Al System Engineer (W2 Only)

Alpha Consulting Corp. is a consulting company seeking an AI Systems Engineer to architect and engineer their intelligence engine. The role involves building autonomous frameworks, high-scale data pipelines, and ensuring secure, scalable cloud infrastructure for production environments.

Responsibilities:

• Architects and engineers the 'intelligence engine' by building autonomous agentic frameworks, high-scale data pipelines, and the cloud infrastructure required for production
• Bridges the gap between raw data and agentic action, ensuring the system is secure, scalable, and seamlessly integrated into the enterprise ecosystem
• Designs and implements multi-step reasoning loops and autonomous tool-calling frameworks (e.g., ADK, MCP) that allow AI to execute complex business tasks and 'handshake' with external APIs without manual intervention
• Develops production-grade SQL/Python pipelines to ingest, clean, and structure high-velocity data, maintaining the vector databases and data artifacts that ensure the AI is grounded in real-time, accurate information
• Provisions secure, enterprise-ready cloud environments using Infrastructure as Code (IaC) and manages containerized deployments (K8s/Docker) to ensure high availability and low-latency performance at scale
• Implements automated 'Eval' frameworks (e.g., Promptfoo, LangSmith) to quantitatively measure model accuracy, grounding, and hallucination rates, ensuring the agent's reasoning is statistically sound and safe for a high-stakes enterprise rollout

Requirements:

• Experience in designing scalable solutions on GCP
• Experience in building autonomous agentic frameworks
• Experience in high-scale data pipelines
• Experience in cloud infrastructure required for production
• Ability to bridge the gap between raw data and agentic action
• Experience in designing and implementing multi-step reasoning loops
• Experience in autonomous tool-calling frameworks (e.g., ADK, MCP)
• Experience in developing production-grade SQL/Python pipelines
• Experience in maintaining vector databases and data artifacts
• Experience in provisioning secure, enterprise-ready cloud environments using Infrastructure as Code (IaC)
• Experience in managing containerized deployments (K8s/Docker)
• Experience in implementing automated 'Eval' frameworks (e.g., Promptfoo, LangSmith)
• Ability to quantitatively measure model accuracy, grounding, and hallucination rates
• Experience with G3