Headline

Senior AI Engineer | LLMOps & Production AI Systems | Multi-Agent Orchestration & RAG | LangGraph, vLLM & TensorRT | AWS Bedrock & Distributed Systems | Bengaluru

About

🚀 4 hours → 2 seconds. I build AI systems that make that kind of production impact. I’m a Senior AI/ML & Generative AI Engineer with 5+ years of software engineering experience, specializing in production LLM systems, agentic AI, AI infrastructure, and high-performance inference. 💡 $2.3M+ measurable business impact | 99.99% uptime | 85% reduction in manual context-fetching latency I bridge the gap between experimental AI and reliable, scalable production systems—taking models from notebooks to low-latency APIs and enterprise-grade platforms. 🚀 What I’m Building Agentic AI & MCP • Production MCP servers connecting multi-agent systems to enterprise tools such as HappyFox and Jira • Reduced manual context-fetching latency by 85% LLM Evaluation & Distillation • GPT-4-supervised evaluation and knowledge-distillation pipelines on B100 GPUs • Compressed enterprise firewall validation from 4+ hours → 2–5 seconds • Achieved zero LLM inference cost in the production validation workflow Advanced Retrieval & AI Systems • 5-stage confidence-gated agent architectures • Hybrid semantic search + NL-to-SQL • p95 latency <300ms for supply-chain intelligence workloads ⚙️ Core Technical Expertise Generative AI: Multi-Agent Systems, LLMs, RAG, GraphRAG, LangGraph, DSPy, Tool Calling, MCP, NeMo Guardrails AI Infrastructure & Inference: vLLM, TensorRT-LLM, GPU Inference, B100, A100, L4, Continuous Batching, Kubernetes, AWS Bedrock, GCP Vertex AI Evaluation & Alignment: LLM-as-a-Judge, RAGAS, RLHF, DPO, LoRA, QLoRA, 72B+ parameter models Production Engineering: Python, FastAPI, Docker, Kubernetes, AWS, GCP, Distributed Systems, MLOps, High-Availability Architecture 🏢 Enterprise & Compliance I build fault-tolerant AI systems for regulated environments, including: • 99.99% uptime for HIPAA-compliant infrastructure • 2 healthcare audits, zero findings • NLP pipelines processing 50,000+ financial documents with zero PII leakage • Production systems across enterprise security, healthcare, and financial services 🏆 Recognition • Co-author — IEEE ACAI 2022 • Winner — AI Help Desk Hackathon • Winner — AI Doctor Analyzer Hackathon 🎯 Open to Opportunities I’m currently exploring: Senior AI Engineer | Senior Applied AI Engineer | AI Platform Engineer | GenAI Engineer | AI Infrastructure Engineer I’m particularly interested in product companies solving difficult architectural problems and scaling AI systems from prototype to production. 📩 Let’s connect: rakshitkumarkn@gmail.com

Location

Bengaluru

AI stack

anthropic apis

claude code

cursor

hugging face

langchain

langgraph

Work experience

SDE 2 AI/ML at Gruve, Sep 2025 - Present · 1 yr 1 mo, Région métropolitaine de Bangalore, Building production GenAI systems and distributed ML infrastructure for Fortune 500 enterprises. Key projects: • Firewall Validation — LLM-supervised Knowledge Distillation (GPT-4 Teacher → distilled student ensemble). 4+ hours → 2–5 seconds. Zero LLM calls at inference. 200+ firewalls, 10× faster migration. • AI/NLP Redaction — Zero PII leakage. SOC 2 passed. 99.2% precision at 2,000+ docs/day. • Enterprise AI Search — Neo4j + Qdrant hybrid. 10K+ QPD at p95 <300ms. 99.9% uptime. • Azure Migration — 62% cost reduction ($18K/month) via event-driven Container Apps. • TechGenie Voice Agent — 80+ ticket types, 42% faster resolution, 3 enterprise clients. Stack: GPT-4 · Claude 3.5 · PyTorch · BERT · LangGraph · Neo4j · Qdrant · AWS Bedrock · ECS · Lambda · SQS · FastAPI · Azure · Docker · Kubernetes

Artificial Intelligence Engineer at August AI, Aug 2024 - Aug 2025 · 1 yr 1 mo, Bengaluru, Karnataka, India, • Architected a multi-agent AI system for automated patient interviews and clinical report summarization, reducing clinician administrative burden by 45% and processing 2,500+ daily interactions across 3 major healthcare facilities. • Optimized LLM memory management and prompt engineering for extended medical conversations, improving context retention and diagnostic accuracy by 75%; achieved 91% accuracy across 5,000+ patient sessions, cutting initial consultation time by 40%. • Engineered NLP-driven medical documentation pipelines achieving 97% accuracy across 10,000+ clinical documents monthly, delivering $150K annual cost savings through reduced manual review. • Deployed HIPAA-compliant AI infrastructure on AWS and Azure with end-to-end encryption and RBAC, sustaining 99.99% uptime for 500+ concurrent users through all enterprise regulatory audits.

Machine Learning Engineer at Snive, Feb 2024 - Aug 2024 · 7 mos, Région métropolitaine de Bangalore, Machine Learning Engineer Snive (Krut AI), BengaluruJan 2024 – Aug 2024 • Implemented Fast UNet and VAE optimizations for SDXL + ControlNet, reducing inference time to 1–2 seconds and cutting e-commerce client content creation costs by 80%; pipeline processed 50,000+ product images monthly. • Reduced GPU memory consumption by 60% via gradient checkpointing and mixed-precision training, enabling costefficient scaling and saving $30K/month in AWS G4/G5 infrastructure costs.

Associate Data scientist at Lincode India, Sep 2022 - Feb 2024 · 1 yr 6 mos, Bangalore, • Delivered OCR, image segmentation, and object detection models for 8 international manufacturing clients, achieving 92% OCR accuracy at 0.25s inference and a 25% improvement in production quality control across automotive and electronics sectors Replaced redundant polling with server-sent events for real-time inference updates, cutting API infrastructure costs by 90% and generating $2M in annual savings across 15+ global facilities processing 50,000+ components daily.

Data Science Intern at Lincode India, Mar 2022 - Sep 2022 · 7 mos, Bengaluru, Karnataka, India, Lincode is an Artificial Intelligence & Industrial IoT solutions company increasing the profitability of manufacturing companies globally.

Research Scholar - Data science at MENMOZHI TECHNOLOGIES, Dec 2021 - Mar 2022 · 4 mos, Бангалор Сельский

Education

Msc, big data analytics, St Joseph's University

Bachelor of Computer application - BCA, Coder, Sheshadripuram Arts, Science & Commerce College, Sheshadripuram , Bangalore-20

Public links

github: https://github.com/rakshit176

rakshith-kumar-kn-ai-engineer-portf.vercel.app: https://rakshith-kumar-kn-ai-engineer-portf.vercel.app/