Sr AI Platform Engineer
Appex Innovation
- Location
- Onsite (Frisco, TX)
- Employment
- Full-time
- Level
- Senior Level
Posted 2 days ago
About the Role
Appex Innovation is seeking a Sr AI Platform Engineer to design and build production-grade data infrastructure for AI and ML use cases. This role involves developing APIs, managing data pipelines, and working with cutting-edge AI technologies.
Skills
Python
FastAPI
Kafka
Redis
Vector Databases
Azure Databricks
Delta Lake
SQL
CI/CD
RAG
Knowledge Graphs
Data Modeling
Unity Catalog
GitLab
GitHub Actions
API Development
Full job details
Job Details:
Role : Sr AI Platform Engineer
Location: Bellevue, Frisco, Kansas, Atlanta (Onsite)
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
Role : Sr AI Platform Engineer
Location: Bellevue, Frisco, Kansas, Atlanta (Onsite)
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
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