Job Requirements

Own the technical direction of AI and agent capabilities across the Keystone platform. The Technical AI Lead will connect AI architecture with the underlying data and event platform, establish engineering standards, guide major technical decisions, and help the team build scalable, reliable, and production-ready AI capabilities.Set AI architecture and technical direction, establish agent/platform standards, and lead AI engineering delivery

Define the technical architecture and engineering standards for AI applications, agents, and agentic workflows.

Establish patterns for agent orchestration, tool calling, workflow execution, state management, and service integration.

Guide adoption and effective use of Python and Embabel for production agent development.

Define approaches for LLM integration, model selection, evaluation, grounding, retrieval, and AI observability.

Design the integration between AI agents and the underlying data, event, API, and platform services.

Establish standards for event-driven systems, data contracts, data quality, observability, security, and reliability.

Guide the evolution of existing systems toward scalable event-driven, data, and AI platform architectures.

Make architecture decisions across data storage, real-time serving,



AI services, integrations, and platform components.

Define approaches for AI quality, evaluation, experimentation, controlled releases, and production monitoring.

Establish technical objectives around AI quality, latency, reliability, scalability, recovery, and cost.

Lead design reviews and architecture discussions.

Mentor Senior AI Developers and establish engineering best practices for AI and platform development.

Identify and manage technical risks, dependencies, and architectural trade-offs.

Work closely with Product, Data Science, Architecture, and Engineering leadership to translate business requirements into technical solutions.

Support modernization and migration planning while minimizing operational risk.

7+ years of experience in software engineering, AI engineering, data platforms, distributed systems, or related areas.

Robust experience owning and delivering production systems.

Deep understanding of AI application architecture, LLM integrations, agentic systems, and production AI engineering.

Hands-on experience with Python and agent development frameworks; Embabel experience is highly relevant.

Work Experience

7-10Years

📌 Architect (Hyderabad)
🏢 Virtusa
📍 Hyderabad