Make high-level design decisions on model architecture and data pipelines. Mentor junior engineers and collaborate with data scientists, ML engineers, and Software Engineering teams to ensure successful delivery of … PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWS Lambda, Athena More ❯

and deploy ML models, algorithms and agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure-as … code tools like AWS CloudFormation and Terraform to automate model deployment and system setup Project Leadership: Oversee the ML lifecycle from data preparation to model training, validation, and deployment. Make high-level design decisions on model architecture and data pipelines. Mentor junior engineers and collaborate with data scientists, ML engineers, and Software Engineering teams to ensure successful delivery of … PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWS Lambda, Athena More ❯

and deploy ML models, algorithms and agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure-as … code tools like AWS CloudFormation and Terraform to automate model deployment and system setup Project Leadership: Oversee the ML lifecycle from data preparation to model training, validation, and deployment. Make high-level design decisions on model architecture and data pipelines. Mentor junior engineers and collaborate with data scientists, ML engineers, and Software Engineering teams to ensure successful delivery of … PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWS Lambda, Athena More ❯

and deploy ML models, algorithms and agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure-as … code tools like AWS CloudFormation and Terraform to automate model deployment and system setup Project Leadership: Oversee the ML lifecycle from data preparation to model training, validation, and deployment. Make high-level design decisions on model architecture and data pipelines. Mentor junior engineers and collaborate with data scientists, ML engineers, and Software Engineering teams to ensure successful delivery of … PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWS Lambda, Athena More ❯

and deploy ML models, algorithms and agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure-as … code tools like AWS CloudFormation and Terraform to automate model deployment and system setup Project Leadership: Oversee the ML lifecycle from data preparation to model training, validation, and deployment. Make high-level design decisions on model architecture and data pipelines. Mentor junior engineers and collaborate with data scientists, ML engineers, and Software Engineering teams to ensure successful delivery of … PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWS Lambda, Athena More ❯

and deploy ML models, algorithms and agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure-as … code tools like AWS CloudFormation and Terraform to automate model deployment and system setup Project Leadership: Oversee the ML lifecycle from data preparation to model training, validation, and deployment. Make high-level design decisions on model architecture and data pipelines. Mentor junior engineers and collaborate with data scientists, ML engineers, and Software Engineering teams to ensure successful delivery of … PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWS Lambda, Athena More ❯

used Flask&FastAPI Typing is used within our Python stack to power automated documentation and API definitions Relational Databases (PostgreSQL) at the heart of majority of services We're AWS for Cloud hosted services Heavy use of AWS lambda Serverless Docker (AWS ECS) for uniform development/deployment from dev to prod Requirements This role will More ❯

AWS Data Engineer Rate: Up to £400 per day (Outside IR35) Contract Length: 6 Months (with strong potential for extension) Location: Hybrid - 1 day per week onsite in Central London A leading organisation is seeking an experienced AWS Data Engineer to join their data and analytics team, contributing to the design, development and optimisation of large-scale data … environment. This contract offers the opportunity to work on high-impact projects, delivering data platforms and pipelines that drive real-time insights and strategic business decisions. Responsibilities for the AWS Data Engineer: Design, build and maintain scalable data pipelines and architectures within the AWS ecosystem Leverage services such as AWS Glue, Lambda, Redshift, EMR and S3 … governance, privacy and security policies throughout all stages of development Collaborate in an Agile environment, contributing to sprint planning, peer reviews and continuous improvement initiatives Essential Skills for the AWS Data Engineer: Extensive hands-on experience with AWS data services Strong programming skills in Python (including libraries such as PySpark or Pandas) Solid understanding of data modelling, warehousing More ❯

development. You'll play a crucial role in technical decision-making, team development, and delivering high-quality solutions across our full-stack environment. Technical Environment Frontend: React, TypeScript Backend: AWS Lambda, TypeScript Infrastructure: Serverless Framework, Terraform AWS cloud infrastructure CI/CD pipelines Key Responsibilities Technical Leadership Drive technical excellence and best practices across the team Make … stakeholders Required Skills & Experience 6+ years of software development experience Previous experience leading engineering teams Strong hands-on coding abilities in TypeScript and React Experience with Serverless architectures and AWS Proven track record of delivering complex technical projects Excellent communication and interpersonal skills Experience mentoring and developing engineers Strong system design and architectural skills Preferred Qualifications Experience in SaaS More ❯

incidents. As a Senior DevOps Engineer/Infrastructure Lead , you will be responsible for overseeing infrastructure strategy, driving DevOps best practices, and ensuring robust cloud operations across Azure and AWS environments. This is a permanent role offering a salary of £43,450 and benefits. You will be home or remote-based , with occasional travel to the office required. Candidates … multidisciplinary Infrastructure and DevOps team to deliver outstanding service levels and meet operational targets. Designing and implementing infrastructure and DevOps roadmaps aligned with organisational priorities. Overseeing cloud environments across AWS and Azure, ensuring performance, scalability, and security. Managing and improving Infrastructure as Code (IaC) deployment using GitHub and automation tools. Maintaining and optimising CI/CD pipelines to enable … continuous delivery of secure and reliable applications. Managing container orchestration (Kubernetes/EKS) and serverless platforms (AWS Lambda). Implementing automation across deployment, monitoring, and scaling processes. Ensuring compliance with security standards and regulatory frameworks (including ISO27001, GDPR, and Cyber Essentials Plus). Collaborating closely with cross-functional teams to deliver integrated technical solutions. Producing documentation, reports, and More ❯

Cloud Operations Team Leader | Milton Keynes (Hybrid) | £75,000-£85,000 | (AWS/Terraform/CI/CD) | Strong benefits package Location: Milton Keynes, hybrid (UK) Salary: £75,000 - £85,000 Company: Leading Technology Provider The Role We're looking for a Cloud Operations Team Leader to manage and optimise our cloud infrastructure and lead a skilled engineering team. … performance monitoring. Excellent communication and stakeholder management skills. Nice-to-have: SQL Server | Windows Server | Active Directory | DNS | IIS/Nginx | Linux | PowerShell/Bash | IDS/IPS | Serverless (AWS Lambda, ECS) | AI applied to Infrastructure-as-Code Why Join Us 25 days holiday + bank holidays, with extra for long service Two paid wellbeing days per year More ❯

/3 days in a week) Skill matrix: Can you please specify how many years of exp do you have in below skills with rating ( Out of 5) : AWS Core Java Microservices/REST Spring Coding skills Terraform/Ansible UI/Angular Database/SQL Apache Spark About the Role We are seeking a highly skilled and experienced … and maintain robust, scalable, and high-performance applications. The ideal candidate will have deep expertise in Core Java, Spring Framework, and Microservices architecture, along with hands-on experience in AWS cloud services and automation tools like Terraform or Ansible. Key Responsibilities • Design, develop, and deploy scalable Java-based applications using Spring 11/17 and Microservices architecture. • Develop RESTful … APIs and integrate with front-end systems built on Angular. • Collaborate with cross-functional teams to deliver secure, efficient, and maintainable software solutions. • Implement and manage cloud infrastructure using AWS services. • Automate deployment and infrastructure provisioning using Terraform or Ansible. • Optimize application performance using Apache Spark for data processing where required. • Write clean, efficient, and maintainable code following best More ❯

L1/L2 scaling frameworks. Built or integrated custodial wallets, exchanges, or on/off-ramp processes. Experience with treasury, FX, reconciliation, or accounting systems. Familiarity with serverless architectures (AWS Lambda). Worked on SaaS platforms operating 24/7 at large scale. Exposure to SOC2/SOX controls and audit-driven systems. You're a Great Fit More ❯

L1/L2 scaling frameworks. Built or integrated custodial wallets, exchanges, or on/off-ramp processes. Experience with treasury, FX, reconciliation, or accounting systems. Familiarity with serverless architectures (AWS Lambda). Worked on SaaS platforms operating 24/7 at large scale. Exposure to SOC2/SOX controls and audit-driven systems. You're a Great Fit More ❯

L1/L2 scaling frameworks. Built or integrated custodial wallets, exchanges, or on/off-ramp processes. Experience with treasury, FX, reconciliation, or accounting systems. Familiarity with serverless architectures (AWS Lambda). Worked on SaaS platforms operating 24/7 at large scale. Exposure to SOC2/SOX controls and audit-driven systems. You're a Great Fit More ❯

L1/L2 scaling frameworks. Built or integrated custodial wallets, exchanges, or on/off-ramp processes. Experience with treasury, FX, reconciliation, or accounting systems. Familiarity with serverless architectures (AWS Lambda). Worked on SaaS platforms operating 24/7 at large scale. Exposure to SOC2/SOX controls and audit-driven systems. You're a Great Fit More ❯

L1/L2 scaling frameworks. Built or integrated custodial wallets, exchanges, or on/off-ramp processes. Experience with treasury, FX, reconciliation, or accounting systems. Familiarity with serverless architectures (AWS Lambda). Worked on SaaS platforms operating 24/7 at large scale. Exposure to SOC2/SOX controls and audit-driven systems. You're a Great Fit More ❯

L1/L2 scaling frameworks. Built or integrated custodial wallets, exchanges, or on/off-ramp processes. Experience with treasury, FX, reconciliation, or accounting systems. Familiarity with serverless architectures (AWS Lambda). Worked on SaaS platforms operating 24/7 at large scale. Exposure to SOC2/SOX controls and audit-driven systems. You're a Great Fit More ❯

L1/L2 scaling frameworks. Built or integrated custodial wallets, exchanges, or on/off-ramp processes. Experience with treasury, FX, reconciliation, or accounting systems. Familiarity with serverless architectures (AWS Lambda). Worked on SaaS platforms operating 24/7 at large scale. Exposure to SOC2/SOX controls and audit-driven systems. You're a Great Fit More ❯

L1/L2 scaling frameworks. Built or integrated custodial wallets, exchanges, or on/off-ramp processes. Experience with treasury, FX, reconciliation, or accounting systems. Familiarity with serverless architectures (AWS Lambda). Worked on SaaS platforms operating 24/7 at large scale. Exposure to SOC2/SOX controls and audit-driven systems. You're a Great Fit More ❯