AI Technical Architect

• 10+ years of overall experience including 2-3 years as Architect
• We are looking for an experienced AI Technical Architect who is responsible for designing enterprise AI solutions that align with business objectives while ensuring scalability, security, and efficiency.
• This role translates business needs into AI-driven architectures (across data ingestion, models and operational workflows), ensuring feasibility, cost-effectiveness, and adherence to industry best practices and firmwide standards.
• They provide deep experience in designing viable, feasible, performant AI solutions.

This role is for you if you have:

• 10+ years of overall experience including at least 2 years in Architect role
• Proven experience architecting AI-driven solutions for enterprise customers, collaborating with RD and engineering teams.
• Expertise in AI Architecture, including LLM/SLM (Large Language Models/Small Language Models) deployment, fine-tuning, inference optimization, retrieval-augmented generation (RAG), API- based AI deployment and model orchestration.
• Build and deploy AI solutions primarily on Microsoft Azure (Azure ML, Azure OpenAI).
• Ensure adherence to cloud architecture best practices, scalability, and reliability standards.
• Proficiency in Cloud Security FinOps, including AI landing zones, model refinement and testing, and compliance strategies.
• Experience in Enterprise AI Design, focusing on scalable, secure, and cost-effective AI integration.
• Understanding of data science principles, enabling informed evaluation of machine learning and statistical models.

Must Have skills:

• Must have experience into the complete life cycle- AI/ML experience.
• Should have hands-on experience in the following areas:
• Deep ML/LLM systems engineering
• RAG and Vector Stores
• Agent Workflow Building
• Hands-on delivery focused
• Multi-Agent Systems
• Strong experience building real GenAI solutions, including:
• RAG implementations
• LangChain, LangGraph, Semantic Kernel, AutoGen or Llamaindex
• Prompt engineering
• Vector databases embeddings
• Comfortable leading delivery and making technical decisions
• Can code, prototype, and guide teams by example