Lead Platform Engineer at TD Securities, developing a high performing Trading Risk Warehouse platform. Responsible for ensuring stability and scalability, while managing underlying infrastructure and supporting development teams.
About the role
- Senior AI Platform Engineer designing core AI framework on data platform for financial technology company. Integrating AI services with pipelines and mentoring fellow engineers in a hybrid work environment.
Responsibilities
- 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
- Experience in Information Security (Nice-to-Have)
- Experience with vector databases (pgvector, Pinecone, Weaviate, Milvus, Vespa) (Nice-to-Have)
- Familiarity with event-driven architectures (Kafka, Pulsar) (Nice-to-Have)
- Understanding of retrieval-augmented generation (RAG) patterns (Nice-to-Have)
- Background in authorization/identity systems (ReBAC, RBAC, Zanzibar-style) (Nice-to-Have)
- Familiarity with observability (OpenTelemetry, DataHub, MLflow, Prometheus) (Nice-to-Have)
- Experience in enterprise AI governance (audit, lineage, compliance) (Nice-to-Have)
- Contributions to open-source AI frameworks (LangChain, OpenAI MCP, Hugging Face, etc.) (Nice-to-Have)
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!
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