Applied AI ML Director AGENT BUILDER PLATFORM

Job Summary
As a Director of Applied AI ML Engineering in the Agent Builder Platform team within the Corporate AI ML Technology Team you will own the technical vision and delivery of the Agent SDK and the agentic systems it enables. You will lead a multidisciplinary team to translate research into robust observable and responsible agent solutions. Together we drive innovation in agentic workflows data science rigor and safe AI practices. You will have the opportunity to shape the firms approach to autonomous agents and empower teams across the organization.

Job Responsibilities

• Define and drive the technical vision and roadmap for the Agent SDK and long-running agentic workflows.
• Set architectural direction for SDK components including task orchestration state management checkpointing and retry logic.
• Champion data science rigor by establishing measurement experimentation and evaluation frameworks for agent performance.
• Oversee the design and optimization of ML pipelines for training fine-tuning and inference of models powering agent intelligence.
• Direct the instrumentation strategy for observability feedback loops and continuous improvement of autonomous agents.
• Guide the adoption and extension of agent frameworks supporting multi-step reasoning tool use and multi-agent coordination.
• Build mentor and scale a high-performing team of ML engineers data scientists and platform engineers.
• Collaborate with engineering data science product and business stakeholders to align the teams roadmap with enterprise AI strategy.
• Serve as the primary technical point of contact for the Agent SDK platform communicating complex trade-offs to diverse audiences.
• Champion safe responsible and compliant agent systems by implementing guardrails and policy enforcement mechanisms.
• Foster a collaborative environment where research insight translates into production impact.

Required Qualifications Capabilities and Skills

• 10 years of experience in machine learning engineering applied data science or ML platform development.
• 3 years of experience in a leadership role managing teams of engineers and/or data scientists.
• Strong technical depth across the ML and data science stack including ML frameworks (PyTorch TensorFlow JAX scikit-learn) and LLM serving and fine-tuning toolchains.
• Proven experience designing and delivering SDKs platforms or agent development kit including API design and documentation strategy.
• Expertise in distributed and long-running systems including state machines workflow orchestration checkpointing and fault-tolerant design.
• Fluency in LLM-based agent architectures prompt engineering tool use and multi-agent coordination patterns.
• Demonstrated ability to craft and drive a technical vision that maximizes business impact and influences decision-making.
• Proven ability to build mentor and retain senior technical talent and foster a collaborative team culture.
• Strong foundation in experimental design statistical analysis and evaluation methodology.
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences.
• Experience integrating data science rigor and responsible AI practices into production systems.

Preferred Qualifications Capabilities and Skills

• Experience building or contributing to open-source ML or agent frameworks such as LangChain AutoGen Haystack or MLflow.
• Background in ML evaluation and monitoring at scale including drift detection A/B testing and automated regression testing.
• Deep familiarity with multi-agent system design including communication protocols task delegation and conflict resolution.
• Experience overseeing AI workload deployment on managed ML platforms such as AWS SageMaker or Bedrock.
• Background leading AI engineering in regulated or high-reliability environments especially financial services or asset and wealth management.
• Experience integrating user and stakeholder feedback loops into continuous model and system improvement processes.

• Experience designing developer experience writing technical documentation and supporting internal developer adoption.