Description :

Job Title : Technical Architect - Gen-AI Adoption (LLM-focused)

Location : Bangalore

Job Type : Full-Time

Job Summary :

We are seeking an innovative and technically hands-on Technical 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.