Vacancy description
GenAI Architect in Bangalore, भारत
ALTRAIZE
- Full-timeStandard weekly hours
Rs 18 - 24 lakhs p.a.
Bangalore, भारत
Generative AI Architect
Experience: 10+ Years
Job Type: Full-Time
Domain: Generative AI / Artificial Intelligence
Role Overview
We are looking for an experienced Generative AI Architect to lead the design and architecture of enterprise-grade GenAI solutions. The ideal candidate will have strong expertise in LLMs, RAG, AI agents, multi-agent systems, prompt engineering, vector databases, LLM orchestration, and enterprise system integration .
The role will be responsible for defining end-to-end GenAI architecture, establishing AI design standards, ensuring responsible and secure AI adoption, and mentoring engineering teams in building scalable AI-first solutions.
Key Responsibilities
Define and own the end-to-end GenAI architecture , including LLM orchestration, agent frameworks, and enterprise integration layers.
Design scalable and modular GenAI solutions using LLMs, embeddings, vector databases, and retrieval mechanisms .
Architect agent-based and multi-agent systems supporting autonomous reasoning, planning, and task execution.
Establish reusable architecture patterns for RAG, conversational AI, document intelligence, and context-aware decision systems .
Lead integration of GenAI solutions with enterprise applications using APIs, microservices, event-driven architectures, and secure data pipelines .
Define prompt engineering strategies, prompt lifecycle management, and context orchestration mechanisms.
Design and implement Responsible AI frameworks covering governance, explainability, auditability, security, and compliance.
Design human-in-the-loop architectures , including confidence thresholds, feedback loops, checkpoints, and fallback mechanisms.
Establish monitoring and observability frameworks covering model performance, hallucination detection, accuracy, drift, and cost optimization .
Work closely with business and product stakeholders to identify high-value GenAI use cases and develop scalable transformation roadmaps.
Drive standardization of GenAI architecture best practices, reusable components, and enterprise AI governance policies.
Mentor and guide engineering teams on GenAI architecture, prompt engineering, LLMOps, and AI-first solution design .
Essential Skills
Strong expertise in Generative AI and Large Language Models (LLMs) .
Extensive experience designing enterprise GenAI architectures .
Hands-on experience with RAG and retrieval-based AI systems .
Strong knowledge of AI agents and multi-agent architectures .
Experience with LLM orchestration and agent frameworks .
Strong understanding of embeddings, vector databases, semantic search, and retrieval mechanisms .
Expertise in prompt engineering and context engineering/orchestration .
Experience integrating AI solutions through REST APIs, microservices, and event-driven architectures .
Knowledge of LLMOps, AI observability, model evaluation, monitoring, and optimization .
Strong understanding of Responsible AI, AI governance, security, compliance, and auditability .
Experience designing scalable, secure, and production-ready AI solutions.
Strong stakeholder management, communication, and technical leadership skills.
Preferred / Desirable Skills
Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform .
Experience with frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar agent frameworks .
Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, or Azure AI Search .
Knowledge of Python and modern AI/ML frameworks .
Experience with CI/CD, DevOps, MLOps, and LLMOps practices.
Experience working with enterprise security and data privacy requirements.
Experience leading enterprise-wide AI transformation initiatives.
Experience Required
10+ years of overall technology experience , with significant hands-on experience in AI/ML and Generative AI architecture .
Candidates should demonstrate experience delivering production-grade GenAI solutions , rather than only POCs or experimental projects.