{
  "generatedAt": "2026-10-03T04:33:28.429Z",
  "profile": {
    "name": "Charneshwar Singh",
    "headline": "GenAI Engineer",
    "location": "Vancouver, BC",
    "email": "charneshwaro@gmail.com",
    "phone": "+1 604-849-3715",
    "intro": "I build enterprise AI platforms, cloud infrastructure, and data-driven applications with secure access, reliable data, and production observability.",
    "resumePath": "/Charneshwar-Singh-Resume.pdf",
    "education": {
      "degree": "Master of Science, Applied Computer Science",
      "institution": "Fairleigh Dickinson University",
      "location": "Vancouver, BC",
      "dates": "MAY 2022 — DEC 2023",
      "specialization": "Database Administration, Distributed Systems, and Large-Scale Data Modeling"
    }
  },
  "experience": [
    {
      "date": "JUN 2026 — PRESENT",
      "location": "Remote",
      "role": "GenAI Developer",
      "company": "Amgen",
      "points": [
        "Develop enterprise GenAI platforms on Microsoft Azure, integrating RAG pipelines, agentic workflows, and model orchestration with enterprise data sources and applications.",
        "Develop reusable platform infrastructure and cloud-native service patterns for AI applications and data workflows, incorporating API contracts, access controls, and observability into solution designs.",
        "Build reference implementations using Python, JavaScript, LangGraph, and MCP to connect enterprise data with retrieval services, Custom GPTs, and LLM-powered applications.",
        "Define data-centric evaluation and governance standards for retrieval relevance, groundedness, and model performance, aligned with security, compliance, and human-in-the-loop requirements."
      ],
      "tags": [
        "Microsoft Azure",
        "Enterprise GenAI platforms",
        "RAG",
        "LangGraph",
        "MCP"
      ]
    },
    {
      "date": "MAR 2025 — MAY 2026",
      "location": "Port Hardy, BC",
      "role": "IT Operations Specialist",
      "company": "KEDC",
      "points": [
        "Developed and maintained AWS ECS/EKS platform infrastructure for containerized AI applications and automated data pipelines, supporting high availability and scalable workload execution.",
        "Built internal dashboards and custom UIs with MCP integrations to connect proprietary ML models with operational data for non-technical stakeholders.",
        "Implemented n8n workflows connecting internal databases and AI services to automate data movement and operational monitoring.",
        "Supported hybrid cloud platforms for compute-intensive workloads and real-time model inference, emphasizing reliable data access and integrity."
      ],
      "tags": [
        "AWS ECS / EKS",
        "n8n",
        "Docker",
        "Kubernetes",
        "Python"
      ]
    },
    {
      "date": "FEB 2024 — FEB 2025",
      "location": "Vancouver, BC · Contract",
      "role": "AI Engineer",
      "company": "Scale AI",
      "points": [
        "Engineered production-grade RAG pipelines and advanced LangGraph agentic workflows for complex, multi-step reasoning tasks.",
        "Used OpenAI Agent Builder and the Responses API to build specialized GPTs and optimize prompts for high-precision enterprise output.",
        "Developed and deployed Custom GPT solutions with OpenAI ChatKit, improving data retrieval accuracy by 21% through fine-tuned semantic search and vector embeddings."
      ],
      "tags": [
        "OpenAI Agent Builder",
        "Responses API",
        "ChatKit",
        "RAG"
      ]
    }
  ],
  "capabilities": [
    {
      "title": "Enterprise GenAI platforms",
      "description": "Azure-based AI platforms that connect enterprise data, retrieval, agents, and model orchestration with production safeguards.",
      "tags": [
        "Azure AI Foundry",
        "Copilot",
        "Agent Builder",
        "Responses API"
      ]
    },
    {
      "title": "Agents, retrieval & automation",
      "description": "RAG and agentic workflows that connect models to tools, applications, and governed enterprise data.",
      "tags": [
        "RAG",
        "LangGraph",
        "MCP",
        "n8n"
      ]
    },
    {
      "title": "Cloud, data & applications",
      "description": "Reusable platform components and data-driven applications built for reliable access, observability, and scale.",
      "tags": [
        "Azure",
        "AWS",
        "Python",
        "SQL",
        "Docker",
        "Kubernetes"
      ]
    }
  ],
  "projects": [
    {
      "title": "Enterprise GenAI platforms",
      "category": "AZURE / ENTERPRISE AI",
      "label": "GOVERNED AI FOUNDATIONS",
      "steps": [
        "Enterprise data",
        "Retrieval",
        "Application"
      ],
      "description": "Reusable Azure platform patterns that connect enterprise data with RAG, agents, model orchestration, and production applications.",
      "tags": [
        "Azure AI Foundry",
        "RAG",
        "Python",
        "MCP"
      ],
      "detail": "The platform approach incorporates clear API contracts, secure access, observability, retrieval evaluation, and human oversight from the start."
    },
    {
      "title": "Agentic retrieval & reasoning",
      "category": "OPENAI / KNOWLEDGE SYSTEMS",
      "label": "CONTEXT-AWARE INTELLIGENCE",
      "steps": [
        "Knowledge",
        "Agent",
        "Answer"
      ],
      "description": "Production-grade RAG and LangGraph workflows for specialized GPTs and complex, multi-step reasoning.",
      "tags": [
        "Agent Builder",
        "Responses API",
        "ChatKit",
        "LangGraph"
      ],
      "detail": "Retrieval quality is improved through semantic search, vector embeddings, prompt optimization, and groundedness evaluation."
    },
    {
      "title": "AI platform automation",
      "category": "CLOUD / APPLICATION INTEGRATION",
      "label": "CONNECTED OPERATIONS",
      "steps": [
        "Operational data",
        "Workflow",
        "Insight"
      ],
      "description": "Cloud infrastructure, custom UIs, and automated workflows that connect operational data with AI services.",
      "tags": [
        "AWS ECS / EKS",
        "MCP",
        "n8n",
        "React"
      ],
      "detail": "The implementation combines reliable platform infrastructure, data movement, real-time inference, and accessible interfaces for non-technical users."
    },
    {
      "title": "Cloud infrastructure for AI workloads",
      "category": "PLATFORM / RELIABILITY",
      "label": "RESILIENT AI RUNTIME",
      "steps": [
        "Containers",
        "Orchestration",
        "Observability"
      ],
      "description": "Scalable Azure and AWS infrastructure for containerized AI services, data pipelines, and real-time inference.",
      "tags": [
        "Azure",
        "AWS ECS / EKS",
        "Docker",
        "Kubernetes",
        "MLOps"
      ],
      "detail": "Hybrid cloud patterns combine container orchestration, dependable data access, observability, and CI/CD to keep AI workloads available and maintainable."
    }
  ],
  "skillGroups": [
    {
      "name": "Generative AI",
      "skills": [
        "Microsoft Copilot",
        "Azure AI Foundry",
        "OpenAI Agent Builder",
        "OpenAI Responses API",
        "OpenAI Codex",
        "OpenAI ChatKit",
        "MCP",
        "RAG Pipelines",
        "LangChain",
        "LangGraph"
      ]
    },
    {
      "name": "ML & Automation",
      "skills": [
        "Machine Learning",
        "PyTorch",
        "TensorFlow",
        "n8n Automation",
        "Custom GPT Development"
      ]
    },
    {
      "name": "Cloud & Platform Infrastructure",
      "skills": [
        "Microsoft Azure",
        "Foundry Tools",
        "AWS",
        "Docker",
        "Kubernetes",
        "CI/CD",
        "MLOps"
      ]
    },
    {
      "name": "Development & Data",
      "skills": [
        "Python",
        "JavaScript",
        "React",
        "Node.js",
        "SQL",
        "Java",
        "Data Pipelines",
        "Semantic Search",
        "Vector Embeddings",
        "API Integration"
      ]
    }
  ],
  "certifications": [
    "IBM Big Data Engineer v2",
    "AWS Academy Cloud Foundations",
    "Cisco CCNA Routing and Switching"
  ]
}