Hire AI developers in India who have shipped real LLM, computer-vision, and ML products
Xenotix Labs is a founder-led, startup-first software company that supplies salaried AI and machine-learning engineers to teams building on the 2026 agentic-AI wave. When you hire an AI developer through us, you are not renting a freelancer for a weekend prototype — you are getting a full-time employee backed by a team that includes NIT and IIT alumni, from institutes like NIT Kurukshetra and IIT Bombay. Across 110+ apps for 50+ brands reaching 10M+ users, our AI work is grounded in production: LLM applications on OpenAI and Claude, RAG pipelines, tool-using agents, computer vision, and custom ML models that actually ship. We hire for capability and shipped work, and we price it transparently in INR instead of hiding behind USD-only quotes.
The centre of gravity in applied AI has moved to large language models, and that is where a lot of our work lives. Our engineers design and productionise LLM applications on OpenAI/GPT and Claude: prompt engineering that survives contact with real users, structured output you can parse and store, function calling that lets a model take actions, and evaluation harnesses that catch regressions before your customers do. CorporateGate — an LLM-powered AI resume builder with ATS matching — is a live example of exactly this: generative language plus criteria-based scoring, shipped as a product rather than presented as a slide. When you hire LLM developers from us, you get people who have already turned a raw model into something that holds up in production.
The hardest part of LLM engineering is keeping answers grounded, and that is what RAG solves. We build Retrieval-Augmented Generation pipelines over your own data using LangChain and vector databases — tuning chunking, embeddings, and retrieval so a model cites your real documents instead of hallucinating a plausible-sounding answer. On top of retrieval sits the agentic layer: tool-using AI agents that plan, call APIs, and complete multi-step workflows with guardrails, retries, and observability. This is the pattern driving 2026 AI demand, and our agents run on the same production LLM foundation proven in CorporateGate, extended with orchestration rather than bolted on as an afterthought. RAG and agents are standard building blocks in our engagements, not experimental extras.
AI is not only language models, and neither is our bench. On the vision side, our team shipped ClaimsMitra, a computer-vision insurance-inspection app with 114+ endpoints doing image-based damage and condition assessment at production scale — object detection, classification, and OCR built with PyTorch and TensorFlow, served behind real APIs for web and mobile clients. Computer vision at this endpoint count is not a research notebook; it is a system that has to stay reliable under load. When you need CV engineers, you get people who have already navigated the gap between a model that works on a validation set and one that survives real, messy input from the field.
Beyond LLMs and vision, a large share of practical AI value still comes from classical and deep machine learning tuned to your domain. We train and fine-tune recommendation engines, adaptive-learning systems, forecasting models, and classifiers on your data — then wrap them in MLOps so they can be served, evaluated, and monitored rather than left to rot after training. Alcedo, our AI adaptive-learning edtech platform, personalises content per learner using ML models instead of hard-coded rules, which is exactly the kind of data-driven system that separates a genuine ML hire from someone who has only called an API. We handle the full loop: feature pipelines, training, evaluation, deployment, and the monitoring that keeps a model honest in production.
What ties all of this together is honesty about what we can prove and how we operate. The economics are published: a dedicated senior AI/ML engineer costs ₹1.8L–₹2.5L per month (roughly $2,200–$3,000) — the higher end of our range, because AI and LLM work is genuine specialty engineering, yet still a fraction of US rates that typically run 3–5x higher. Every engagement is IST-aligned with overlap for US, UK, and UAE hours, onboarded within 48 hours after a one-week trial, and covered by a mutual NDA with 100% IP transfer to you on day one. Our AI portfolio — CorporateGate for LLMs, ClaimsMitra for computer vision, Alcedo for adaptive ML — is the real reason we can promise senior capability from the first sprint. We do not invent engineer names or credentials; we match a proven engineer to your problem and let the shipped work speak.
