Sr. Lead Software Engineer - Python, AWS, AI
JPMorgan Chase17 hours ago
Glasgow, United KingdomStaff+
Responsibilities
- Design and implement complex Python backend services and APIs for production environments.
- Build agentic capabilities with the Smart SDK, including tool integrations, orchestration, and production safety and reliability guardrails.
- Develop and optimize end-to-end RAG pipelines covering ingestion, chunking, embeddings, retrieval, reranking, and prompt and response patterns with OpenSearch.
- Build LLM and agent evaluation, regression testing, relevance, grounding, latency, safety, cost, and monitoring frameworks.
- Engineer secure integrations, data flows, search solutions, schema designs, migrations, query tuning, indexing strategies, and relevance tuning using AWS Aurora and OpenSearch.
- Write secure production code, conduct code reviews, debug systems, mentor engineers, and improve maintainability and performance.
- Drive operational excellence through automation, preventative controls, reliability improvements, and reduced operational toil.
- Contribute to AWS cloud-native engineering, Terraform infrastructure-as-code, deployment safety, environment consistency, and observability.
- Use enterprise-authorized AI coding and development tools while validating their outputs through peer review, testing, and secure coding practices.
Requirements
- Formal training or certification in software engineering concepts and advanced applied experience.
- Strong hands-on Python experience building production backend systems, APIs, services, testing practices, performance debugging, and dependency management.
- Experience building agentic and LLM-powered capabilities with tool integration, orchestration, and production safety and reliability guardrails.
- Experience implementing LLM and agent evaluation and measurement loops, including relevance, grounding, regression, reliability, and latency monitoring.
- Experience across the full Software Development Life Cycle from design and implementation through testing, deployment, and production support.
- Proficiency with AWS, Terraform, GitHub, Jenkins, and modern developer tooling.
- Experience with Docker and container orchestration platforms such as Amazon ECS, Amazon EKS, or Kubernetes.
- Expertise with monitoring and observability tools such as Splunk, Datadog, Dynatrace, or CloudWatch.
- Hands-on experience using enterprise-authorized AI-assisted development tools and critically evaluating and refining generated outputs for correctness, performance, and security.
- Understanding of responsible AI use, data sensitivity, secure input and output handling, resiliency, and security expectations.
- Strong written and verbal communication skills for explaining technical tradeoffs to cross-functional partners.
- Preferred experience includes Redis in production, scaling and hardening RAG systems, integrating AI services with banking or financial-services systems, and exposure to continuous integration and delivery, resiliency, and secure engineering.
Tech Stack
Categories
About JPMorgan Chase
JPMorgan Chase provides consumer and commercial banking, payments, credit card, wealth management, and corporate and investment banking services to individuals, businesses, institutions, and governments. The public company (NYSE: JPM) earns revenue from interest, fees, trading, and asset management across operations in more than 100 markets. Headquartered in New York City with roots dating to 1799, it serves retail customers and prominent corporate and government clients through brands including Chase and J.P. Morgan.