Hire Dedicated AI Developers
Accelerate your product roadmap with AI developers to build intelligent apps powered by LLMs, custom embeddings, and real-time reasoning using the latest AI frameworks and tools.
- Free Trial, Zero Overheads, Quick Setup
- Create Proprietary LLM-Powered Solutions.
- Interview Developers Before Committing
- Benefit from Flexible, Simple Terms
Trusted by Leading
Industry Clients Globally
Join our esteemed clients who rely on innovative technology solutions to drive their success and growth.
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Trusted by Leading
Industry Clients Globally
Join our esteemed clients who rely on innovative technology solutions to drive their success and growth.
Hire Dedicated AI Developers for Your LLM-Powered Applications
Sridhar
Sridhar builds generative AI applications using OpenAI, LangChain, and Gemini. He works with custom embedding pipelines, vector databases, and streaming responses for chat interfaces.
Skilled In
Swathi
Swathi focuses on LLM-based backend systems and retrieval-augmented generation. She uses LangGraph workflows, works with tools like LlamaIndex, and deploys APIs via FastAPI or Flask.
Skilled In
Mithun
Mithun builds scalable AI applications with Django and FastAPI, integrating vector search, chunking strategies, and streaming UIs. He works across AWS, GCP, and Azure for production deployments.
Skilled In
Hire Dedicated AI Developers for Their Specialized Expertise
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LLM-Powered Backend Systems
We build intelligent backends using OpenAI, Claude, and open-source LLMs with structured prompt orchestration via LangChain and LangGraph.
Vector Search and Embeddings
Our developers design embedding pipelines and work with Pinecone, Weaviate, and FAISS for real-time semantic search and retrieval-augmented generation.
Custom Toolchains and Agents
We use LangGraph, LlamaIndex, and React patterns to build AI agents with memory, tool usage, and decision-making loops for enterprise use cases.
Python Framework Expertise
From Django APIs to FastAPI microservices and Flask apps, our team builds scalable LLM-powered APIs ready for integration into production systems.
Testing and Evaluation of LLM Apps
We test for hallucinations, latency, and performance using LangSmith, prompt testing tools, and model tracing for reproducibility and debugging.
Cloud Deployment and Scaling
Deploy your AI stack on AWS Lambda, Azure Functions, or GCP Cloud Run, with CI/CD pipelines and observability for production-grade performance.
Why Hire Dedicated AI Developers from Entrans
1. LLM Experience That Scales
We’ve built apps with GPT-4, Claude, Gemini, and open-source LLMs.
2. Built for Production
Start within a week — no long hiring cycles or back-and-forth delays.
3. Tool-Aware AI Workflows
Integrate memory, RAG, and agent logic with LangChain or LangGraph.
4. Cost-Effective API Development
Build APIs with affordable pricing models using Django, Flask, or FastAPI.
5. Flexible Cloud Deployment
Deploy on AWS, Azure, or GCP with containerized and serverless options.
Our Hiring Models
Dedicated AI Developers
Ideal for long-term projects involving AI apps, chatbots, or LLM pipelines.
Team Augmentation
Add AI talent to your existing dev team to speed up innovation.
Project-Based Engagement
Build and deploy custom LLM tools, vector search, or chatbot interfaces.
Tech Stack Used By Our AI Developers
LLM + Embedding Stack
Python Frameworks + APIs
Testing + Prompt Tools
Deployment + Cloud
Our Development Process
Requirement Analysis
Planning & Design
Development
Testing
Deployment
Maintenance & Support
Latest Trends in AI Development
Generative AI Evolution
GenAI creates diverse content like video and code. Top companies are using GenAI across apps for productivity and automation. See how it can boost your efficiency today.
Development of Specialized AI Agents
Agents plan, act, and achieve goals independently. Specialized AI agents perform complex processes and interact with systems curated to your business needs.
Widespread Use of Multimodal AI
AI understands text, images, audio, and video better. Using multimodal AI, companies handle interactions and complex data processing. Use multimodal AI for more engaging experiences.
Ethical Usage of AI
Ethics, privacy, and governance are critical concerns. For companies, transparency and addressing biases are key. Work with AI teams focused on building trust and mitigating risks safely.
Usage of Edge AI
Deploying AI closer to data sources is essential for faster real-time decisions and lower latency. Use Edge AI for instant insights and to act faster.
Entrans launches Thunai - An Agentic Platform for AI Agents, Meeting Assistance & Enterprise Search
We built Thunai, a powerful enterprise-grade Agentic Orchestration platform that revolutionizes sales, support, and marketing operations. From concept to market in just 5 months, Thunai showcases our technical prowess and ability to execute complex AI solutions with exceptional speed and precision.
Our Customer Success Stories
Building an Affiliate Marketing App + Platform
The client aimed to create an app that integrates e-commerce with social change, providing users with curated deals from ethical brands and fostering a community of conscious consumers.
With consistent delivery and ownership, the engagement extended into a long-term roadmap for new features and optimizations.
HIPAA-Certified Blockchain-Enabled Chat Platform
The client sought a technical partner to brainstorm, plan, design, develop, and implement a robust chat platform with the capacity to scale as their product grows.
The backend was powered by Node.js, ensuring efficient data handling and processing. MongoDB was used for the database, providing scalable and flexible data storage.
FAQs on Hiring Dedicated AI Developers
An AI developer builds applications that use machine learning, LLMs, and embeddings to add intelligence to digital systems.
They work with frameworks like LangChain, LangGraph, LlamaIndex, and libraries like Hugging Face, OpenAI API, and Python-based web tools like FastAPI.
LLM-powered applications are typically deployed on AWS, Azure, or GCP using serverless infrastructure or containerized pipelines with observability and scaling in place.
