Senior Software Engineer, Data and Infrastructure, Professional Intelligence, DeepMind

Google•Mountain View, CA

6d•$174,000 - $252,000

About The Position

At DeepMind, the mission is to build the world's first general-purpose learning agent. This role works with AI agents developed by machine learning and neuroscience research scientists, building software and infrastructure to support agent capabilities and evaluation. The responsibilities described include creating systems for agent testing, developing test problems, visualizing results, building leaderboards, and testing algorithms on robots. The role also focuses on production systems for LLM agents that search, read, reason over, and cite private corporate information, with particular attention to data access controls, reliability, testing, and operational quality. DeepMind is an interdisciplinary AI lab focused on advancing AI to address global challenges and accelerate product innovation. The organization states that it prioritizes safety and ethics and aims to use its technologies for public benefit and scientific discovery. Individual pay is determined by job-related skills, experience, and relevant education or training. The stated US compensation is $174,000–$252,000, plus a 15% bonus target, equity, and benefits.

Requirements

Bachelor's degree in Computer Science or equivalent practical experience.
Experience in Python with modern toolchains and frameworks such as uv, ruff, FastAPI, and Pydantic.
Experience building and operating data pipelines using one or more of Apache Beam, Dataflow, Flink, and Spark, and understanding trade-offs between batch and streaming designs.
Experience with data storage solutions such as SQL/Postgres, NoSQL, blob storage, search indexes, and vector databases, and understanding trade-offs between them.
Experience using coding agents to develop code and tests to specification.

Nice To Haves

Experience with infrastructure-as-code such as Terraform and serverless or container platforms such as Cloud Run and GKE.
Experience implementing access control and security in data systems, such as row-level security, IAM, and VPC Service Controls, or working with sensitive or regulated data.
Experience with document processing at scale, such as OCR, PDF/Office rendering, e-discovery, or load-file formats.
Experience in start-up-like environments where priorities can change quickly, and enthusiasm for learning new technologies and teaching teammates.
Exposure to production systems that rely heavily on ML models, including batch inference with large language models.

Responsibilities

Act like an owner by asking questions, proposing solutions, building consensus, and driving execution from concept to delivery.
Design and implement skills, plugins, and typed tools for LLM agents that search, read, reason over, and cite large private corporate information.
Maintain a strong focus on code and product quality, testing, CI/CD, monitoring, and on-call; keep live systems healthy while building the next generation.
Implement fine-grained, per-document access controls across search indexes, databases, and storage, and ensure every access is logged.
Use the latest AI coding agents to work efficiently and help the team do the same.
Create systems for agent testing using 2D and 3D games and develop test problems within physics simulators.
Create graphical visualizations of results, build competitive agent leaderboards, and test new algorithms on robots.