Roles and Responsibility
- Own the architecture and make it easy to build on.
- Develop and evolve our enterprise reference architecture for generative and agentic AI across models, retrieval, orchestration, reasoning, and governance.
- Build and demonstrate hands-on prototypes, stand up working proofs, and continuously learn as the field evolves.
- Lead solutioning from proof-of-concept to production, including scoping experiments and proving them.
- Set technical standards and own build-vs-buy decisions, running architecture reviews and mentoring engineers.
- Translate technical trade-offs clearly for leadership, clients, and engineering.

Job Requirements
- Production-proven, end-to-end experience in software/AI engineering.
- Hands-on depth across the up-to-date agentic stack, including orchestration frameworks, protocols, RAG and GraphRAG, vector and graph databases, model serving, and LLMOps.
- Practical evaluation and guardrails experience, making model quality measurable and defensible.




- Command of the full span from classical ML/DL to generative to agentic, with the ability to choose the simplest approach that works.
- Cloud and data-platform depth (AWS / Azure / Databricks) and familiarity with semantic layers and lakehouse architectures.
- Excellent communication and stakeholder management skills, including senior leadership and mentoring.
- Experience in regulated industries such as life sciences, pharma, or healthcare, and compliance-aware AI architecture (GxP, GAMP 5, 21 CFR Part 11, ALCOA+ data integrity, EU AI Act / HIPAA awareness).
- Knowledge of graphs, semantic layers, and ontologies as first-class design elements.
- Multi-tenant SaaS or customer-deployed system design experience.
- Public contributions (talks, writing, or open source) on generative/agentic AI architecture.

📌 AI Architect (Hyderabad)
🏢 Aparajita Consultancy services
📍 Hyderabad