Senior Technical Architect

Job Summary

The AI Architect will lead the design and execution of an** AI‑led SDLC** to deliver** AI Agents and Multi‑Service (Agentic) solutions** for a Retail enterprise. The role ensures scalable, secure, and governed AI solutions that accelerate value realization across customer experience, supply chain, and store operations.

Key Responsibilities

• AI‑Led SDLC: Define and operationalize an AI‑first SDLC from use‑case discovery to deployment, monitoring, and continuous optimization (DevOps + MLOps/LLMOps).

• Agentic Architecture: Design and govern** single and multi‑agent architectures** (planner/executor, tool‑using, memory‑enabled agents) integrated with enterprise systems.

• Retail Use Cases: Enable high‑value Retail AI scenarios including personalization, intelligent customer service, demand forecasting, inventory optimization, pricing, and fraud/loss prevention.

• Platform & Integration: Architect end‑to‑end solutions across LLM platforms, vector databases/RAG, data platforms, APIs, and microservices; integrate with ERP, OMS, WMS, CRM, POS.

• Governance & Security: Establish** Responsible AI**, security, privacy, observability, and audit controls; define standards for model/prompt lifecycle, agent behavior, and risk management.

• Delivery Leadership: Act as technical authority; mentor AI/ML and engineering teams; support client workshops, solution walkthroughs, and executive reviews.

Skill Requirements

• Experience: 10+ years in solution/enterprise architecture; 5+ years delivering AI/ML solutions at scale.

• Technical: Strong in AI/ML, LLMs, RAG, agent orchestration, APIs, microservices; hands‑on with cloud platforms (AWS/Azure/GCP) and MLOps/LLMOps practices.

• Enterprise & Retail: Proven ability to align AI outcomes to business KPIs in large Retail environments.

• Delivery: Experience operating in regulated, security‑conscious enterprise settings.

Other Requirements

Nice to Have

• Prior delivery of autonomous/semi‑autonomous agents

• ERP/Commerce/Supply Chain platform integrations

• Cloud/AI architecture certifications

Success Measures

• Time‑to‑value for AI use cases

• Stability, governance compliance, and reusability of agent frameworks

• Measurable business impact (CX uplift, cost reduction, revenue growth)