Applied AI ML Lead - Python & Agentic AI
JPMorgan Chase2 months ago
Glasgow, United KingdomStaff+
Responsibilities
- Design, develop, and deploy generative AI and agentic AI solutions for automation, decision-making, and user experience improvements.
- Build LLM/SLM-powered applications including RAG systems, summarization and extraction pipelines, copilots, and tool-using agents.
- Engineer production-grade Java and/or Python services, APIs, microservices, and libraries.
- Develop prompt templates, routing, guardrails, prompt-engineering assets, and automated evaluation systems.
- Build and maintain data pipelines and processing workflows for ML and GenAI use cases using cloud services.
- Apply MLOps practices for experimentation, versioning, CI/CD, deployment, monitoring, and maintenance of models, prompts, and agents.
- Implement unit and integration testing, latency and cost benchmarking, and logging, metrics, and tracing for AI services.
- Collaborate with technical and non-technical stakeholders on requirements, success metrics, rollout plans, and communication.
Requirements
- An undergraduate or master's degree, or equivalent practical experience, in Computer Science, Data Science, Machine Learning, or a related field.
- Hands-on experience building applied AI/ML or GenAI solutions such as RAG, classification, extraction, ranking, summarization, or copilots.
- Familiarity with MCP, Agent Skills, and architectures connecting models to tools and enterprise data through standardized interfaces.
- Knowledge of LLM application patterns including embeddings, vector search, prompt orchestration, tool or function calling, safety, guardrails, and evaluation.
- Strong software engineering experience delivering maintainable production systems with clean, testable code.
- Proficiency in Java and/or Python and experience building services and integrating with data sources and downstream systems.
- Experience deploying solutions on AWS and cloud-native environments, with knowledge of security fundamentals and operational excellence.
- Experience with code reviews, unit testing such as pytest or JUnit, deployment automation, containers, orchestration, and production monitoring.
- Preferred experience building multi-step agentic AI workflows with tool routing, planning, memory, supervision, and fallback strategies.
- Preferred experience with AWS Bedrock or SageMaker, scalable inference deployment, evaluation frameworks, model fine-tuning, SLMs, embeddings, retrieval systems, GitHub Copilot, Claude Code, distributed compute, or regulated financial-services environments.
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.