Senior Manager, Data Science & AI

At SolarWinds, 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 SolarWinds and grow with us!

The Role We are moving from traditional analytics to a Google Cloud–centric, AI‐driven organization built on BigQuery, 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 BigQuery + 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.

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 SolarWinds.

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 BigQuery/dbt models, and Vertex/Gemini to build agents that are grounded, auditable, and safe. , churn, propensity, adoption, expansion, forecasting): Problem framing, feature design, model selection, evaluation. Deployment on Vertex AI / BigQuery ML with robust MLOps.

Writebacks into BigQuery and integration into Tableau, workflows, or agents. Ensure AI outputs are anchored in governed dbt models and BigQuery 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 (BigQuery, 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, BigQuery ML, Glean).