Senior AI/ML Backend Engineer — Python & Cloud

JPMorgan Chase & Co.; Glasgow; On-site; GBP 70,000 - 110,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Software Engineer III to design and ship production-grade Python/Java services with a strong AI/ML focus. You will build APIs, microservices, and LLM-based features, working across Terraform, Kubernetes, and CI/CD in a multi-cloud environment.

You’ll collaborate across teams to implement secure, observable systems and deliver end-to-end software lifecycles, from requirements to production support, in a fast-paced, enterprise-scale setting.

Qualifications

• Formal training or certification on software engineering concepts and proficient applied experience.
• Strong hands-on Python development experience building backend services, including testing, packaging, dependency management, and maintainability.
• Strong database and SQL proficiency, with experience implementing application logic and APIs on top of relational data.
• Experience building APIs and microservices using REST or gRPC, including contracts, security basics, and observability.
• Practical experience delivering LLM-based features as part of software systems, with familiarity with agentic patterns.
• Working knowledge of delivery and operations including CI/CD, Git, containers, and Kubernetes.
• Familiarity with Terraform and cloud infrastructure concepts in a multi-cloud environment.
• Solid understanding of software engineering fundamentals and software development lifecycle practices.
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment.
• Understanding of responsible AI use in engineering workflows.

Responsibilities

• Deliver software through a disciplined software development lifecycle, working from well-defined requirements through design, implementation, testing, release, and production support.
• Write maintainable Python code with unit and integration tests, debugging issues across application, API, data-access, and runtime layers.
• Implement LLM-driven workflows including prompting, tool and function calling, routing, orchestration, and state handling to support multi-step agentic task execution.
• Build and maintain inference-time integrations such as model gateways, APIs, caching, fallbacks, timeouts, and concurrency controls for production AI systems.
• Implement retrieval-augmented generation components where applicable, including chunking, embeddings, retrieval, and grounding strategies.
• Build REST and gRPC endpoints following agreed contracts, implementing authentication and authorization integration, input validation, error handling, and secure data handling practices.
• Implement SQL-backed business logic powering APIs and microservices, including joins, aggregations, filtering, pagination, and transactional workflows.
• Contribute to CI/CD pipelines and Git workflows, packaging and deploying services using containers and Kubernetes with support for safe rollouts and rollbacks.
• Contribute to infrastructure-as-code using Terraform within established team patterns across modules, environments, and state management.
• Improve operability of services by adding and using observability tooling including logs, metrics, traces, dashboards, and alerts, and participate in incident response and root-cause analysis.
• Leverage enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity.

Skills

Python development

REST/gRPC

CI/CD

Kubernetes

Terraform

Security practices

AI/ML concepts

Code quality

Education

Software engineering training/certification

Tools

Git

Docker

Job description

JPMorgan Chase & Co. is seeking a Software Engineer III to design and ship production-grade Python/Java services with a strong AI/ML focus. You will build APIs, microservices, and LLM-based features, working across Terraform, Kubernetes, and CI/CD in a multi-cloud environment.

You’ll collaborate across teams to implement secure, observable systems and deliver end-to-end software lifecycles, from requirements to production support, in a fast-paced, enterprise-scale setting.