GEN AI - Architect

We are seeking an experienced GenAI Architect to lead the design, development, and implementation of enterprise-scale Artificial Intelligence solutions leveraging Google Cloud Platform (GCP) and Amazon Web Services (AWS).

The ideal candidate will have expertise in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI frameworks, cloud-native architectures, MLOps, and AI governance.

This role involves collaborating with business stakeholders, data scientists, engineers, and product teams to deliver scalable, secure, and responsible AI solutions.

• Define enterprise GenAI strategy, architecture standards, and technology roadmaps.
• Design and implement scalable Generative AI solutions using foundation models and custom LLMs.
• Architect RAG-based systems integrating structured and unstructured enterprise data.
• Design Agentic AI solutions leveraging multi-agent frameworks and orchestration platforms.
• Evaluate and select appropriate foundation models based on business requirements, cost, security, and performance.
• Develop reference architectures, reusable frameworks, and best practices for AI adoption.
• Architect AI solutions using:
• Big Query
• Cloud Functions
• Dataflow
• GKE
• Design AI pipelines utilizing Vertex AI Model Garden and Vector Search.

• Design AI/ML platforms using:
• Amazon Bedrock
• Sage Maker
• AWS Lambda
• Amazon Open Search
• ECS/EKS
• Step Functions
• API Gateway
• Implement scalable inferencing, fine-tuning, and model deployment strategies.
• Design and optimize:
• Prompt Engineering frameworks
• Knowledge retrieval systems
• AI Agents and Workflow Automation
• Implement model evaluation frameworks for accuracy, relevance, hallucination detection, and performance monitoring.
• Define guardrails for responsible AI and content moderation.

• Implement model versioning, monitoring, observability, and governance.
• Design scalable infrastructure using Infrastructure as Code (Terraform/Cloud Formation).

• Ensure AI solutions comply with enterprise security standards.
• Define data privacy, compliance, and responsible AI policies.
• Implement IAM, encryption, audit logging, and model governance frameworks.
• Provide technical leadership to architects, engineers, and data scientists.
• Engage stakeholders to translate business requirements into AI solutions.
• Mentor development teams on GenAI best practices.
• Conduct architecture reviews and technology assessments.

Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, or related field.

• Generative AI:
  • Prompt Engineering
  • RAG
  • Agentic AI
  • Semantic Search
  • Vector Databases
• Google Cloud:
  • Gemini
  • Big Query
  • Dataflow
  • GKE
  • Pub/Sub
• AWS:
  • Amazon Bedrock
  • Sage Maker
  • Open Search
  • Lambda
  • ECS/EKS
  • Step Functions
• AI Frameworks:
  • Lang Chain
  • Lang Graph
  • CrewAI
  • Auto Gen
  • Semantic Kernel
• Programming
  
  Languages:
  • Python
  • Java
  • Type Script
  • SQL
• Vector Databases:
  • Pinecone
  • Weaviate
  • Chroma
  • FAISS
  • Open Search Vector Engine
• Dev Ops & MLOps:
  • Terraform
  • Docker
  • Git Hub Actions
  • Jenkins
  • MLflow

• Experience designing enterprise AI solutions for Financial Services, Healthcare, Insurance, or Retail domains.
• Knowledge of Responsible AI, AI Safety, and Model Governance.
• Experience integrating GenAI solutions with Salesforce, Service Now, SAP, or enterprise applications.
• Experience with multimodal AI solutions involving text, image, and document processing.

• Google Cloud:
  • Professional Cloud Architect
  • Professional Machine Learning Engineer
• AWS:
  • AWS Certified Solutions Architect – Professional
• Additional:
  • Kubernetes Certifications (CKA/CKAD)

• Strong communication and stakeholder management skills.
• Ability to lead architecture workshops and…