Lead Software Engineer – AIML Data Platform (Data, Python, Containers/Kubernetes)
JPMorgan Chase12 hours ago
London, United KingdomStaff+
Responsibilities
- Design, develop, troubleshoot, and optimize batch, streaming, ML, and LLM workloads across latency, throughput, resilience, cost, and governance tradeoffs.
- Build high-volume data platforms for ingestion, transformation, enrichment, storage, and consumption using distributed data and streaming technologies.
- Productionize ML through training, evaluation, deployment, monitoring, lifecycle management, and quality-drift detection.
- Build production LLM systems with retrieval, tool use, orchestration, caching, batching, evaluation, and human-in-the-loop controls.
- Write, review, debug, and tune production code; lead design and code reviews and own incident response.
- Lead adoption and validation standards for enterprise-authorized AI-assisted engineering tools and responsible AI practices.
- Provide technical leadership across engineers, product managers, vendors, startups, and stakeholders, and mentor junior engineers.
- Identify and automate recurring remediation opportunities to improve application and system stability.
Requirements
- Formal training or certification in software engineering concepts and advanced applied experience.
- Hands-on experience with system design, application development, testing, and operational stability.
- Advanced Python experience; Java, Kotlin, or Scala experience is a plus.
- Strong cloud-based and cloud-native engineering experience.
- Deep distributed-systems knowledge, including partitioning, parallelism, state, fault tolerance, and performance tuning.
- Production experience with data engineering and streaming platforms at meaningful volume.
- Practical ML engineering experience across inference, evaluation, monitoring, and deployment.
- Real-world LLM delivery experience beyond prototypes, including quality, cost, safety, and governance considerations.
- Experience leading the effective use of approved AI-assisted software development tools and validating their outputs for correctness, performance, and security.
- Understanding of responsible AI practices, data sensitivity, secure input and output handling, resiliency, and security expectations.
- Proficiency across the software development lifecycle and understanding of databases and data structures.
- Understanding of application resiliency, security, CI/CD, and agile delivery practices.
- Proven record of leading technical delivery across teams while contributing directly to code.
- Financial-services IT knowledge; regulated environments, agent frameworks, MCP, RAG, vector search, Kubernetes, modern observability, and real-time analytics or search architectures are preferred.
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.