{"id":2932543,"url":"https://alion.io/job/google-deepmind-software-engineer-gemini-app-skills-platform","title":"Software Engineer, Gemini App Skills Platform","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":335000,"period":"year","method":"role_country_seniority_unknown","sample_n":8836},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"C++","optional":false},{"name":"Clean Architecture","optional":false},{"name":"Context Engineering","optional":false},{"name":"Function Calling","optional":false},{"name":"Gemini","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false}],"status":"live","first_seen_at":"2026-10-20T12:12:29Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-25T19:08:37Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"About the job\nJoin DeepMind’s mission to solve intelligence and benefit humanity by building the next generation of agentic AI. As a Software Engineer on the Gemini App Skills Platform, you will be a key contributor to the extensible execution layer that transforms Gemini from a conversational assistant into an action-oriented, universal agent.\nIn this role, you will architect the systems that allow Gemini to discover, retrieve, and execute modular capabilities (skills) across Google, DeepMind, and third-party ecosystems. Your work will bridge foundation model intelligence and real-world execution spanning dynamic context engineering (system instructions), low-latency routing algorithms, and automated evaluation frameworks. While this role focuses heavily on Large Language Model (LLM) behavior and evaluation, you will dive directly into Gemini app’s production serving infrastructure (primarily C++) and Python evaluation pipelines to make high-impact, hands-on architectural enhancements. You will have an opportunity to operate at the center of Google’s flagship AI product. You will see your code, prompts, and evaluation standards actively shape the user experience for hundreds of millions of users across web, mobile (Android/iOS), and Chrome, helping define how people and AI interact with software.\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: $174000 - $252000 (USD) + 15% bonus target + equity + benefits\nLearn more about benefits at Google.\nResponsibilities\nDesign and build intelligent skill discovery, hybrid routing architectures, and low-latency C++ serving components across Gemini on web, mobile, and Chrome.\nPioneer dynamic system instructions, prompt representations, and semantic retrieval schemas that enable Gemini to seamlessly navigate expanding skill catalogs without attention dilution or quality regressions.\nDesign automated evaluation frameworks (auto-raters, simulated environments, and benchmarking suites) to rigorously measure single-turn triggering precision, multi-turn tool, and parameter validity.\nPerform in-depth loss analysis on production telemetry, drive iterative prompt/model hill-climbing to surpass quality thresholds, and set standards for system reliability and clean architecture across the organization.\nPartner closely with DeepMind Research, Search, Vertical teams (e.g., local, shopping), and external Engineering teams to onboard new modular capabilities onto the platform.\nQualifications\nMinimum qualifications:\nExperience developing software with large language models, agentic workflows, tool use, or retrieval-augmented generation (RAG).\nExperience designing evaluation datasets, automated rating systems, or conducting error analysis and prompt optimization for generative models.\nPreferred qualifications:\nExperience collaborating cross-functionally across research, product, and platform engineering teams to take novel AI features from prototype to production.\nDemonstrated ability to design experimental setups, analyze model telemetry, and define reproducible metrics for complex 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