{ "generatedAt": "2026-10-22T08:22:00.605Z", "profile": { "name": "Charneshwar Singh", "headline": "AI Engineer", "location": "Vancouver, BC", "email": "charneshwaro@gmail.com", "phone": "+1 604-849-3715", "intro": "I build enterprise AI applications, intelligent agents, and data pipelines that turn data science into secure, reliable business tools.", "resumePath": "/Charneshwar-Singh-Resume.pdf", "education": { "degree": "Master of Science in Applied Computer Science", "institution": "Fairleigh Dickinson University", "location": "Vancouver, BC", "dates": "MAY 2022 — DEC 2023", "specialization": "Database Administration. Focus: Distributed Systems and Large-Scale Data Modeling." } }, "experience": [ { "date": "JUN 2026 — PRESENT", "location": "Remote", "role": "GenAI Developer", "company": "Amgen", "points": [ "Developed 10+ enterprise AI solutions, with 3 in pilot and the remainder delivered, using LLMs, intelligent agents, and copilots to automate workflows across multiple business functions.", "Developed reusable platform infrastructure across Azure, Databricks, and AWS, and integrated Planisware through configuration, request routing, hosting, and APIs.", "Engineered a 3-stage data pipeline from agent to AWS to dashboard that retrieves and processes data, dynamically populating resource-allocation dashboards and reducing manual preparation.", "Partnered with business and platform stakeholders on requirements and delivery, applying software testing and evaluation checks for output quality, source grounding, and application performance." ], "tags": [ "10+ AI Solutions", "Azure", "Databricks", "AWS", "Planisware" ] }, { "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 scalable deployment and high availability.", "Built internal dashboards and custom interfaces connecting proprietary ML models with operational data for non-technical stakeholders.", "Implemented n8n workflows and API integrations connecting internal databases and AI services to automate data movement, business processes, and operational monitoring.", "Supported hybrid-cloud development and production workloads, addressing deployment reliability, data integrity, and operational issues for compute-intensive applications and real-time inference." ], "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 RAG pipelines and LangGraph agentic workflows for enterprise use cases requiring contextual retrieval and multi-step reasoning.", "Developed LLM-powered solutions using Python and OpenAI APIs, refining prompts and evaluating responses for relevance, accuracy, and consistency.", "Improved data retrieval accuracy by 21% through semantic search and vector embedding optimization, strengthening grounded AI responses." ], "tags": [ "Python", "OpenAI APIs", "RAG", "LangGraph" ] } ], "capabilities": [ { "title": "Enterprise AI applications", "description": "LLM, intelligent-agent, and copilot applications delivered across business functions with secure deployment and production support.", "tags": [ "LLMs", "Intelligent Agents", "Copilots", "OpenAI APIs" ] }, { "title": "Agents, retrieval & automation", "description": "Grounded RAG and agentic workflows that connect models to enterprise data, tools, and automated business processes.", "tags": [ "RAG", "LangGraph", "MCP", "n8n" ] }, { "title": "Cloud, data & system integration", "description": "Reusable multi-cloud platforms and data pipelines integrated with enterprise systems for reliable operational delivery.", "tags": [ "Azure", "Databricks", "AWS", "Planisware", "Salesforce" ] } ], "projects": [ { "title": "Enterprise AI delivery at scale", "category": "LLMS / AGENTS / COPILOTS", "label": "FROM PILOT TO DELIVERY", "steps": [ "Requirements", "Build", "Delivery" ], "description": "More than 10 enterprise AI solutions developed across business functions, with 3 in pilot and the remainder delivered.", "tags": [ "LLMs", "Intelligent Agents", "Copilots", "Software Testing" ], "detail": "Delivery combines stakeholder requirements, secure deployment, source-grounding checks, output-quality evaluation, and application-performance validation." }, { "title": "Multi-cloud AI platform integration", "category": "AZURE / DATABRICKS / AWS", "label": "REUSABLE PLATFORM INFRASTRUCTURE", "steps": [ "Cloud", "Routing", "APIs" ], "description": "Reusable infrastructure spanning three cloud platforms, with Planisware integrated through configuration, request routing, hosting, and APIs.", "tags": [ "Azure", "Databricks", "AWS", "Planisware" ], "detail": "The integration pattern supports secure system access, service principals, deployment automation, and maintainable connections to enterprise applications." }, { "title": "Agent-to-dashboard data pipeline", "category": "AGENT / AWS / DASHBOARD", "label": "3-STAGE DATA DELIVERY", "steps": [ "Agent", "AWS", "Dashboard" ], "description": "A data pipeline that retrieves and processes data, then dynamically populates dashboards for resource-allocation insights.", "tags": [ "Agents", "AWS", "Data Pipelines", "Dashboards" ], "detail": "Automating the flow from agent to AWS to dashboard reduces manual preparation and makes operational insights available to business stakeholders." }, { "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, deployment reliability, and production support for maintainable AI workloads." } ], "skillGroups": [ { "name": "AI & Data Science", "skills": [ "Large Language Models", "RAG", "Intelligent Agents", "Copilots", "LangGraph", "LangChain", "Machine Learning", "MCP", "OpenAI APIs", "PyTorch", "TensorFlow" ] }, { "name": "Cloud Technologies", "skills": [ "Microsoft Azure", "Azure AI Services", "Databricks", "AWS", "Copilot Studio", "Power Platform" ] }, { "name": "Software, Data & MLOps", "skills": [ "Python", "SQL", "JavaScript", "React", "Node.js", "REST APIs", "Data Pipelines", "Vector Embeddings", "Docker", "Kubernetes", "Software Testing", "CI/CD", "Deployment Automation", "Model Monitoring", "Production Support", "Service Principals" ] }, { "name": "Integration, Evaluation & Business", "skills": [ "Salesforce", "CRM/ERP Integration", "Planisware", "n8n", "Workflow Automation", "Access Controls", "Source Grounding", "Output Quality", "Drift and Bias Assessment", "Resource Management", "Sales Pipeline", "Bookings", "Pricing", "Margin Analysis", "Git", "Tableau" ] } ] }