Senior Manager of 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.

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 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.

Production ML Excellence (BigQuery + 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 / 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).
• 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 Science / Machine Learning, with 3+ years in a formal leadership role managing high‐impact technical teams.
• Proven track record of taking models and AI solutions into production and delivering measurable business outcomes (revenue, retention, efficiency, or cost).

AI & Modeling Expertise

Hands‐on experience with:

• LLM orchestration and RAG architectures (retrieval over internal data, grounding, prompt chaining).

Explore our comprehensive directory of visa sponsorship jobs from employers worldwide who are ready to sponsor talented international professionals.

• Fine‐tuning or adapting foundation models for business‐specific contexts.
• A broad range of statistical and ML methods across classification, regression, time‐series, and uplift/propensity modeling.
• Ability to apply these methods to large, messy real‐world datasets and ship something that works now, not just in theory.
• Deep Google Stack Experience (Required)

Significant, recent experience with Google Cloud Platform, including:

• BigQuery for large‐scale analytics, feature stores, and model inputs/outputs.
• Vertex AI and/or BigQuery ML for model training, deployment, and monitoring.
• Comfortable designing solutions that combine BigQuery + dbt + Vertex/BigQuery ML end‐to‐end.

Technical Skills

• Strong proficiency in Python (and/or R) and SQL; familiarity with common ML frameworks.
• Practical knowledge of MLOps patterns:
• Model versioning, CI/CD, monitoring, retraining policies.
• Integration of predictions and agents into production workflows and tools.

Mindset & Leadership

Strong bias for action:

• You prefer a working prototype that solves 80% of the problem this quarter over a perfect model six months from now.
• Demonstrated ability to:
• Attract, grow, and retain high‐caliber DS/AI talent.
• Thrive in a fast‐paced environment with evolving priorities.
• Drive a data‐ and AI‐informed culture across multiple functions.

Education

• Master’s or PhD in a quantitative field (CS, Statistics, Mathematics, Physics, Engineering) preferred, or equivalent deep industry experience.

If you want to shape an enterprise AI strategy on Google Cloud, lead a hands‐on DS/AI team, and turn BigQuery + Vertex into real competitive advantage, we’d like to talk.

SolarWinds is an Equal Employment Opportunity Employer. SolarWinds will consider all qualified applicants for employment without regard to race, color, religion, sex, age, national origin, sexual orientation, gender identity, marital status, disability, veteran status or any other characteristic protected by law.

All applications are treated in accordance with the SolarWinds Privacy Notice: https://www.solarwinds.com/applicant-privacy-notice