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.

Requirements

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.

Benefits

401 (k) Matching Program
Professional Development Reimbursement
Flexible Personal/Vacation Time Off
Sick Leave
Paid Holidays
Medical
Dental
Vision
Employee Assistance Program
Parental Leave
Discounts on fitness clubs, travel, and more!

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Pythondata engineeringdistributed systemsAPI designintegrationLLM-based systemsagent frameworkscloud infrastructurecontainer orchestrationproduction-grade AI/data platforms

Soft Skills

mentoringcollaborationbest practices