Senior Manager, Data Science & AI

At Solar Winds, we're a people-first company. Our purpose is to enrich the lives of the people we serve-including our employees, customers, shareholders, partners, and communities. Join us in our mission to help customers accelerate business transformation with simple, powerful, and secure solutions.

The ideal candidate thrives in an innovative, fast-paced environment and is collaborative, accountable, ready, and empathetic. We're looking for individuals who believe they can accomplish more as a team and create lasting growth for themselves and others. We hire based on attitude, competency, and commitment. Solarians are ready to advance our world-class solutions in a fast-paced environment and accept the challenge to lead with purpose.

If you're looking to build your career with an exceptional team, you've come to the right place. Join Solar Winds and grow with us!

The Role

We are moving from traditional analytics to a Google Cloud-centric, AI‐driven organization built on Big Query, dbt, Vertex AI, and Glean.

As our Senior Manager of Data Science & AI, you will:

* Lead a high‐performing, distributed team of Data Scientists (US & EMEA).

* Own the design and deployment of production‐grade ML models and AI agents on Big Query + Vertex.

* Be a product‐minded builder who uses AI as a lever for business productivity and automated decision‐making - not as a science project.

You'll combine deep Google stack expertise with a strong sense of business impact and a bias for shipping.

Core Responsibilities

AI Strategy & Vision

* Define and execute a Data Science & AI roadmap that integrates LLMs, GenAI, and classical ML into core functions (GTM, Product, Finance, Operations).

* Partner with Enterprise Data, IT, and business leaders to prioritize use cases by expected impact, feasibility, and time‐to‐value.

* Lean in on the rapidly changing data + AI space (Vertex, Gemini, Glean, agents) and translate platform evolution into a clear plan for Solar Winds.

Agentic Workflows & Applied LLMs

* Lead the design of agentic workflows and AI copilots that:

* Monitor business KPIs and health signals.

* Perform automated root‐cause exploration over governed data.

* Push proactive, explainable "answers" and recommendations to executives and operators.

* Use LLM orchestration, RAG over Big Query/dbt models, and Vertex/Gemini to build agents that are grounded, auditable, and safe.

Production ML Excellence (Big Query + Vertex)

* Own the end‐to‐end lifecycle for predictive models (e.g., churn, propensity, adoption, expansion, forecasting):

* Problem framing, feature design, model selection, evaluation.

* Deployment on Vertex AI / Big Query ML with robust MLOps.

* Write backs into Big Query and integration into Tableau, workflows, or agents.

* Ensure AI outputs are anchored in governed dbt models and Big Query marts to minimize hallucination and maintain executive trust.

Team Leadership & Ways of Working

* Recruit, mentor, and scale a world‐class DS/AI team; set clear expectations for technical quality and business impact.

* Foster a culture of "high‐velocity shipping":

* Lightweight experimentation with fast feedback loops.

* Code reviews, reproducibility, and MLOps best practices as the norm.

* Clear measurement of impact and iteration based on results.

Collaborate tightly with:

* Data Engineering & Platform (Big Query, ingestion, performance/cost).

* Analytics Engineering & BI (semantic layer, dashboards, NLQ).

* Data Governance & Security (policies, access, responsible AI).

Stakeholder Evangelism & Communication

* Act as the internal "how to solve X with AI" consultant:

* Translate ambiguous business problems into tractable DS/AI solutions.

* Explain technical trade‐offs, risks, and constraints in clear language.

* Regularly brief GTM, Finance, Product, and Exec stakeholders on what's possible now, what's next, and what's not worth doing.

AI Innovation

* Stay at the forefront of AI and LLM research and GCP platform capabilities (Vertex, Gemini, Big Query ML, Glean).

* Quickly separate hype from practical value; pilot and harden innovations that can become repeatable, governed patterns for the wider organization.

Required Experience

Experience

* 8+ years in Data…