Hire the Best Artificial Intelligence Engineers in Bengaluru, IN

I hold a M. Tech degree in Data Science & Machine Learning from PES University Bengaluru. Bachelor of Engineering in Computer Science from U.V.C.E Bengaluru. My work in AI/ML: Computer Vision project on Football Analysis using Yolov5 pre-trained model & KMeans cluster algorithm Worked on OpenAI LLM, vector database for Q & A app, document parsing app. Built Classification model for Intrusion Detection in Drones. Food delivery agency dataset visualization using Tableau. SQL backend connectivity using Power Bi. Mentored people build ML models. Tuning parameters and stuff. My work on frontend Web development: 1)A fashion boutique site I designed for my friend from scratch. No WordPress, no Workflow used. Visibility: desktop, mobile, tablet. 2)School Quiz game. 3) Some Mini projects a) SearchBar b)Progress Bar c)Form Validation d)Countdown(Excuse me for the negative value. The countdown uses our republic day as the reference. e)Hamburger menu appears upon small screen size. Wireshark network packet tracing, packet loss/retransmittion detection, network latency investigation. Network Security debugging

I primarily work on four types of projects: 1) Crafting your AI Strategy Expand your business vision with the latest tools and frameworks. Teach me about your industry, and I'll steer your AI journey from discovery through deployment—identifying opportunities, crafting your roadmap, and shaping a data-driven strategy that delivers measurable impact. 2) Automation and Intelligent Workflows Transform time-sensitive, repetitive tasks into streamlined, AI-powered workflows—from lead validation and customer onboarding to compiling accurate, visually compelling reports and advanced analytics. I help boost efficiency, reduce manual effort, and scale your operations. 3) Conversational bots and Multi-Agent Systems Engage users and help employees with text and audio based conversations. Whether for customer service, data scientists on top of internal DBs and training material, or compliance-based communication, our solutions act autonomously and collaborate seamlessly to get things done. 4) AI-Assisted Full Stack Development Our team is trained to use AI judiciously during every stage of development. Vibe coding can go horribly wrong when in the hands of the uninitiated, but when you combine tools like Cursor with our engineering expertise, you get reliable new products and services faster than has ever been possible. My portfolio has more examples, but in short, if you're looking to build specialized agents to perform enterprise-ready tasks, you'd be hard-pressed to find a more qualified developer anywhere on Upwork. I'll be applying as an organization - krazimo (krazimo.com), so you'll get two world-class engineers (Mridul and I) working on your project, as well as a number of junior engineers to perform the smaller engineering tasks. You'll have full transparency into who's doing what, and our junior engineers work for approximately 2/3 our hourly rate. Here's a little about my 11 years of experience. Google (2019-2025) I spent six years as a senior software engineer at Google. My two major projects currently were Admin AI Assistant: I'm worked as an LLM specialist on building a RAG solution to improve Google's customer service in our workspace Admin Console. Gemini Reporting: Led a team of 10 people in building a large scale pipeline that can handle high QPS events on Gemini usage and report on value and RoI for our Gemini Product in Google Workspace. Apart from these, I have designed, implemented and shipped many technically complex products at Google. They often involved coordinating efforts among large teams and always required me to adhere to the highest engineering standards. I hope I can bring this expertise to your company. NLP Engineer (2016-2019) Cofounded, Headed AI and built the prototype and MVP for Butter.ai, which raised $3M in seed funding and was eventually acquired by Box. Worked on sentiment analysis problems for psychiatric chat centers (analysis user messages to flag dangerous situations) Worked on text extraction and question answering problems for a company that helped health insurance providers answer complex questions related to a customer's coverage. Mobile Engineer (2013-2015) Worked on a number of apps for clients - including building the cleartax.in android application. Worked at IBM as a software engineer on a MDM product that involved core android development (very low level control of services and permissions). At the moment, this process is more about exploring the space and seeing what people are looking for in the world of AI, outside massive AI-centric companies like Google (my hourly rate is actually below my current salary, so you're getting a pretty great deal while I perform this exploration)!

I'm a SaaS developer who has been CTO three times, and I've shipped for YC and a16z startups. I still write the code. At Dun & Bradstreet I built GetEmail, a Fortune 500 AI SaaS on 800M+ profiles serving 2M+ active users. As CTO of MonkeyBox I took an $18M-funded platform to 70,000 users. WHERE THE SCALE COMES FROM : • GetEmail (Dun & Bradstreet): AI and big-data SaaS on a dataset of 800M+ profiles and 50M+ companies. Pipelines processing 5M profiles a day and verifying 10M emails a day, plus the AWS architecture underneath. • MonkeyBox: CTO of a B2B2C food SaaS that raised $18M+ from NB Ventures and Blume Ventures. 70,000+ users, 150+ schools, 2,000+ daily orders, 1.2M+ meals delivered, 20 engineers. • One Earth Venture Studio (NB Ventures): Fractional CTO. Built and ran a 30-engineer organisation across four agile teams, launching ventures from zero and setting build-versus-buy across the portfolio. • UnitPay: I designed, built and shipped it alone. Think Stripe Billing plus usage-based metering: it meters AI consumption and orchestrates Stripe, Razorpay and Paddle behind one API, so a pricing change never means a rewrite. • Agent sandbox infrastructure: early engineer on a venture-backed AI app builder. Sandboxed execution of model-generated code, prompt optimisation and prompt caching, across E2B, Daytona and Cloudflare runtimes. • Nine years, 40+ MVPs shipped, and a 22-month continuous contract on this platform. WHAT I ACTUALLY BUILD : • Multi-tenant SaaS architecture: tenant isolation, RBAC, OAuth2, audit trails, built in on day one rather than retrofitted • Usage-based and subscription billing: Stripe, Paddle, Razorpay, metering, invoicing, dunning, credit and entitlement systems • SaaS MVPs that survive real users and then scale, instead of getting rewritten at the first traction spike • AI features inside SaaS products: RAG over your own data, LLM integration, agents, and metering the token spend they generate • Sandboxed code execution for AI agents: E2B, Daytona and Cloudflare runtimes, prompt caching, plus the per-tenant accounting for what those runs actually cost you • High-throughput data pipelines and the AWS architecture and cost control around them • Admin dashboards, internal tools, analytics and reporting layers THE PART MOST DEVELOPERS SKIP : Billing is where SaaS products quietly lose money. A webhook that retries without being idempotent double-credits a customer. A plan limit enforced in the UI instead of the metering layer is not enforced at all. Usage that is counted after the fact cannot be billed for. I have built the metering, credit and entitlement layer that sits under all of it, which is why I would rather ask what your pricing model is before I ask what your stack is. MY STACK : Frontend: React, Next.js, TypeScript, Redux, Tailwind CSS Backend: Node.js, ExpressJS, NestJS, REST APIs, microservices Databases: PostgreSQL, MongoDB, MySQL, Redis, DynamoDB Cloud: AWS (Lambda, EC2, RDS, S3, CloudFront, API Gateway), Docker, Kubernetes, CI/CD AI: RAG pipelines, OpenAI and Claude APIs, pgvector, Pinecone Payments: Stripe, Razorpay, Paddle, usage-based metering I hold AWS Solutions Architect, Developer and DevOps Engineer certifications. WHERE I'M A GOOD FIT You're building a SaaS product, or you have one that works and is starting to buckle: slow dashboards, billing that can't express your pricing, an architecture that fights every new feature. I've been on the other side of that table as a CTO, so I can tell you what to cut as well as what to build. Available 30+ hours per week. Send me what you're building and the one thing about it that's keeping you up, and I'll tell you honestly whether I'm the right person for it.

Overview: You have an AI product idea — or an existing product that needs AI built into its core. You need someone who won't just write code, but make the hard architectural decisions that determine whether your product scales or breaks at 10,000 users. That's what I do. I've shipped 5 AI-native products in the last 2 years, each running in production with real users today. Not prototypes. Not demos. Production systems handling real data, real money, and real compliance requirements. Recent results: → Built an AI conversation intelligence platform that analyzes calls across 19 dimensions in real-time — now processing hundreds of conversations daily for a US-based SaaS company → Delivered an AI medical education platform with 11 LLM-powered endpoints, integrating clinical evidence from randomized controlled trials — used by healthcare professionals for continuing education → Shipped an AI learning platform with 9 specialized AI pipelines — 500+ study hours saved for users within months of launch → Architected an AI-powered industrial support system with vector search and multi-tenant isolation — deployed across operator, technician, and admin roles for a European client What makes me different from other AI developers: Most developers bolt AI onto existing products as a feature. I architect systems where AI is a core capability — from database schema to user experience. Every project I deliver includes production infrastructure (CI/CD, monitoring, error tracking), not just application code. I also run a team at Growth Loops Technology, which means I can scale up when your project needs it — without you managing multiple freelancers. I'm the right fit if you need: → An AI-native product built end-to-end (backend, AI pipelines, deployment) → LLM integration done properly (structured output, RAG, multi-stage pipelines) → A senior architect who can own technical decisions and communicate clearly → Someone who ships on schedule and writes code that holds up in production Technical depth (for the engineers reading this): Backend: NestJS, Node.js, TypeScript, Python, FastAPI, Django AI/ML: GPT-4o, Claude, LangChain, LangSmith, Whisper, AssemblyAI Data: PostgreSQL, Redis, BullMQ, Pinecone, OpenSearch, Meilisearch Infra: Docker, GitHub Actions, AWS, Cloudflare R2, Sentry 15+ years of software engineering. Every project delivered with authentication, async job processing, multi-tier caching, and production monitoring baked in from day one.

Namaste! 🙏 Thank you for visiting my profile. I am a solution-oriented engineer with a passion for turning complex ideas into scalable, high-performing products. From high-level Generative AI to precision design, I bridge the gap between imagination and execution. 🛠️✨ 💎 Key Highlights 🏆 IIT Alumnus – Driven by logic, backed by elite education. 🌍 65+ Global Clients served across 15+ countries. 💯 100% Job Success Rate – Excellence is my only standard. 📜 25+ Professional Certifications in AI, Cloud, and Frameworks. 🧠 AI, Machine Learning & LLM Expertise 🤖 - Generative AI: OpenAI GPT-4, Claude, LangChain, & Llama-3 💬 - Custom Chatbots: VectorDBs (Pinecone, Milvus, ChromaDB) & RAG Pipelines 🏗️ - LLM Fine-Tuning: Domain-specific training (Medical, Legal, Finance) 📚 - Computer Vision: YOLO, Object Detection, Scene Recognition & Motion Tracking 🎥 - AI Agents: Building autonomous voice & text bots for seamless engagement 🗣️ - Hardware AI: Expert in NVIDIA Jetson for Edge Computing ⚡ 💻 Full-Stack Development & UI/UX 🌐 - Frontend: React.js, Vue.js, Angular, Next.js (Modern & Fast) 🚀 - Backend: Node.js, Flask, FastAPI, Django (Scalable & Secure) 🛡️ - Cloud & DevOps: AWS (Certified), GCP, Azure, Docker, & CI/CD ☁️ 📊 Data Engineering & Automation ⚙️ - Web Scraping: Advanced Python automation, Selenium, & Scrapy 🕸️ - Data Science: Analysis with Power BI, Tableau, & Seaborn 📈 - OCR & Processing: Extracting data from images, posters, & documents 📄 - Parallel Computing: Multiprocessing for high-speed data handling ⚡ 💍 Specialized Design & Hardware 🛠️ - 3D CAD: Professional Jewelry & Industrial design in Rhino CAD 💎 - Image/Video: OpenCV, Stable Diffusion, & Digital Image Processing 🖼️ - Edge AI: Deploying AI models on local hardware & IoT devices 🔌 🗄️ Database Mastery - SQL: PostgreSQL, MySQL, MSSQL 🗄️ - NoSQL: MongoDB, Firebase, Redis 📁 - Vector/Graph: Pinecone, Milvus, Neo4j 🕸️ 🤝 Let’s Build Something Extraordinary! Whether you are a startup looking for a Founding Engineer or an enterprise seeking AI Transformation, I am here to lead your tech journey. 🚀 📩 Let’s collaborate to bring your vision to life! 🌟 - Himanshu Moliya (IIT Alumnus)

Voice AI · AI Agents · RAG · LLM Apps · Conversational AI Vedansh is a CTO and AI engineer with 12 years of experience, the last 4 building AI agents and AI products at scale. He has taken 6+ products from zero to one. He founded Devsnest and ran the world's largest coding bootcamp, placing 2,000+ students at Google, Amazon, and Microsoft. Before that, he scaled HackerRank from 500K to 10M+ developers and was a Tech Lead at Casper and Owens Corning. As Fractional CTO: → Voice AI agents for Fortune 500 clients (3x cost reduction) → AI agents automating Amazon agency ops for 20+ agencies → AI writing tool with 500K+ users, $20K MRR → AI recruiter automating 50% of a human recruiter's job → AI legal drafting for Indian lawyers Time-zone overlap: 8 hrs with EST/CST, 6 hrs with PST/MST, Full UK & EU coverage. He thrives in ambiguity, ships fast, hires well, and turns ambiguous product ideas into working software. If you're building an AI product and need senior CTO-level thinking with hands-on engineering, let's talk.