Senior Software Engineer, Analytics Data & Applied AI

We are hiring a Senior Software Engineer to work on an internal AI product analytics agent at Unity. This agent enables teams across Unity—including product managers, engineers, analysts, and leadership—to ask questions of our product data in natural language. This role will join the data-facing half of the team, focusing on both the analytics datasets and pipelines the agent depends on, as well as the agent capabilities built on top of them, such as retrieval, knowledge, evaluation, and answer quality.

This agent’s effectiveness relies on the data and knowledge layer beneath it, and you will own that layer. You will collaborate daily with data scientists and analysts who are both your closest collaborators and your users. Requirements are still evolving, so you will have significant influence over what gets built.

Responsibilities

• Own and improve the analytics datasets that the agent queries, including data modelling, semantic definitions, and the documentation and metadata that make those datasets legible to an LLM.
• Build and maintain the ETL and transformation pipelines that feed those datasets, and raise the bar on their correctness, freshness, and testability.
• Improve how the agent finds and uses knowledge: knowledge base search, retrieval quality, context construction, and prompt history.
• Build and extend the evaluation systems that tell us whether the agent is answering correctly, and use them to drive measurable quality improvements.
• Develop backend agent workflows covering prompt handling, orchestration, and response generation.
• Build user-facing features that make analytics workflows faster for technical and non-technical colleagues alike.
• Partner with data scientists to turn recurring analytics needs into reusable, scalable capabilities rather than one-off answers.
• Help set the roadmap and technical direction for the data and quality side of the platform.

Requirements

• Strong software engineering fundamentals and experience building and shipping production systems.
• Hands-on data engineering experience: SQL, data modelling, warehouse or lakehouse design, and building pipelines that other people depend on.
• Experience working with a cloud data warehouse, ideally BigQuery, and with a pipeline orchestration framework.
• Experience with LLM and agent systems, or a clear pull towards them, especially retrieval quality and how you measure whether an answer is any good.
• Comfort working without a fully specified brief, and a bias towards putting something usable in front of users early.
• Genuine enthusiasm for working alongside data scientists and analytics users, and for shaping the product around how they actually work.

Nice to Have

• A background in data science, analytics engineering, or analytics infrastructure.
• Experience building data products that non-specialists can use without hand-holding.
• Experience with data quality, lineage, governance, or metadata tooling.
• Experience evaluating LLM outputs systematically, for example building eval sets, scoring rubrics, or feedback loops.

Pay

We determine the base salary range for this role based on your primary work location:

• Zone A: $135,800 - $203,600 USD gross
• Zone B: $153,400 - $230,200 USD gross
• Zone C: $172,400 - $258,600 USD gross

Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate’s relevant experience, professional background, and skill set.

Benefits

While specific benefits vary by country and employment status, here are some of the ways we strive to take care of our eligible team members globally:

• Comprehensive health, life, and disability insurance
• Commute subsidy
• Employee stock ownership
• Competitive retirement/pension plans
• Generous vacation and personal days
• Support for new parents through leave and family-care programs
• Office food and snacks
• Mental Health and Wellbeing programs and support
• Employee Resource Groups
• Global Employee Assistance Program
• Training and development programs
• Volunteering and donation matching program