AI Architect (SDLC Strategy & Automation)

Role : AI Architect (SDLC Strategy & Automation)
• *Key Responsibilities
• Agentic Framework Design & Strategy:**

Design and implement multi-agent systems (LangGraph, CrewAI) to automate complex SDLC tasks. Beyond technical builds, you will
• *lead Discovery Workshops**

to map client pain points to agentic architectures.
• Pre-Sales Technical Leadership:

Act as the primary technical point of contact during the sales cycle, conducting
• *Proof of Value (PoV) engagements**

and demonstrating how AI-driven SDLC acceleration translates into reduced "Time-to-Market."
• Strategic SDLC Consulting:

Conduct
• *Value Stream Mapping**

for clients to identify bottlenecks in CI/CD pipelines. Develop "North Star" roadmaps for AI-driven automation, code reviews, and self-healing infrastructure.
• LLM Orchestration & Governance:

Fine-tune and prompt-engineer LLMs for secure coding tasks, while
• *advising clients on AI Governance**

, data privacy, and the total cost of ownership (TCO) for LLM deployments.
• Seamless Ecosystem Integration:

Architect integrations between AI agents and enterprise toolsets (Jira, GitHub, Slack) to deliver a
• *unified Developer Experience (DevEx)**

that aligns with client business objectives.
• *Technical & Consulting Qualifications
• AI/ML Expertise:**

Deep mastery of Agentic Workflows (planning, memory, tool-use) and RAG. Ability to explain complex LLM architectures to
• *C-suite stakeholders**

in terms of business impact.
• Consulting & Pre-Sales:

3+ years in a
• *customer-facing technical role**

(Solutions Architect, Sales Engineer, or Technical Consultant) with a track record of winning bids and driving adoption.
• Full-Stack Engineering:

5+ years of experience in Python, Node.js, or Go. You can build the demo
• and*

write the production-grade code behind it.
• DevOps & IAC:

Experience with CI/CD (GitHub Actions) and Terraform. You understand how to pitch "Self-Healing" infrastructure as a
• *risk-mitigation strategy**

.
• Strategic Data Systems:

Proficiency with vector databases (Pinecone, Weaviate) to build
• *Enterprise Knowledge Bases**

that serve as the "brain" for client-specific AI agents.
• Communication Mastery:

Ability to pivot from deep-dive technical debugging to
• *executive-level presentations**

without losing the room.