{"id":3528195,"url":"https://alion.io/job/google-deepmind-software-engineer-applied-ai-agents-professional-intelligence","title":"Software Engineer, Applied AI Agents, Professional Intelligence","company":{"id":4,"name":"Google DeepMind","domain":"deepmind.google","url":"https://alion.io/company/deepmind","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":null},"role":"Backend","role_family":"Backend","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mountain View, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":157000,"max_usd":339000,"period":"year","method":"role_country_seniority_unknown","sample_n":9411},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Function Calling","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"TypeScript","optional":false},{"name":"Fine-tuning","optional":true},{"name":"GCP","optional":true},{"name":"Red Teaming","optional":true},{"name":"Reinforcement Learning","optional":true},{"name":"Reinforcement Learning","optional":true}],"status":"live","first_seen_at":"2026-10-30T14:41:34Z","employer_posted_date":"2026-10-30","last_verified_at":"2026-11-04T02:56:16Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"About the job\nAt DeepMind our mission is to build the world's first general-purpose learning agent. Central to this mission is the complex task of measuring the intelligence of our prototypes. As a Software Engineer, you will be working with the AI agents developed by our exceptional team of Machine Learning and Neuroscience research scientists. Your responsibilities will include everything from creating systems for agent testing using 2D and 3D games to developing test problems within physics simulators. You will create graphical visualization of results, build competitive agent leaderboards and test new algorithms on robots. To succeed in this role you will need to have a strong foundation in software engineering and enjoy working on a wide range of challenging problems within a mission-driven team.\nArtificial intelligence will be one of humanity’s most transformative inventions. At DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.\nWe are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.\nIndividual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits\nLearn more about benefits at Google.\nResponsibilities\nAct like an owner ask questions, propose solutions, build consensus, and drive execution from concept to delivery.\nBuild agent capabilities design and implement skills, plugins and typed tools for LLM agents that search, read, reason over and cite large private corporate.\nMake outputs verifiable build grounding and citation checks, access-aware retrieval, and automated review of agent-authored knowledge, so every result can be audited back to its sources.\nLead evaluation build evaluation suites and datasets with subject matter experts, measure factual accuracy, citation fidelity and multi-step reasoning, and use the results to drive improvements.\nShip to production strong code quality, testing, CI/CD and monitoring for agent systems used daily by professionals.\nQualifications\nMinimum qualifications:\nBachelor's degree in Computer Science, or equivalent practical experience.\nExperience in Python or TypeScript with modern toolchains and frameworks.\nExperience building/shipping applications powered by LLMs: prompting, tool use or function calling, retrieval-augmented generation, and agent orchestration.\nExperience designing evaluations for LLM or ML systems and using them to drive measurable quality improvements.\nExperience owning production software end-to-end, from design and implementation to deployment, monitoring and iteration on user feedback.\nExperience using coding agents to develop code and tests to specification.\nPreferred qualifications:\nExperience with agent frameworks and protocols or agentic coding environments.\nExperience with search and 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