The company is looking to shape the future of their agentic platform by leveraging advanced machine learning (ML) techniques to tackle complex, large-scale challenges and deliver impactful customer experiences in cybersecurity applications.
Requirements
- Strong coding skills in Python and proficiency with SQL, including performance/scalability optimization.
- End-to-end experience designing and deploying RAG systems (indexing strategy, retrieval optimization, reranking).
- Expertise with LLMs and fine-tuning techniques (e.g., LoRA/QLoRA), prompt/agent design, and function-calling patterns.
- Familiarity with Google ADK (agents, long-term knowledge/memory) and LlamaIndex (graph construction, query engines).
- Strong background in NLP and/or recommender systems; experience with evaluation methods and dataset curation.
- Experience with microservices on GCP (e.g., GKE/Cloud Run, Pub/Sub, Vertex AI, CloudSQL/BigQuery) and real-time streaming.
- Hands-on experience with vector search and RAG frameworks.
Responsibilities
- Design & build agentic systems: Architect workflows and POCs using frameworks such as Google ADK and LlamaIndex; implement tool use, function calling, and multi-step planning.
- Retrieval & reasoning: Develop RAG pipelines (indexing, retrieval, reranking), code-interpreter/tool execution flows, and robust context management.
- Model evaluation: Define evaluation suites for performance, efficiency, safety, and business alignment; analyze latency, quality, and cost trade-offs.
- Scale & reliability: Deploy models and agents to production; build scalable ML pipelines for batch and real-time/streaming use cases; implement monitoring and guardrails.
- Platform & CI/CD: Drive end-to-end delivery with modern CI/CD; automate testing, rollout, and experiment tracking.
- Strategy & incubation: Contribute to AI product vision; incubate new AI initiatives and design microservices-based solutions on GCP.
- Lead the design, prototyping, and productionization of AI agent systems that solve complex user and business problems in cybersecurity applications.
Other
- This role is located at our Santa Clara Headquarters Campus 3 days a week.
- Collaboration & leadership: Partner with ML engineers, data scientists, and product to deliver roadmaps; mentor teammates and lead technical design reviews.
- Documentation & communication: Maintain clear specs and decision records; communicate complex concepts to technical and non-technical audiences.
- Ability to work independently and in cross-functional teams with excellent written and verbal communication.
- M.S. or Ph.D. in a technical field (or equivalent practical experience).
