Technical Architect- AI

We are seeking a highly experienced AI Architect to lead the design, architecture, and implementation of enterprise-scale Generative AI solutions on Google Cloud Platform (GCP). The ideal candidate will possess deep expertise in Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), Agentic AI, Vector Databases, and the Google AI ecosystem including Vertex AI and Gemini. The role requires a blend of strategic architecture leadership and hands‑on technical expertise to deliver scalable, secure, and production‑ready AI platforms.

• 10+ years of overall experience in software engineering, cloud architecture, or data platforms.
• 5+ years of experience designing and implementing AI/ML solutions.
• 3+ years of experience delivering Generative AI and LLM-based applications in enterprise environments.
• Proven experience implementing RAG architectures, conversational AI platforms, and AI-powered knowledge management solutions.

• Bachelor’s degree in Computer Science, Data Science.
• Generative AI & LLMs:
  Gemini, Vertex AI, OpenAI, Llama, Foundation Models, Prompt Engineering, Conversational AI, Agentic AI / Multi-Agent Architectures, AI Model Evaluation and Monitoring
• RAG & Knowledge Systems:
  Retrieval-Augmented Generation (RAG), GraphRAG, Knowledge Graphs, Semantic Search, Embeddings and Vector Search, Document Intelligence and Enterprise Search
• Google Cloud Platform (GCP):
  Vertex AI, Big Query, Cloud Storage, Cloud Run, Cloud Functions, Cloud SQL, Pub/Sub, Dataflow, GKE (Google Kubernetes Engine)
• Vector Databases & Search:
  Vertex AI Vector Search, Pinecone, ChromaDB, FAISS, pg Vector
• AI Frameworks & Development:
  Lang Chain, Lang Graph, Llama Index, FastAPI, REST APIs, Python, SQL
• MLOps & Dev Ops:
  Vertex AI Pipelines, MLflow, CI/CD for AI Applications, Model Governance & Monitoring, Infrastructure as Code (Terraform)
• Security & Governance:
  Responsible AI, AI Risk Management, Data Governance, Security Architecture, Compliance & Audit Controls

• Google Cloud Professional Cloud Architect
• Google Cloud Professional Machine Learning Engineer
• Google Generative AI Certifications
• Databricks Generative AI Certifications (preferred)

• Define enterprise AI architecture standards, patterns, and best practices.
• Design end-to-end Generative AI, RAG, and Agentic AI solutions.
• Develop AI roadmaps aligned with business objectives and technology strategy.

• Architect large-scale RAG and GraphRAG solutions.
• Design document ingestion, chunking, indexing, retrieval, re-ranking, and grounding strategies.
• Optimize AI solution accuracy, scalability, latency, and cost efficiency.
• Build enterprise knowledge platforms leveraging structured and unstructured data sources.

• Lead the design and implementation of AI assistants, chatbots, copilots, and autonomous agents.
• Enable integration of LLMs with enterprise systems, APIs, and workflows.
• Establish frameworks for prompt engineering, model evaluation, and continuous improvement.

• Architect scalable AI platforms using GCP services.
• Drive cloud-native AI application development and deployment.
• Define best practices for performance optimization, reliability, observability, and resilience.

• Implement AI governance frameworks, security controls, and monitoring capabilities.
• Ensure compliance with enterprise policies, data privacy, and regulatory requirements.
• Establish standards for model transparency, explainability, and risk management.

• Partner with business stakeholders, product owners, data engineers, and AI teams.
• Conduc…