Architect

AI Lead Architect / AI Program Lead / AI Champion

Job Summary: We are seeking an AI Lead Architect / Program Lead / AI Champion to drive the setup, execution, and optimization of AI-native software engineering (Agentic SDLC) across enterprise engagements. This hands-on leadership role combines software architecture with agentic delivery expertise to guide teams from traditional to AI-native SDLC.

Responsibilities

• Program Planning & Operating Model: Assess AI readiness across SDLC; define Agentic SDLC roadmaps, autonomy levels, quality thresholds, and human-in-the-loop controls.
• Harness Architecture & Setup: Lead design, configuration, and setup of the AI engineering harness for client programs.
• Agent & Context Engineering: Continuously optimize agent capabilities, context engineering, orchestration, and tools.
• Software Engineering Execution: Transition traditional SDLC into seamless human + agent collaborative workflows.
• Troubleshooting & Optimization: Diagnose root causes of poor agent outputs and tune intent, context, skills, or orchestration.
• Quality, Speed & Evaluation: Establish continuous feedback loops (Observe → Diagnose → Tune → Measure) and evaluation frameworks.
• Client Collaboration & Governance: Advise CIO/CTO offices, ensure security/responsible AI compliance, and upskill teams.
  
  

Mandatory Skills

• Strong background in software & AI engineering, enterprise architecture, Agile, CI/CD, and DevOps.
• Hands-on experience with AI harnesses, coding agents, context engineering, RAG, MCP, and AI tools (e.g., Claude, Kiro).
• Ability to diagnose/tune AI systems beyond black-box usage.
• Strong consulting, stakeholder management, and cross-functional leadership skills.
  
  

Preferred Skills

• Experience with specialized agents, evaluation frameworks, and AI Centers of Excellence (CoEs).
• Experience in cloud platforms, app modernization, and regulated industries (banking, telecom).
  
  

Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or a related field.