[Hiring] Principal AI/ML Engineer @NMDP

Role Description

The Principal AI/ML Engineer is a senior individual contributor who sits at the intersection of deep engineering and technical delivery leadership. This is not a management role, but an amplifier role. You write serious production code, and you use that credibility to drive the sprint by unblocking engineers, making implementation calls, coordinating across teams, and ensuring that every technical dependency between your squad and the rest of the organization gets resolved fast.

You will report to the Senior Director, AI & Architecture and work closely with the AI Architect and AI Engineers. You are the engineering face to the engineering teams across the organization. You are the person who turns AI architecture and strategy into running production systems.

You provide technical leadership and deliver innovative, scalable solutions that leverage artificial intelligence and machine learning to meet complex business needs. This role balances technical excellence with feasibility, cost, maintainability, and ethical use of AI and data. You are an exceptional engineer who has grown into the technical leadership of sprint delivery without stepping into architecture ownership or people management.

The successful candidate has a strong track record of delivering production-grade systems, influencing architecture decisions, and partnering effectively with business and technical stakeholders. This role extends beyond hands-on development to include technical design, mentoring, cross-functional collaboration, and influencing architecture.

Qualifications

• Knowledge of scalable architecture patterns for traditional ML, GenAI and Agentic AI.
• AWS experience with SageMaker, Textract, Bedrock, Agentcore etc.
• Strong familiarity with multiple LLMs and embedding models (e.g., OpenAI, Anthropic, Meta, Google, Hugging Face).
• Proficiency in multiple vector databases for semantic search and contextual memory.
• MLOps and LLMOps practices, including CI/CD, model monitoring, versioning, drift detection, and governance.
• Prompt engineering and management practices, including prompt versioning, A/B testing of prompts, and experience with prompt management tools.
• Eval frameworks like Promptfoo, DeepEval or equivalent.
• AI/ML observability stacks such as Dynatrace, Weights & Biases, Langsmith or similar tools.

Requirements

• Hands-on experience designing and building AI/ML solutions from prototype to production.
• Proven ability to drive technical delivery in an agile/sprint environment to keep engineering moving.
• Exposure to MLOps practices: model versioning, experiment tracking, deployment pipelines.
• Experience with MCP (Model Context Protocol), and Familiarity with A2A patterns, or emerging agentic AI frameworks.
• Strong Python development skills, including frameworks and libraries for ML, GenAI, and Agentic AI best practices.
• Deep understanding of software engineering, including modular design, testing, version control (Git), and CI/CD pipelines.
• Proven track record of building and running PoCs to validate architecture and feasibility.
• Experience working in agile environments, participating in sprints and cross-functional delivery.
• Ability to communicate technical concepts clearly to a wide range of stakeholders.
• Eagerness and ability to quickly learn and apply new AI/ML and automation technologies.
• Demonstrated commitment to learning and applying emerging technologies responsibly.

Benefits

• Medical, dental, vision, life and disability insurance.
• Accident/critical illness/hospital benefits.
• Well-being, legal, identity theft and pet benefits.
• Retirement plans.
• Paid time off/holidays.
• Leave and incentive plans for eligible employees.