1,301 to 1,325 of 3,103 AWS Jobs in London

is utilised in the development workflow Full Tech Stack: Backend & Data: Python, PostgreSQL, BigQuery, MySQL Frontend: TypeScript, React, styled-components Testing: Jest, React Testing Library, Cypress, pytest Cloud & Infra: AWS, GCP, ECS Fargate, Docker, Terraform, GitHub Actions This is a unique opportunity for an engineer who understands what best practice looks like when working with AI assistance. While you won More ❯

as capital markets system integration will be a very useful complement to the above. 2. Key technology used Primary: Java 8+ Secondary: Spring FIX Hibernate (Postgres) Sockets Linux Maven AWS/Cloud deployment SVN/GIT EPL (Esper) JMS (ActiveMQ) 3. Methodology Agile/Scrum Continuous integration Test automation TDD 4. Requirements Must have Core Java SE Desire to learn More ❯

scalability, and reliability. Requirements 5+ years' experience in Data Engineering with strong Python and SQL skills. Background in building and maintaining ETL/ELT pipelines in a cloud environment (AWS or Azure). Knowledge of data warehousing (e.g., Redshift, Postgres) and tools like DBT . Familiarity with CI/CD , data modelling, and Agile practices. Comfortable collaborating with Data Scientists More ❯

frameworks (LangChain, LlamaIndex, AutoGen, CrewAI) ● Proven track record designing scalable AI architectures (RAG, Graph RAG, multi-agent systems) ● Experience with vector databases (Pinecone, Weaviate, FAISS) and major cloud platforms (AWS, Azure, GCP) ● Strong foundation in MLOps/LLMOps and Agile delivery ● Excellent leadership, communication, and stakeholder engagement skills ● 10+ years’ experience in AI/ML, including senior solution architecture or More ❯

frameworks (LangChain, LlamaIndex, AutoGen, CrewAI) ● Proven track record designing scalable AI architectures (RAG, Graph RAG, multi-agent systems) ● Experience with vector databases (Pinecone, Weaviate, FAISS) and major cloud platforms (AWS, Azure, GCP) ● Strong foundation in MLOps/LLMOps and Agile delivery ● Excellent leadership, communication, and stakeholder engagement skills ● 10+ years’ experience in AI/ML, including senior solution architecture or More ❯

such as TensorFlow or PyTorch Knowledge of SQL and relational databases; experience with Big Data environments Familiarity with API development and NoSQL databases Understanding of CI/CD practices , AWS , and GIT Background in working to strict project deadlines Palantir experience is a bonus – full training will be provided if not Must have active SC or DV clearance Experience working More ❯

such as TensorFlow or PyTorch Knowledge of SQL and relational databases; experience with Big Data environments Familiarity with API development and NoSQL databases Understanding of CI/CD practices , AWS , and GIT Background in working to strict project deadlines Palantir experience is a bonus – full training will be provided if not Must have active SC or DV clearance Experience working More ❯

frameworks (LangChain, LlamaIndex, AutoGen, CrewAI) ● Proven track record designing scalable AI architectures (RAG, Graph RAG, multi-agent systems) ● Experience with vector databases (Pinecone, Weaviate, FAISS) and major cloud platforms (AWS, Azure, GCP) ● Strong foundation in MLOps/LLMOps and Agile delivery ● Excellent leadership, communication, and stakeholder engagement skills ● 10+ years’ experience in AI/ML, including senior solution architecture or More ❯

frameworks (LangChain, LlamaIndex, AutoGen, CrewAI) ● Proven track record designing scalable AI architectures (RAG, Graph RAG, multi-agent systems) ● Experience with vector databases (Pinecone, Weaviate, FAISS) and major cloud platforms (AWS, Azure, GCP) ● Strong foundation in MLOps/LLMOps and Agile delivery ● Excellent leadership, communication, and stakeholder engagement skills ● 10+ years’ experience in AI/ML, including senior solution architecture or More ❯

such as TensorFlow or PyTorch Knowledge of SQL and relational databases; experience with Big Data environments Familiarity with API development and NoSQL databases Understanding of CI/CD practices , AWS , and GIT Background in working to strict project deadlines Palantir experience is a bonus – full training will be provided if not Must have active SC or DV clearance Experience working More ❯

such as TensorFlow or PyTorch Knowledge of SQL and relational databases; experience with Big Data environments Familiarity with API development and NoSQL databases Understanding of CI/CD practices , AWS , and GIT Background in working to strict project deadlines Palantir experience is a bonus – full training will be provided if not Must have active SC or DV clearance Experience working More ❯

markets and trading systems. Strong communication skills with the ability to collaborate across research and technology teams. Exposure to low-latency or real-time systems. Experience with cloud infrastructure (AWS, GCP, or Azure). Familiarity with data engineering tools such as Kafka, Airflow, Spark, or Dask. Knowledge of equities, futures, or FX markets. Company Rapidly growing hedge fund offices globally More ❯

role. Expertise in Python (or a similar backend language), with proven experience designing distributed systems, APIs, and microservices at scale. Deep understanding of software architecture, cloud infrastructure (Google Cloud, AWS, or Azure), and modern DevOps practices. Strong knowledge of data structures, algorithms, and system design principles. Demonstrated experience influencing technical direction across teams and driving alignment on complex engineering decisions. More ❯

and proficiency in data modelling and data product building in Data Bricks. Developed Azure cloud experience for data storage and processing, considerations made for alternate cloud providers such as AWS and GCP. Substantial programming ability using languages/tools such as R, Python and C++ for data manipulation and scripting Solid understanding of relevant data governance, data quality, and data More ❯

and proficiency in data modelling and data product building in Data Bricks. Developed Azure cloud experience for data storage and processing, considerations made for alternate cloud providers such as AWS and GCP. Substantial programming ability using languages/tools such as R, Python and C++ for data manipulation and scripting Solid understanding of relevant data governance, data quality, and data More ❯

Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Vertex AI, Azure ML). Strong understanding of data engineering, data pipelines, and ETL More ❯

Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Vertex AI, Azure ML). Strong understanding of data engineering, data pipelines, and ETL More ❯

Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Vertex AI, Azure ML). Strong understanding of data engineering, data pipelines, and ETL More ❯

etc. Experience with object oriented design, distributed systems architecture, performance tuning. Experience with designing and programming relational database such as MySQL, RedShift, Oracle SQL Server, or Postgres. Experience with AWS based system architecture covering S3, EKS, EC2, Batch, or Airflow etc. Experience with caching and messaging technologies such as, Redis, Hazelcast, MQ, or Kafka etc. Experience with programming within a More ❯

and database design, with experience across relational, time-series, and high-availability database environments. Understanding of on-premises Linux-based infrastructure, and deploying and managing containerised/virtualised environments (AWS, OpenShift). Demonstrated ability to work within Agile/Scrum SDLC, translating business objectives into actionable user stories and robust technical deliverables. Proven ability to produce and maintain high-quality More ❯

governance processes and balance technical innovation with compliance and risk. Deep understanding of secure development principles, DevOps practices, and systems resilience. Relevant technical certifications (e.g. TOGAF, Azure Solutions Architect, AWS Certified Architect) desirable. Diversity, equity and inclusion We are committed to equal opportunities for all and will not discriminate on any grounds. We encourage applications from people from the widest More ❯

and maintaining data pipelines. Containerization experience (e.g. Docker) Hands-on experience with vector databases. Experience integrating language models (LMs) into data workflows. Proficiency with cloud platforms such as Azure, AWS, or GCP and their managed data services. Desirable: Experience with asynchronous python programming Experience with graph technologies (e.g., Kuzu, Neo4j, Apache AGE). Familiarity with embedding models (hosted or local More ❯

and maintaining data pipelines. Containerization experience (e.g. Docker) Hands-on experience with vector databases. Experience integrating language models (LMs) into data workflows. Proficiency with cloud platforms such as Azure, AWS, or GCP and their managed data services. Desirable: Experience with asynchronous python programming Experience with graph technologies (e.g., Kuzu, Neo4j, Apache AGE). Familiarity with embedding models (hosted or local More ❯

and maintaining data pipelines. Containerization experience (e.g. Docker) Hands-on experience with vector databases. Experience integrating language models (LMs) into data workflows. Proficiency with cloud platforms such as Azure, AWS, or GCP and their managed data services. Desirable: Experience with asynchronous python programming Experience with graph technologies (e.g., Kuzu, Neo4j, Apache AGE). Familiarity with embedding models (hosted or local More ❯

and maintaining data pipelines. Containerization experience (e.g. Docker) Hands-on experience with vector databases. Experience integrating language models (LMs) into data workflows. Proficiency with cloud platforms such as Azure, AWS, or GCP and their managed data services. Desirable: Experience with asynchronous python programming Experience with graph technologies (e.g., Kuzu, Neo4j, Apache AGE). Familiarity with embedding models (hosted or local More ❯