Virat Srivastava

AI/ML Engineer | GPU Computing Specialist | FinTech Enthusiast

I am a specialized AI/ML Engineer with a strong focus on high-performance computing, GPU acceleration, and scalable machine learning pipelines. My expertise spans C++ development, Python, AWS, and advanced SQL, enabling me to design and optimize systems that deliver efficiency, reliability, and reproducibility at scale.

As an Agentic AI Engineer at FirstEigen, I architected frameworks that integrated multi-step decision-making workflows, retrieval-augmented generation pipelines, and transformer benchmarking. My work bridged academic research (MTech in AI/ML at VIT) with industry applications, particularly at the intersection of technology and finance, where I aimed to build impactful solutions that enhanced decision-making, risk modeling, and operational efficiency in financial systems.

My professional journey includes valuable experience at ISRO (NRSC), where I contributed to projects involving remote sensing, spatial data modeling, and sustainable development applications. These experiences strengthened my ability to combine scientific rigor with practical deployment, ensuring that AI systems are not only innovative but also reliable in mission-critical environments.

Beyond my core engineering role, I am deeply invested in the future of agentic AI systems—orchestrating custom tools, APIs, and database queries to refine autonomous workflows. I believe that the next wave of AI innovation lies in context-aware, decision-making agents that can seamlessly integrate into complex ecosystems.

Outside of work, I actively contribute to open-source projects, mentor peers in the AI/ML community, and stay updated with the latest advancements in Generative AI, deep learning, and financial technology applications. I thrive on collaboration and knowledge sharing, believing that innovation accelerates when diverse minds come together.

🔹 Core Strengths

• High-Performance Computing & GPU Acceleration – Optimizing ML workloads for speed and scalability.
• Machine Learning Pipelines – Designing reproducible, modular workflows for production-ready AI systems.
• C++ & Python Development – Building robust, efficient solutions across domains.
• Agentic AI & GenAI – Exploring autonomous systems, RAG pipelines, and transformer benchmarking.
• Finance + AI – Applying ML algorithms to enhance decision-making in financial systems.
• Cloud & Infrastructure – AWS-certified, with experience in secure authentication, caching, and connection pooling.

🔹 Personal Philosophy

I see AI not just as a tool, but as a catalyst for systemic transformation. Whether in finance, sustainability, or everyday workflows, my goal is to build solutions that are scalable, transparent, and impactful. I value clarity, reproducibility, and collaboration—principles that guide both my engineering practice and my contributions to the broader tech community.