Generative AI Architect

Role Summary :

We are seeking an experienced Generative AI Architect with 15 to 19 years of overall experience and deep expertise in Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI technologies.

The ideal candidate will be responsible for defining AI strategy, architecting enterprise-scale AI solutions, leading AI transformation initiatives, and driving the adoption of cutting-edge Generative AI technologies across the organization.

This role requires strong technical leadership, hands-on expertise in LLMs, RAG architectures, Agentic AI frameworks, cloud AI platforms, and enterprise AI solution design.

Key Responsibilities :

- Define and drive the organization's Generative AI architecture, strategy, and implementation roadmap.

- Design scalable, secure, and production-ready AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multimodal AI technologies.

- Lead architecture and solution design discussions for enterprise AI initiatives and business transformation programs.

- Design and implement AI-powered applications, copilots, virtual assistants, intelligent search platforms, and knowledge management solutions.

- Architect end-to-end RAG frameworks, vector search solutions, and enterprise knowledge retrieval systems.

- Evaluate, select, and integrate foundation models, open-source LLMs, and commercial AI services based on business requirements.

- Lead model fine-tuning, optimization, evaluation, and deployment strategies for enterprise AI applications.

- Design Agentic AI solutions involving autonomous workflows, multi-agent collaboration, and intelligent orchestration.

- Establish AI governance, security, scalability, observability, and responsible AI practices.

- Provide technical leadership and mentorship to AI engineers, data scientists, architects, and development teams.

- Collaborate with business stakeholders to identify AI use cases and translate business objectives into scalable technical solutions.

- Drive innovation through continuous evaluation of emerging AI technologies, frameworks, and industry best practices.

- Support pre-sales, solution consulting, architecture reviews, and executive stakeholder engagements.

Required Skills & Experience :

- 15 to 19 years of overall experience in Software Engineering, Data Science, Artificial Intelligence, Machine Learning, or Enterprise Architecture.

- Minimum 2+ years of hands-on experience in Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, and Generative AI projects.

- Strong programming expertise in Python and experience building production-grade AI applications.

- Hands-on experience in model training, fine-tuning, evaluation, and deployment.

- Strong understanding of Machine Learning, Deep Learning, Neural Networks, and Transformer architectures.

- Experience designing enterprise-scale AI platforms and AI-enabled business solutions.

- Strong architecture and solution design capabilities with experience leading complex technology transformation initiatives.

- Excellent communication, consulting, stakeholder management, and leadership skills.

Required Generative AI Expertise :

- Strong hands-on experience with Large Language Models (LLMs) and enterprise Generative AI implementations.

- Deep understanding of Retrieval-Augmented Generation (RAG) architectures and enterprise knowledge retrieval systems.

- Experience designing and implementing multimodal AI solutions involving text, image, audio, and document understanding.

- Strong knowledge of prompt engineering, context engineering, prompt optimization, and response evaluation techniques.

- Experience working with open-source LLMs from Hugging Face and commercial foundation models.

- Hands-on experience with LangChain and LangGraph frameworks.

- Strong understanding of vector databases, embedding models, semantic search, indexing strategies, and retrieval optimization.

- Experience designing AI communication flows for both direct LLM and RAG-based architectures.

- Knowledge of model orchestration, AI workflow automation, and enterprise AI integration patterns.

(ref:hirist.tech)