Senior AI Platform Engineer

Type: W2 Full-time, not offering sponsorship
Pay Range: $180,000-200,000 per year
Location: San Francisco, CA - Hybrid (must be onsite 6 times per month)
Title: Senior AI Platform Engineer


Job Description

We are building a next-generation Agentic AI Framework that integrates Model Context Protocol (MCP), Agent-to-Agent (A2A) communication, Machine Learning, and advanced orchestration on top of our enterprise big data platform.

We are looking for Senior AI Platform Engineers to join our R&D team. These engineers will design and implement the core AI framework, ensuring it seamlessly integrates with our big data infrastructure, and enabling scalable, intelligent, and autonomous data-driven systems.

What You Will Get to Do

• Design and build a scalable Agentic AI framework on top of our data platform.
• Implement MCP- and A2A-based architectures for agent collaboration and orchestration.
• Integrate AI services with data pipelines (Airflow, Spark, Trino, StarRocks, DBT).
• Build APIs, SDKs, and tooling to enable other teams to use the framework.
• Work with platform and application teams to ensure secure, reliable, and multi-tenant deployment of AI agents.
• Evaluate new agentic AI, LLM, and orchestration technologies and recommend adoption.
• Mentor other engineers and contribute to AI engineering best practices.

Core Skills (Must-Have)

• Strong programming skills in Python with 5+ years of experience
• Proven experience with data engineering or distributed systems (Spark, Hive, Trino, StarRocks, DBT, Airflow, Kubernetes).
• Deep understanding of LLM-based systems and agent frameworks (LangChain, LlamaIndex, DSPy, OpenAI MCP, A2A).
• Hands-on experience with API design & integration (REST, GraphQL, gRPC).
• Knowledge of cloud infrastructure & container orchestration (Kubernetes, Docker).
• Strong understanding of IAM, security, and multi-tenancy in enterprise systems.
• Track record of building production-grade AI/data platforms.

Desired Skills (Nice-to-Have)

• Experience in Information Security.
• Experience with vector databases (pgvector, Pinecone, Weaviate, Milvus, Vespa).
• Familiarity with event-driven architectures (Kafka, Pulsar).
• Understanding of retrieval-augmented generation (RAG) patterns.
• Background in authorization/identity systems (ReBAC, RBAC, Zanzibar-style).
• Familiarity with observability (OpenTelemetry, DataHub, MLflow, Prometheus).
• Experience in enterprise AI governance (audit, lineage, compliance).
• Contributions to open-source AI frameworks (LangChain, OpenAI MCP, Hugging Face, etc.).