12+ years of experience in data science and AI/ML, with a proven record of scaling AI systems from research to production
Proven ability to lead technical delivery across multiple concurrent workstreams
Experience managing large multi-team programs, focusing on technical risk and delivery quality
Exceptional stakeholder management and communication skills, especially with senior executives
Hands-on experience with LLM and agentic systems, including prompt engineering and multi-agent orchestration
Deep expertise in model evaluation and applied statistics for generative systems
Strong proficiency in Python and modern data science/ML stack
Responsibilities
Provide technical oversight of all agentic AI workstreams from design to operation
Define the technical strategy and architecture for agentic systems
Manage technical delivery across streams, resolving blockers and ensuring quality
Establish evaluation frameworks for LLM and agent performance
Guide the design of scalable ML platforms and workflows
Ensure AI reliability and security across deployed systems
Utilize modern AI tools to enhance work quality and efficiency
Benefits
Collaborative work environment with experienced professionals
Opportunities for mentorship and leadership development
Engagement in high-stakes technical decision-making
Access to cutting-edge AI tools and technologies
Involvement in shaping the future of AI within the organization
Full Job Description
We're looking for a Principal Data Scientist to serve as the technical lead across an entire agentic AI program. This role is ideal for a deeply experienced data science and AI leader who can set direction across many workstreams at once: owning the technical vision, guiding large teams through complex design and delivery challenges, and keeping the full AI/ML program coherent, high quality, and moving at pace.
In this role, you will be the senior technical authority over every agentic AI workstream in the program, spanning a large delivery organization. You'll set architecture and evaluation standards, manage technical delivery across streams, and act as the trusted voice on technical decisions with client leadership. You'll partner closely with executives to define the AI roadmap and make high-stakes decisions that determine how agentic AI scales across the organization.
What You'll Do
Craft & Delivery
Provide technical oversight of all agentic AI workstreams, from problem framing and design through evaluation, deployment, and ongoing operation
Define the technical strategy and reference architecture for agentic systems, including multi-agent orchestration, tool and function calling, RAG patterns, vector databases, embeddings, and streaming responses
Manage technical delivery across streams, identifying cross-team dependencies, resolving technical blockers, and keeping quality and velocity high as the program scales
Set the standard for model development, experimentation, and the path from research to production across the program
Establish rigorous evaluation frameworks for LLM and agent performance, including quality, safety, hallucination, cost, and latency, so progress is measured and not assumed
Guide the design of scalable ML platforms, pipelines, and workflow orchestration that support event-driven, asynchronous operations at scale
Ensure AI reliability, security, and scalability across deployed systems, including observability, monitoring, and debugging in production
Bring an AI-forward mindset to your daily work, using tools like Claude, Cursor, and other modern AI assistants to ship higher-quality work at pace
Collaboration & Communication
Serve as the technical face of the AI/ML program to senior client stakeholders, building trust through clear, honest communication on progress, risk, and tradeoffs
Co-define the AI roadmap with executive leadership, operating as a peer in strategic technical conversations
Translate complex technical concepts for executive, engineering, and business audiences, turning depth into decisions others can act on
Align data science, engineering, product, and business teams so every workstream ladders up to shared priorities and measurable outcomes
Leadership & Influence
Lead and influence a large, multi-team delivery organization, setting expectations for technical excellence across every stream
Define and champion data science and AI engineering standards that shape how the program builds, evaluates, and operates AI systems
Review and elevate the quality of work across teams, giving direct feedback that makes the work better
Mentor technical leads and senior practitioners, developing the next generation of technical leaders
Own high-stakes technical decisions with program-wide weight, balancing innovation, risk, and delivery speed
Drive technical vision, defining not just what gets built, but how agentic AI practice evolves across the program over time
What You'll Bring
12+ years of experience in data science and AI/ML, with a record of taking AI systems from research to production at enterprise scale
Proven track record leading technical delivery across multiple concurrent workstreams or teams, with influence that extends well beyond the immediate team
Experience leading, or technically overseeing, large multi-team programs, including managing technical risk, dependencies, and delivery quality
Exceptional stakeholder management and communication skills, including credibility with senior executives and client leadership
Hands-on experience with LLM and agentic systems, including prompt engineering, function/tool calling, multi-agent orchestration, RAG architectures, vector databases, embeddings, and streaming LLM responses
Deep expertise in model evaluation, experimentation design, and applied statistics, including evaluation approaches specific to generative and agentic systems
Strong proficiency in Python and the modern data science and ML stack
Expertise in MLOps and AI infrastructure, including model versioning, monitoring, deployment automation, and reproducibility
Strong software engineering fundamentals, including system design, API design, code quality, and strong unit testing practices
Experience with distributed systems, event-driven architectures, and workflow orchestration tools
In-depth experience with AWS, especially the AWS GenAI offering (e.g., Amazon Bedrock); working knowledge of other cloud platforms
Familiarity with both SQL and NoSQL databases, including scalable design patterns
Working knowledge of AI governance, responsible AI, and compliance considerations in production environments
Helpful Extras and Unique Skills
Experience supporting AI programs in regulated industries such as life sciences, healthcare, or financial services
Experience in a consulting or client-facing technical leadership role
Background in fine-tuning, evaluation automation, or agent safety and guardrails
You'll Do Well Here if You Are
A doer. You see something broken and fix it. You'd rather move on clarity than wait for certainty.
A fast learner who knows you don't know everything. The AI landscape changes weekly. You're senior enough to know better and curious enough to keep learning anyway.
Direct in a way that makes the work better. You give honest feedback. You'd rather have the hard conversation than blow smoke.
Obsessed with craft. You know genius is in the details. You ship exceptional, not perfect, and you don't put your name on work you wouldn't stand behind.
Built for ownership. You honor commitments, admit mistakes fast, and back your teammates when a decision costs something. No handoffs, no finger-pointing.
All in. You treat clients' businesses like your own. You take the work seriously without taking yourself seriously.
Resourceful when the budget, timeline, or team is tight. Constraints don't slow you down. They sharpen you.
Glad to be in the room with people who care as much as you do. Our teams average fifteen-plus years of experience. We hire people who push each other to do better work.
