AI Analytics Engineer

6 – 8 years of experience in data engineering, analytics engineering, or ML/AI platform engineering.

Key Responsibilities

Design and build a governed Customer 360 platform with semantic layers, APIs, and natural-language access.
Build and manage MCP servers to securely connect Claude and Gemini with BigQuery data and business tools.
Develop AI agent and assistant workflows, including tools, prompts, context, and evaluation.
Implement scalable security, access control, auditing, and data-privacy controls.
Establish LLM evaluation, monitoring, accuracy, latency, and cost-control frameworks.
Use Vertex AI, feature stores, and vector search for AI/ML use cases.
Collaborate with data, analytics, governance, and security teams to productionize solutions.

Skill set
6 – 8 years in data engineering, analytics engineering, or ML/AI platform engineering.
Experience with MCP, Claude, and Gemini, including agents, tools, and MCP servers/clients.
Strong Python, SQL, and BigQuery skills.
Experience with GCP services such as Cloud Run, Vertex AI
Knowledge of semantic layers, governed metrics, data security, PII, and audit controls.
Experience evaluating, monitoring, and optimizing LLM applications for quality, performance, and cost.
Excellent communication and presentation skills are essential.