Job Responsibilities:

• Define and evolve agentic AI architectures, including orchestration, retrieval, memory, guardrails, and evaluation

• Act as technical authority for applied AI/ML, making architecture decisions and setting production-readiness standards

• Stay hands-on by reviewing code, prototyping complex components, and unblocking critical technical challenges

• Ensure AI/ML systems are scalable, reliable, secure, observable, and cost-efficient

• Partner with platform, data, and infrastructure teams on distributed systems and training/serving patterns

• Lead, mentor, and grow a high-performing team of applied AI/ML engineers

• Set clear technical expectations, career paths, and standards of excellence

• Foster a culture of strong engineering fundamentals, experimentation, and responsible AI practices

• Hire senior technical talent and raise the bar across the organization

• Oversee delivery of multi-agent systems that automate and scale end-to-end workflows

• Collaborate with product, risk, legal, and compliance partners to ensure solutions are innovative and deployable

Required Qualifications, Capabilities, and Skills:

• 10 years of experience building and deploying applied AI/ML systems, with significant recent hands-on work

• Experience leading and managing teams of senior engineers

• Deep understanding of machine learning and AI fundamentals, including modern generative AI and LLM-based systems

• Proven track record delivering AI/ML solutions to production at scale

• Strong familiarity with distributed systems for training, inference, and state management

• Ability to communicate complex technical trade-offs to both technical and non-technical stakeholders

• Demonstrated experience setting engineering standards and driving operational excellence

• Experience collaborating with cross-functional teams in a regulated environment

• Strong coding and code review skills in Python and modern ML frameworks

• Commitment to responsible AI practices and continuous improvement

• Ability to mentor and develop engineering talent

Preferred Qualifications, Capabilities, and Skills:

• Experience with agentic systems, multi-agent architectures, and LLM evaluation frameworks

• Experience deploying AI workloads on AWS (e.g., SageMaker, Bedrock) or equivalent platforms

• Background building AI systems in regulated or high-reliability environments

• Experience integrating user feedback loops for continuous model and system improvement

• Familiarity with financial services or asset and wealth management workflows

• Track record of hiring and developing senior technical talent

• Experience fostering a culture of experimentation and innovation

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.