Hiring For Gen AI Lead/Architect

Glauben Technologies; Hyderabad, Pune District, Bengaluru; Hybride; INR 4 000 000 - 7 000 000; Plein temps

Avantages offerts par ce poste

Résumé du poste

Glauben Technologies is seeking an experienced Generative AI Lead / Architect to design and deliver enterprise-grade Gen AI solutions. You will lead architecture for LLMs, RAG, and AI agents, collaborating with business and engineering teams to scale production-ready AI systems.

The role requires deep expertise in Python, cloud platforms (AWS/Azure/GCP), MLOps, governance, and experience driving PoCs to production while mentoring engineers.

Qualifications

• Extensive experience with Generative AI and LLMs in enterprise settings.
• Strong knowledge of RAG, embeddings, vector search, and evaluation.
• Experience building AI agents / multi-agent systems and AI workflows.

Responsabilités

• Define and lead enterprise Gen AI architecture for large-scale apps.
• Design and implement RAG-based solutions, LLM apps, and AI platforms.
• Architect Agentic AI solutions and multi-agent workflows and tools.
• Evaluate OpenAI, Azure OpenAI, Gemini, Claude, Llama models and others.
• Develop prompt engineering, context engineering, guardrails, and governance.

Connaissances

Generative AI

LLMs

RAG

Agentic AI

MLOps

Python

LangChain

LangGraph

Formation

Bachelor's or Master's in CS/AI/Engineering

Outils

LangChain

LangGraph

LlamaIndex

Semantic Kernel

AutoGen

Description du poste

Role & responsibilities

Generative AI Lead / Architect

Experience: 1020 Years
Location: PAN India
Employment Type: Full-Time
Role: Generative AI Lead / Architect

Role Overview

We are looking for an experienced Generative AI Lead / Architect to lead the design, architecture, and implementation of enterprise-grade Generative AI, LLM, and Agentic AI solutions. The ideal candidate will have strong experience in AI/ML architecture, Large Language Models, RAG, AI agents, cloud platforms, MLOps, and enterprise AI transformation.

The candidate will work closely with business stakeholders, engineering teams, data scientists, and technology leaders to build scalable, secure, and production-ready AI solutions.

Key Responsibilities

• Define and lead the Generative AI / LLM architecture for enterprise applications.
• Design and implement RAG-based solutions, LLM applications, and AI-powered platforms.
• Architect Agentic AI solutions, multi-agent workflows, AI agents, and tool/function calling.
• Evaluate and integrate LLMs such as OpenAI, Azure OpenAI, Gemini, Claude, Llama and other foundation models.
• Design prompt engineering, context engineering, model evaluation, guardrails, and responsible AI frameworks.
• Develop scalable AI architectures using Python, APIs, microservices, vector databases, and cloud-native technologies.
• Work with vector databases such as Pinecone, Azure AI Search, FAISS, Weaviate, Milvus or equivalent.
• Design enterprise AI solutions on AWS, Azure, or GCP.
• Establish MLOps / LLMOps practices for model deployment, monitoring, evaluation, and lifecycle management.
• Lead PoCs and convert successful AI prototypes into production-ready solutions.
• Define AI security, governance, privacy, observability, and compliance standards.
• Mentor and guide AI/ML engineers, data scientists, developers, and technical leads.
• Collaborate with business and technology stakeholders to identify and prioritize Gen AI use cases.
• Drive technical innovation and stay current with developments in LLMs, Gen AI, Agentic AI, multimodal AI, and AI platforms.

Required Technical Skills

Generative AI & LLM

• Strong hands-on experience with Generative AI and Large Language Models (LLMs).
• Experience with RAG, embeddings, vector search, prompt engineering, fine-tuning, and model evaluation.
• Strong understanding of Transformer architecture and foundation models.
• Experience building AI agents / Agentic AI / multi-agent systems.
• Knowledge of function calling, tool use, memory, orchestration, and AI workflows.

Programming & Frameworks

• Strong proficiency in Python.
• Experience with frameworks such as:
• LangChain
• LangGraph
• LlamaIndex
• Semantic Kernel
• AutoGen or equivalent
• Strong experience with REST APIs, microservices, FastAPI/Flask and enterprise application integration.

Cloud & Data

• Strong experience in at least one cloud platform:
• AWS
• Microsoft Azure
• Google Cloud Platform
• Experience with Azure OpenAI / AWS Bedrock / Google Vertex AI is preferred.
• Knowledge of vector databases and search technologies.
• Experience with databases such as SQL, NoSQL, MongoDB, PostgreSQL or equivalent.

MLOps / LLMOps

• Experience with CI/CD, Docker, Kubernetes, ML pipelines, model deployment, monitoring, and observability.
• Understanding of LLMOps, model governance, AI evaluation, security, and responsible AI.
• Exposure to tools such as MLflow, Azure ML, AWS SageMaker, Databricks or equivalent.

Leadership & Architecture Skills

• 10-20 years of overall experience in software engineering, AI/ML, data science, or technology architecture.
• Strong experience in solution architecture and enterprise application design.
• Ability to translate business requirements into scalable AI architecture.
• Experience leading technical teams and large-scale AI initiatives.
• Strong stakeholder management and communication skills.
• Ability to present AI architecture and solutions to senior leadership / CXO-level stakeholders.
• Strong problem-solving, analytical, and consulting skills.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
• Experience delivering enterprise Gen AI solutions to production.
• Experience in AI transformation / digital transformation programs.
• Knowledge of multimodal AI, computer vision, speech AI, or NLP.
• Experience with Responsible AI, AI governance, security, and compliance.
• Cloud or AI certifications are an advantage.

Key Competencies

Generative AI | LLM | RAG | Agentic AI | AI Agents | Prompt Engineering | LLMOps | MLOps | Python | LangChain | LangGraph | LlamaIndex | Azure OpenAI | AWS Bedrock | Vertex AI | Vector Database | Embeddings | Fine-Tuning | AI Architecture | Cloud | Kubernetes | Docker | AI Governance | Responsible AI

What You Will Do

• Lead enterprise Gen AI architecture and strategy.
• Build scalable LLM and Agentic AI solutions.
• Guide engineering teams from PoC to production.
• Establish reusable AI frameworks and accelerators.
• Drive adoption of Gen AI across business functions.
• Ensure solutions meet enterprise requirements for security, scalability, performance, cost, and governance.