Principal Generative AI Solutions Architect

Idexcel; Bengaluru; On-site; INR 2,500,000 - 3,500,000; Full time

Job summary

A technology firm in Bengaluru seeks a Principal Generative AI Solutions Architect to lead the design and implementation of innovative Generative AI solutions using Large Language Models. This role requires 10+ years of experience in software architecture and significant expertise with LLMs like ChatGPT and Claude. Candidates should possess excellent leadership abilities, a strong understanding of AI compliance, and hands-on experience in building agentic systems. Remote work options may be available.

Qualifications

• 10+ years of experience in software architecture with 2+ years in AI/ML or NLP.
• Hands-on experience with LLMs including prompt engineering.
• Strong experience in designing autonomous agentic systems.

Responsibilities

• Lead design and implementation of GenAI solutions using LLMs.
• Collaborate with stakeholders to identify use cases and scale pilots.
• Define end-to-end architecture and ensure compliance with security principles.

Skills

Software architecture

Generative AI

Large Language Models

Prompt engineering

Containerization

Data privacy

Tools

LangChain

AWS

Azure

Docker

Kubernetes

Job description

Principal Generative AI Solutions Architect

Principal Generative AI Solutions Architect

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Assistant Manager - Talent Acquistion @IdexcelLeadership Hiring|| VP of Software Engineering|| Director-AI/ML|| AWS Solution Architects|| Principle…

Job Summary:

We are seeking an innovative and technically hands-on Principal Generative AI Solutions Architect to lead the design and implementation of Generative AI (GenAI) solutions using Large Language Models (LLMs) such as Claude, ChatGPT, and open-source models (e.g., LLaMA, Mistral). A key aspect of the role will be to integrate agentic capabilities, enabling autonomous and goal-driven AI systems to handle complex enterprise workflows.

Key Responsibilities:

• Architect & implement GenAI solutions using LLMs (hosted and open-source) to solve real business problems across domains such as customer support, marketing, HR, legal, and R&D.
• Collaborate with stakeholders to identify use cases, design proof-of-concepts (PoCs), and scale successful pilots into production-grade systems.
• Define the end-to-end architecture, including data pipelines, prompt engineering, retrieval-augmented generation (RAG), model fine-tuning, and deployment strategies.
• Evaluate and integrate APIs from platforms such as OpenAI (ChatGPT), Anthropic (Claude), Google Vertex AI, Amazon Bedrock, and other model hubs.
• Lead the development of multi-agent systems for complex workflows involving planning, reasoning, and tool use.
• Design agent-based architectures using frameworks like LangGraph, AutoGen, CrewAI, or custom orchestrators where LLMs collaborate with tools, APIs, or other agents to accomplish tasks autonomously.
• Ensure GenAI solutions are aligned with enterprise security, compliance, and responsible AI principles.
• Analyze the current application and its architecture to design an enterprise platform for GEN AI based integrated or shared services.
• Understand various compliance criteria (SOC 1, SOC 2, PCI-DSS, ISO-27001) to design/architect GEN AI based solutions.
• Lead development teams in implementing architectural blueprints and mentor engineers in GenAI best practices.
• Stay current on the GenAI landscape and continuously assess emerging tools, frameworks, model capabilities and planning agents(e.g., LangChain, LlamaIndex, vector databases).
• Support hybrid LLM deployments using cloud-native and on-premise infrastructure (e.g., SageMaker, Azure ML, Databricks, Kubernetes).

Required Skills & Experience:

• 10+ years of experience in software architecture with at least 2+ years in designing and deploying AI/ML or NLP solutions.
• Hands-on experience with LLMs (e.g., ChatGPT, Claude, LLaMA, GPT-4, Gemini), including prompt engineering, fine-tuning, or RAG architectures.
• Strong experience in designing and implementing agentic systems where LLMs operate autonomously or in structured workflows (e.g., using LangChain Agents, LangGraph, AutoGen, CrewAI).
• Proficient with modern AI development frameworks: LangChain, Transformers, Hugging Face, Vector DBs (e.g., Pinecone, FAISS, Weaviate).
• Cloud platform experience: AWS, Azure, or GCP; familiarity with Amazon Bedrock, Azure OpenAI, or Google Generative AI Studio.
• Experience in containerization, orchestration (e.g., Docker, Kubernetes) and MLOps practices.
• Strong understanding of data privacy, model governance, and ethical AI considerations in enterprise settings.

Excellent communication and leadership skills with a track record of guiding cross-functional teams

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  IT Services and IT Consulting and Banking

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