Sr AI Platform Engineer

Role :

Sr AI Platform Engineer Required experience API development: production Python with FastAPI or comparable; versioned REST APIs, contracts, governance.

Batch and real-time data pipelines:

Kafka or comparable streaming, plus CDC or incremental batch; built and operated end-to-end.

Caching and key-value serving:

production Redis or Valkey; cache invalidation, TTL strategies, hot-path serving.

Vector databases and knowledge graphs:

Pinecone, Weaviate, pgvector, Neo4j, or comparable; embeddings and retrieval patterns.

AI software engineering:

hands-on building data infrastructure for AI and ML use cases (RAG, agent tooling, feature serving).

Azure Databricks, Delta Lake, Unity Catalog:

hands-on production experience.

Delta Lake internals:

transaction log, time travel, and Change Data Feed (CDF).

SQL and data modeling:

comfortable with point-lookup vs analytical query patterns.

CI/CD:

GitLab or GitHub Actions; automated tests for data pipelines.

Communication:

works directly with senior architects, product managers, and domain stakeholders. Nice to have Embedded analytical engines: DuckDB or comparable. Microsoft Fabric / OneLake /

Power BI Semantic Models:

production experience.

SLAs and SLOs:

defining and operating for data products or APIs.

MCP-style tooling:

data access for AI agents.

Enterprise-scale data serving:

prior work on serving infrastructure at large enterprise