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)
Support with architecture, design, and implementation of Kubernetes environments. Involving in CI/CD pipelines, multi - cloud orchestration, and providing relevant content for clients.
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