Enterprise Architect - Mumbai, Pune
1 day ago
Job description
Role Overview :
We are looking for a world-class AI Enterprise Architect to define architecture, and future-proof our enterprise AI for engineering strategy.
This is a deep technical leadership role for someone who can design the AI backbone of the organization from models to governance to scalable frameworks — and help us operate at global AI maturity standards.
You will shape the AI tech stack, define architectural rigor, build enabling platforms (including context/data lakes), and elevate our thought leadership in the AI ecosystem.
If you are a "builder of builders" who thinks in systems, not features — we want to talk. This is your opportunity to architect the AI foundation of an entire organization.
Why This Role Exists :
We are scaling AI across enterprise clients and need a heavy-hitter architect who can:
- Make sharp decisions on model selection and architecture strategy.
- Establish AI governance, traceability, and quality rigor.
- Build reusable AI frameworks and acceleration environments.
- Enable teams to move faster without compromising depth.
- Position us as a credible AI-first engineering organization.
Key Responsibilities :
Enterprise AI Architecture Leadership & Acceleration & Platform Enablement :
- Own and evolve the enterprise AI reference architecture
- Define model strategy: LLMs vs SLMs, open-source vs proprietary
- Establish evaluation, benchmarking, and model governance standards
- Lead architectural decisions across RAG, fine-tuning, multi-agent systems, orchestration, and guardrails
- Serve as the organization's AI technical authority and conscience
- Guide delivery teams on architecture choices and best practices
- Evaluate and select external AI tools and partnerships
- Shape and influence the long-term AI roadmap
- Design and govern enterprise-grade context lakes
- Define traceability, compliance, and governance frameworks
- Set enterprise standards for data cleaning, fine-tuning quality, prompt management, monitoring, and explainability
- Build AI accelerators and internal AI platforms
- Develop reusable toolkits for industry use cases, automation, and model deployment
- Drive engineering velocity through structured, scalable AI environments
AI Tech Stack :
Own decisions across:
Model selection
- Embedding strategies
- Vector databases
- Data cleaning & preprocessing pipelines
- Fine-tuning environments
MLOps frameworks
Define reusable ML frameworks that accelerate delivery teams
- Create scalable environments for experimentation and product ionization
- Research & guide on AI tech stack for both internal agents & clients
Thought Leadership:
- Publish insights on AI architecture and enterprise adoption
- Representing the organization in industry forums
- Translate market shifts into strategic direction
Ideal Candidate Profile
You are likely:
- AI Enterprise Architect / Principal Scientist / Distinguished Engineer
- Former CTO (architecture-focused)
- Senior AI product architect from a high-quality engineering organization
Must-Have Capabilities :
- 12–18+ years' experience; 3+ years in Applied AI or AI Research
- Deep expertise in LLMs, RAG, fine-tuning, data engineering(optional), MLOps
- Experience Delivering AI Projects at Scale
- Strong communication Skills
Preferred Backgrounds :
- AI product companies
- High-rigor mid-sized engineering firms
- Enterprise AI groups within large IT services organizations
- Strong CTO-led technology organizations
- Entrepreneurial AI founders looking to re-enter a larger platform
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