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    Home/Jobs/AI Solution Architect

    AI Solution Architect

    Wadhwani Foundation

    Bengaluru
    6-10 years
    45 days ago
    ₹23–44 LPA
    Full-time
    Remote

    Skills Required

    LLM
    LangChain
    RAG
    Vector Database
    Prompt Engineering
    LLMOps
    LangGraph
    AutoGen
    CrewAI
    System Design
    Backend systems

    Description

    We are building the next generation of AI-native products and looking for an AI Solution Architect to be a core part of that foundation.

    Company: Wadhwani Foundation

    Role: AI Solution Architect

    Location: India Remote / Hybrid

    Experience:

    • 6–10 years of total experience in backend or distributed systems engineering
    • 3–4 years of hands-on, production-focused experience in Generative AI or LLM-based systems

    Role Focus: • Design and own scalable architectures for agentic AI systems and LLM-powered platforms • Architect multi-agent systems • Define system design for RAG pipelines, memory systems, context management, prompt orchestration, and stateful workflows • Build and optimize AI pipelines for latency, cost, scalability, and reliability • Design integration patterns with enterprise systems • Establish observability, tracing, and evaluation frameworks for AI systems • Define guardrails, safety layers, and failure handling mechanisms • Drive best practices in prompt engineering, system design, and AI architecture • Work closely with engineering, product, and research teams

    Nice to have:

    • Experience building AI platforms, internal tooling, or developer-facing SDKs
    • Understanding of AI governance, security, and compliance
    • Exposure to open-source LLM ecosystems (Llama, Mistral, etc.)

    More skills:

    LLM architectures, Generative AI, Agentic orchestration frameworks (LangChain, LangGraph, AutoGen, CrewAI), Embedding models, Context design, Scalability, Performance optimization, Fault tolerance, Cost optimization, Async workflows, Event-driven architectures, Cloud platforms (AWS, Azure, GCP), MLOps / LLMOps workflows, Observability and tracing tools

    Other:

    • This is not a consulting or advisory role. You will own architecture end-to-end.
    • The ability to translate ambiguous business problems into concrete, scalable AI architectures
    • Comfort operating as a senior IC in a fast-moving, AI-native environment

    Prepare for this role

    Recommended resources to build the skills for this position. Sponsored.

    Generative AI with Large Language Models

    Coursera

    Comprehensive LLM course covering transformer architecture, fine-tuning, RLHF, and deployment.

    Functions, Tools and Agents with LangChain

    Coursera

    Advanced LangChain covering function calling, tool use, and conversational agents.

    Large Language Models: Application through Production

    edX

    Production-focused LLM course covering deployment, monitoring, and scaling.

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