Tejinder Pal Singh

About Tejinder Pal Singh

I am a Data Scientist and AI Engineer with hands‑on experience designing, developing, and deploying production‑grade AI applications that solve real business problems. My work sits at the intersection of machine learning, agentic AI systems, and responsible AI practices, with a strong focus on building scalable, trustworthy, and impactful AI solutions.I specialize in end‑to‑end AI product development—from problem framing and data strategy to model development, orchestration, deployment, and monitoring. Over the course of my work, I have built and operationalized LLM‑powered systems, intelligent automation, and agentic AI workflows capable of reasoning, planning, tool usage, and autonomous decision‑making. What I Work OnDesigning and implementing Agentic AI systems (multi‑step reasoning, tool‑calling, orchestration, memory, guardrails)Developing ML and GenAI solutions using classical ML, deep learning, and large language modelsBuilding AI applications that integrate models with APIs, data pipelines, and enterprise systemsApplying Responsible AI principles—fairness, explainability, robustness, privacy, and governance—across the AI lifecycleEvaluating AI systems for performance, bias, hallucinations, and risk before and after deployment Technical Focus AreasMachine Learning & Deep Learning: predictive modeling, classification, NLP, feature engineeringGenerative AI & LLMs: prompt engineering, RAG pipelines, evaluation, fine‑tuning, inference optimizationAgentic AI Architectures: autonomous agents, task planning, tool integration, multi‑agent systemsMLOps / AI Engineering: deployment, monitoring, reproducibility, CI/CD for ML, model governanceResponsible AI: ethical AI design, transparency, security, compliance, and risk mitigation How I Think About AII believe AI should be:Purpose‑driven, not experimental for experimentation’s sake.My approach combines strong technical rigor with business alignment, ensuring that AI systems deliver value while remaining safe, compliant, and explainable.I enjoy collaborating across data science, engineering, product, and risk teams to translate complex AI capabilities into reliable, real‑world solutions. I’m particularly interested in solving problems where agentic AI, automation, and responsible governance come together at scale. Core Interests: Agentic AI · Applied ML · Enterprise GenAI · Responsible AI · AI EngineeringI thrive in collaborative environments, partnering with executive leadership and cross-functional teams to drive data-informed decisions.

Experience

1. Sr Data Scientist

   Infosys

   Sep 2025 — Present · Houston, TX, US

   Designing and building AI business applications/solutions adhering to responsible AI principles.

Education

• Texas A&M University

  Masters, Industrial Engineering

• Birla Institute of Technology and Science, Pilani

  BE, Mechanical Engineering

Skills

• Supply Chain Optimization
• Algorithms
• Network Optimization
• C#
• Unix
• Optimizations
• C++
• Mathematical Modeling
• Software Development
• Distributed Systems
• Matlab
• C
• Optimization
• Supply Chain Consulting
• Operations Research
• Machine Learning
• Java
• Sql
• Core Java
• Logistics