Applied AI/ML Platform Director: Agent SDK & GenAI

JPMorgan Chase & Co.

Palo Alto (CA)

On-site

USD 250,000 - 420,000

Full time

8 days ago

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Job summary

JPMorgan Chase & Co. seeks an Applied AI/ML Director to lead the Agent Builder Platform. You will design core SDKs, build reusable agent components, and drive scalable, secure platform features for enterprise use.

You will evaluate GenAI techniques, set engineering standards, and collaborate with data, platform, and application teams to ensure measurable business outcomes. This is a hands-on leadership role in a highly scaled environment.

Qualifications

Formal training or certification on applied artificial intelligence and machine learning concepts with 10+ years of applied experience.
10+ years of hands-on experience building large-scale ML systems and platform services used by multiple teams.
Strong software engineering skills with end-to-end delivery from design through implementation, testing, and operation.
Extensive experience with ML frameworks such as PyTorch or TensorFlow.
Hands-on experience with agentic and generative AI system design, including tool use, planning patterns, retrieval-augmented generation, and evaluation methods.
Strong experience with cloud and Kubernetes ecosystems, including building and operating production workloads.
Background in high-performance ML systems, including GPU optimization.
Proven ability to influence across teams through technical leadership and execution.

Responsibilities

Architect and implement core Agent SDK capabilities and reference implementations, with production-ready code.
Build specialized agents and reusable agent components, improving reliability, observability, and evaluation quality.
Translate emerging agentic and generative AI techniques into scalable platform features for teams.
Design and implement evaluation approaches for agent behavior, including quality, robustness, latency, and cost trade-offs.
Develop and optimize model-serving and workflow patterns for agentic systems, including orchestration and tool use.
Partner with product and engineering stakeholders to align platform capabilities to clear success metrics.
Drive technical decisions by clarifying ambiguity, identifying trade-offs, and providing crisp designs.
Improve the agentic platform’s performance, accuracy, and efficiency through profiling and system optimization.