This role represents a rare opportunity to define and build the AI capabilities of a newly standalone company (DePuy Synthes). You will shape how generative and agentic AI is designed, governed, reused and scaled, while leading a team that turns emerging technologies and priority business needs into enterprise platforms, accelerators and strategic applications.
Locations (2)
Raritan, New Jersey, United States
Bengaluru, Karnataka, India
Compensation
The anticipated base pay range for this position is $140,000.00 - $241,500.00
Responsibilities
Define and evolve the enterprise AI strategy, architecture and roadmap across Databricks Mosaic AI, Amazon Bedrock, AgentCore, the enterprise model gateway and related services.
Architect the agentic runtime, including agent orchestration and mesh, MCP tool and skill registries, Agent-to-Agent interoperability, agent identity, entitlements and secure tool execution.
Design reusable context and knowledge services, including RAG and Graph RAG, vector stores, knowledge graphs such as Amazon Neptune, shared memory and context assembly.
Establish patterns for LLMOps and MLOps, observability, evaluation, Responsible AI, security and AI cost management in partnership with platform and governance teams.
Create a discoverable catalog of AI services, models, agents, tools, skills and reference patterns that teams can reuse across the enterprise.
Requirements
Bachelor's degree in Computer Science, Engineering or a related technical field
Lead end-to-end AI system design and architecture for a major Generative AI platform, ensuring secure, resilient, compliant, and enterprise-aligned solutions.
Compensation
Salary Range: $90,000 - $157,500 Annual
Responsibilities
Own end-to-end architecture and system design for a major AI platform domain, including model integration, orchestration, APIs, data flows, and downstream system interactions.
Define and implement reference architectures, design standards, integration contracts, and non-functional requirements (NFRs) for the platform area.
Translate business and product requirements into scalable, secure, resilient, and maintainable AI solution designs.
Partner with business stakeholders, product managers, engineers, data scientists, platform teams, and security teams to deliver enterprise-ready AI systems.
Design solutions leveraging cloud architecture principles on AWS, Azure, or Google Cloud, ensuring interoperability, scalability, observability, and operational readiness.
Requirements
Bachelor’s degree in Computer Science, Computer Information Systems, Engineering, Mathematics, or a related discipline; Master’s degree preferred.
Architect and build scalable machine learning models and AI systems that directly impact Workday's core enterprise applications.
Compensation
The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants.
Responsibilities
Design, develop, and deploy scalable machine learning models and AI systems
Take full ownership of the ML lifecycle, including data extraction, feature engineering, model training, deployment, optimization, and continuous monitoring in a high-scale production environment
Partner closely with Data Scientists, Software Engineers, Product Managers, and UX Designers to translate complex business problems into robust AI solutions
Establish and advocate for engineering best practices, robust MLOps processes, and highly optimized code
Guide and mentor junior engineers, conduct code and architecture reviews, and help shape the technical roadmap for the team
Requirements
Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related highly quantitative field (or equivalent practical experience)
Senior Machine Learning EngineerNewWorkday · Vancouver, Canada