Staff Software Engineer, Cloud Agentic AI

• Own the end-to-end architecture, technical roadmap, and core goal for agent memory systems, dynamic context synthesis pipelines, graph-based cloud representations, and hybrid search/RAG platforms.
• Lead the design and implementation of low-latency context caching, token compression/pruning strategies, working memory buffers, and long-term episodic knowledge stores for autonomous agents.
• Architect high-throughput, low-latency distributed systems and automated benchmarking frameworks to ensure sub-second cloud state aggregation, high retrieval recall, and hallucination mitigation.
• Ensure all context and memory subsystems meet stringent enterprise-grade multi-tenancy standards, tenant data isolation policies, compliance mandates, and fine-grained access controls.
• Partner across research (e.g., DeepMind) and platform service teams to standardize shared context models and APIs, while mentoring engineers and upholding architectural review standards.

Minimum qualifications:

• Bachelor's degree in Computer Science, AI/ML, Data Systems, Information Retrieval, a related technical field, or equivalent practical experience.
• 8 years of experience in software development.
  
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
• 2 years of experience building infrastructure on cloud platforms.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• Experience building low-latency, high-availability distributed storage systems and APIs on major cloud platforms.
• Expertise in agent memory (working/episodic), context caching, token pruning, vector search, and knowledge graphs.
• Ability to define technical roadmaps, author comprehensive design docs, and align multi-organization stakeholders. Demonstrated skill in coaching engineers and clearly communicating complex architectures to leadership and research partners.
• Track record in hybrid search, graph databases, and querying complex cloud telemetry and topology.
• Background in engineering secure, multi-tenant cloud architectures with strict data isolation and compliance controls.

• Bachelor's degree in Computer Science, AI/ML, Data Systems, Information Retrieval, a related technical field, or equivalent practical experience.
• 8 years of experience in software development.
  
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
• 2 years of experience building infrastructure on cloud platforms.