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$162,000–$254,750.
Based on 240 similar postings.
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About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1254 open roles
on FindRole.
As the Applied AI/ML Lead - Small Business, you will set the technical direction for agentic AI products supporting Small Business Lending. You will lead a small team to design and produce agent behaviors across prompts, retrieval, tools, evaluation, routing, and memory while owning the measurement loop for system performance. Your daily work involves translating ambiguous needs into solution strategies, managing projects from discovery through production, and defining safety guardrails for non-deterministic systems. You will utilize Python, SQL, and LLM orchestration frameworks like LangChain or LangGraph. Technical requirements include experience with RAG, vector databases, fine-tuning foundation models, and observability tools like Arize Phoenix. You will ensure reliable, cost-aware solutions within a regulated financial environment by managing data pipelines and complex statistical methods.
Set the technical direction for applied AI products within the Small Business Lending division.
Lead the design and production delivery of agent behaviors including prompts, retrieval, tools, and memory.
Define evaluation, safety, and guardrail approaches for non-deterministic AI systems.
Manage projects from discovery through production while overseeing priorities, risks, and dependencies.
Partner with Engineering to develop infrastructure, tool APIs, telemetry, and release readiness.
Own the measurement loop to demonstrate system performance and success measures.
Mentor junior team members and communicate complex findings to senior management.
What we're looking for
Master's or PhD degree in computer science or a data science-related discipline.
5+ years of industry experience.
Experience developing and deploying production machine learning or generative AI solutions using Python.
Experience leading AI/ML services from ideation to deployment, including design, code review, automated testing, CI, monitoring, and post-release improvement.
Experience building evaluations and safety controls for nondeterministic and agentic systems.
Experience with data pipelines, SQL, and structured and unstructured data.
Advanced knowledge of statistical methods, experimental design, and A/B testing.
Experience with RAG, vector databases, search, and fine-tuning foundation models or training embeddings.
Python
PyTorch
TensorFlow
Large Language Models
Generative AI
AWS
SageMaker
EKS
Deep Learning
RAG
Reinforcement Learning
Distributed Training
Prompt Engineering
Multi-agent Orchestration
Java
C++
GPU Optimization
Search/Ranking
Recommender Systems
Graph Techniques