We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Lead Software Engineer at JPMorganChase within Commercial & Investment Bank, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading AI-enabled technology products in a secure, stable, and scalable way. You will own the end-to-end lifecycle of AI systems - from rapid prototyping and prompt engineering through to production deployment, monitoring, and continuous improvement. You will apply deep technical expertise in agentic architectures, LLM orchestration, and modern AI frameworks to tackle a diverse array of challenges that span multiple technologies and applications.

Job Responsibilities:

Build and productionize agentic AI solutions including agents, orchestrators, tool/function integrations, workflow/state management, and guardrails
Design and develop Python and Java services (microservices and shared libraries) with strong API contracts and domain-driven design where applicable
Architect and manage data pipelines, embeddings, and vector stores that power RAG and other AI capabilities, including prompt versioning, templating, and optimization for reliability
Build evaluation and observability frameworks to monitor AI system performance, including hallucination detection, latency, accuracy, and user feedback loops
Deliver AI-enabled business UI experiences in partnership with product and UX, ensuring usability, performance, and accessibility
Establish and maintain MLOps practices for AI model deployment, including CI/CD pipelines, model versioning, and infrastructure-as-code for AI workloads
Collaborate with security, risk, and controls partners to ensure solutions meet governance and compliance expectations for AI-enabled systems
Drive decisions that influence product design, application functionality, and technical operations, applying creative problem-solving to tackle challenges beyond routine approaches

Required qualifications, capabilities, and skills:

Formal training or certification on software engineering concepts and 8+ years of applied experience in software engineering, with demonstrable depth in AI/ML systems
Advanced proficiency in Python, with strong experience in at least one additional programming language (e.g., Java)
Hands-on experience building and productionizing agentic AI systems, including multi-agent orchestration using frameworks such as LangChain, LangGraph, or equivalent
Practical understanding of LLM orchestration, retrieval-augmented generation (RAG), tool calling, prompt engineering, and dynamic reasoning
Experience evaluating and integrating AI/LLM capabilities into production applications, including model evaluation, output quality monitoring, and feedback loops
Hands-on experience with AI coding tools (Claude Code, Copilot, or similar) - you know when they accelerate work and when human judgment is critical
Hands-on practical experience delivering system design, application development, testing, and operational stability
Strong experience with cloud services (AWS)

Preferred qualifications, skills, and capabilities:

Experience architecting solutions where AI tools handle implementation while you focus on business logic and edge cases
Track record of rapid prototyping and iteration in ambiguous problem spaces
Experience building with LLMs as development partners, not just API integrations
Proficiency in graph database query languages such as Cypher, Gremlin, or SPARQL
Knowledge of database technologies such as SQL, NoSQL, and ORM frameworks
Experience with MLOps tooling, model versioning, and AI deployment pipelines
Familiarity with vector databases (e.g., OpenSearch,FAISSDB) and embedding management

Lead Software Engineer - Applied AI Engineer (Agentic/ Gen AI)