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X In most instances, this position requires in-person interviews as part of the hiring process.
Minimum qualifications: - Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or equivalent practical experience
- 5 years of experience in software development, including coding experience in Python, C , Java, JavaScript, or R.
- 3 years of experience in ML system design and optimizing ML infrastructure (e.g., distributed training, model deployment, evaluation, data processing).
- Experience developing autonomous agents, multi-agent workflows, or agentic frameworks (e.g., AutoGen, CrewAI, LangGraph, ADK, tool-use/function-calling, or multi-agent RL).
- Experience designing, pre-training, fine-tuning, or evaluating Large Language Models (LLMs) and multimodal foundation models.
Preferred qualifications: - Master's degree or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline.
- First-author scientific publication submission(s) on agents in machine learning and NLP for conferences, journals, or public repositories (e.g., NeurIPS, ICML, ICLR, ACL).
- Proven experience independently driving engineering delivery in rapid SWAT, Pathfinding, or Forward Deployed Engineering (FDE) environments.
- Experience building complex evaluation benchmarks, test harnesses, or simulation environments.
- Experience in RL, reward modeling, and human/AI preference alignment techniques (e.g., RLHF, RLAIF, DPO).
About the jobIn this role, you will deconstruct complex strategic requests, design robust agent state machines, and prove viability through functional thinnest viable proofs (TVPs). You will independently lead engineering workstreams to build both generalizable horizontal agents and vertical enterprise solutions, taking novel agentic prototypes directly into the field to solve real customer bottlenecks while mentoring junior engineers.
Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $174000 - $252000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Lead 2-4 week "Strike Sprints" to rapidly prototype advanced agent state machines, tool-use orchestration, and reflection loops, transforming boilerplate programming into intent-driven AI topologies.
- Partner with product and engineering teams via Forward Deployed Engineering (FDE), embedding into their workflows to translate novel agentic prototypes into scalable enterprise solutions.
- Architect and build generalizable horizontal agents (e.g., AutoResearch and AutoFounder) to accelerate engineering/researcher velocity.
- Develop agent architectures, planning frameworks, and self-improving foundation models to advance autonomous AI systems.
- Collaborate across Google to disseminate technical playbooks and optionally paublish breakthroughs at ML conferences.
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