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Hi, I'm Pranav Chand. I'm a senior AI/ML engineer who loves turning complex problems into reliable AI platforms that people can actually use. Over the last five years, I've designed and shipped production-grade Generative AI and ML systems for enterprise-scale applications. I specialize in LLM application architecture, prompt engineering at scale, multi-provider orchestration, and safety guardrails, while keeping a strong focus on observability, reliability, and cost optimization. I enjoy mentoring teams to raise production-readiness standards and translating business needs into practical, scalable solutions on AWS and GCP.…Hi, I'm Pranav Chand. I'm a senior AI/ML engineer who loves turning complex problems into reliable AI platforms that people can actually use. Over the last five years, I've designed and shipped production-grade Generative AI and ML systems for enterprise-scale applications. I specialize in LLM application architecture, prompt engineering at scale, multi-provider orchestration, and safety guardrails, while keeping a strong focus on observability, reliability, and cost optimization. I enjoy mentoring teams to raise production-readiness standards and translating business needs into practical, scalable solutions on AWS and GCP.

Pranav Chand

AI Engineer, Data Scientist, Full Stack Developer, +2

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Hi, I'm Pranav Chand. I'm a senior AI/ML engineer who loves turning complex problems into reliable AI platforms that people can actually use. Over the last five years, I've designed and shipped production-grade Generative AI and ML systems for enterprise-scale applications. I specialize in LLM application architecture, prompt engineering at scale, multi-provider orchestration, and safety guardrails, while keeping a strong focus on observability, reliability, and cost optimization. I enjoy mentoring teams to raise production-readiness standards and translating business needs into practical, scalable solutions on AWS and GCP.…Hi, I'm Pranav Chand. I'm a senior AI/ML engineer who loves turning complex problems into reliable AI platforms that people can actually use. Over the last five years, I've designed and shipped production-grade Generative AI and ML systems for enterprise-scale applications. I specialize in LLM application architecture, prompt engineering at scale, multi-provider orchestration, and safety guardrails, while keeping a strong focus on observability, reliability, and cost optimization. I enjoy mentoring teams to raise production-readiness standards and translating business needs into practical, scalable solutions on AWS and GCP.

Available to hire

Hi, I’m Pranav Chand. I’m a senior AI/ML engineer who loves turning complex problems into reliable AI platforms that people can actually use. Over the last five years, I’ve designed and shipped production-grade Generative AI and ML systems for enterprise-scale applications.

I specialize in LLM application architecture, prompt engineering at scale, multi-provider orchestration, and safety guardrails, while keeping a strong focus on observability, reliability, and cost optimization. I enjoy mentoring teams to raise production-readiness standards and translating business needs into practical, scalable solutions on AWS and GCP.

Skills

Experience Level

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Work Experience

AI/ML Engineer at ServiceNow

November 1, 2020 - Present

Architected and led development of enterprise-scale Generative AI platforms using GPT and Azure OpenAI, supporting multiple internal products with strict reliability, latency, and security requirements. Designed LLM application architecture with advanced model routing, provider abstraction, fallback strategies, retries, timeout controls, and circuit breakers to ensure high availability across providers. Built prompt engineering frameworks at scale, including versioned prompt templates, system prompts, tool calling, structured outputs, and automated evaluation pipelines. Implemented LLM safety and governance layers, including moderation workflows, prompt injection mitigation, policy enforcement, and hallucination reduction techniques. Developed usage analytics and cost-optimization pipelines, applying token budgeting, adaptive model selection, response truncation, and caching strategies, reducing LLM operational costs by 30%. Led design of event-driven AI workflows using AWS Step Functi

ML Engineer at Infinite Infolab

August 1, 2019 - June 1, 2023

Built and productionized transformer-based ML inference systems and hybrid rule-based + LLM architectures for personalization and intelligent automation use cases. Designed and deployed ML model serving pipelines, including batching, latency tuning, and inference optimization for real-time and batch workloads. Developed personalization and ranking systems with well-defined experiments, metrics, and error analysis workflows. Implemented ML monitoring, drift detection, and data quality validation, improving model stability and long-term performance. Built secure backend services using Python Flask, Celery, and asynchronous processing for scalable ML workflows. Designed multi-tenant architectures with strong isolation, RBAC, and JWT-based authentication. Automated CI/CD pipelines using Docker, Terraform, AWS SAM, and GitHub Actions, significantly improving deployment reliability and release velocity.