IND_Technical Architect

Description

Role Descriptions

"1. Define and own the end-to-end GenAI architecture| including Large Language Model (LLM) orchestration| agent frameworks| and enterprise system integration layers.

• Design scalable and modular GenAI solutions using LLMs| embeddings| vector databases| and retrieval mechanisms to support complex enterprise use cases.
• Architect agent-based and multi-agent systems that enable autonomous reasoning| planning| and task execution across workflows.
• Establish design patterns for GenAI solutions including Retrieval-Augmented Generation (RAG)| conversational AI| document intelligence| and context-aware decision systems.
• Lead integration of GenAI solutions with enterprise applications using APIs| microservices| event-driven systems| and secure data pipelines.
• Define prompt engineering strategies| prompt lifecycle management| and context orchestration mechanisms for consistent and high-quality model outputs.
• Implement Responsible AI frameworks including governance| explainability| auditability| security| and compliance for enterprise AI deployments.
• Design human-in-the-loop architectures| defining checkpoints| confidence thresholds| feedback loops| and fallback mechanisms.
• Establish monitoring and observability frameworks covering model performance| hallucination detection| accuracy| drift| and cost optimisation.
• Collaborate with business and product stakeholders to identify high-value GenAI use cases and define scalable transformation roadmaps.
• Drive standardisation of GenAI architecture best practices| reusable components| and enterprise AI governance policies.
• Mentor and guide engineering teams on GenAI architecture| prompt engineering| LLMOps practices| and AI-first solution design principles."

Essential Skills

"1. Define and own the end-to-end GenAI architecture| including Large Language Model (LLM) orchestration| agent frameworks| and enterprise system integration layers.

• Design scalable and modular GenAI solutions using LLMs| embeddings| vector databases| and retrieval mechanisms to support complex enterprise use cases.
• Architect agent-based and multi-agent systems that enable autonomous reasoning| planning| and task execution across workflows.
• Establish design patterns for GenAI solutions including Retrieval-Augmented Generation (RAG)| conversational AI| document intelligence| and context-aware decision systems.
• Lead integration of GenAI solutions with enterprise applications using APIs| microservices| event-driven systems| and secure data pipelines.
• Define prompt engineering strategies| prompt lifecycle management| and context orchestration mechanisms for consistent and high-quality model outputs.
• Implement Responsible AI frameworks including governance| explainability| auditability| security| and compliance for enterprise AI deployments.
• Design human-in-the-loop architectures| defining checkpoints| confidence thresholds| feedback loops| and fallback mechanisms.
• Establish monitoring and observability frameworks covering model performance| hallucination detection| accuracy| drift| and cost optimisation.
• Collaborate with business and product stakeholders to identify high-value GenAI use cases and define scalable transformation roadmaps.
• Drive standardisation of GenAI architecture best practices| reusable components| and enterprise AI governance policies.
• Mentor and guide engineering teams on GenAI architecture| prompt engineering| LLMOps practices| and AI-first solution design principles."

Skills

Generative AI

Experience Required

10 & Above

Location

Bangalore