Role Overview

Vsquare Systems Pvt Ltd is actively seeking experienced AI Engineers with a proven track record of building and delivering production-ready AI solutions. This role is specifically for seasoned professionals who have moved beyond academic projects or basic API integrations, and have successfully designed, built, and deployed AI systems integral to real enterprise workflows.

The successful candidate will be instrumental in developing cutting-edge AI-driven applications, intelligent automation systems, advanced document intelligence platforms, and sophisticated agent-based AI solutions for our enterprise clientele. A strong hands-on command of Generative AI, Machine Learning, NLP pipelines, and production AI deployment, ideally within AWS environments, is essential.

Key Responsibilities

AI Solution Engineering

• Design and build production-grade AI applications utilizing Generative AI and Machine Learning.
• Develop comprehensive end-to-end AI pipelines, encompassing data ingestion, model inference, evaluation, and deployment.
• Construct robust enterprise AI solutions that seamlessly integrate with APIs, databases, and data platforms.

Generative AI Development

• Implement LLM-based applications using state-of-the-art frameworks.
• Design and implement advanced Retrieval Augmented Generation (RAG) architectures.
• Optimize prompts, embeddings, and knowledge retrieval pipelines for maximum efficiency.

Agentic AI Systems

• Develop AI agents capable of executing complex, multi-step workflows.
• Implement orchestration frameworks that enable sophisticated reasoning and effective tool usage.
• Build AI automation systems that integrate seamlessly with existing enterprise tools.

Machine Learning & NLP

• Develop and deploy models for text processing, classification, knowledge extraction, and automation workflows.
• Work proficiently with large-scale structured and unstructured datasets.

Production Deployment

• Deploy AI applications in cloud environments, with a preference for AWS.
• Implement rigorous monitoring, evaluation, and optimization strategies for AI systems in production.

Mandatory Experience (Strict Requirement)

Candidates must demonstrate hands-on project experience in at least two or more of the following areas:

• Development of Generative AI or LLM-based applications.
• Building NLP or document intelligence systems.
• Developing AI-driven automation solutions.
• Implementing RAG-based knowledge retrieval systems.
• Deploying machine learning models in production.
• Developing AI agents or workflow automation systems.

Applicants should be prepared to articulate their role, architectural decisions, and technical implementation details for past AI projects clearly.

Required Technical Skills

Programming

• Strong proficiency in Python.
• Experience developing scalable AI applications.

AI / ML

• Hands-on experience with:
• Machine Learning
• NLP
• Generative AI
• LLM application development

AI Frameworks

• Experience with one or more of the following:
• LangChain / LlamaIndex or equivalent.
• HuggingFace ecosystem.
• Vector search / embedding frameworks.

Data & Integration

• Experience building pipelines that process structured and unstructured data.
• Experience integrating AI systems with APIs, databases, or enterprise applications.

Cloud

• Experience working with AWS-based AI or data platforms.

Strongly Preferred Experience

• Experience with Agentic AI frameworks.
• Experience with AI automation workflows.
• Experience building document intelligence platforms.
• Experience with vector databases and semantic search.

Domain Experience

Experience working within Life Sciences, Healthcare, Research, or other regulated industries will be considered an advantage.

Experience

3 - 8 years of professional experience is required. Candidates must possess demonstrated experience delivering AI solutions in real enterprise environments.

Important Note for Applicants

Candidates should be prepared to discuss:

• Real AI projects they have personally worked on.
• The architecture and implementation details of these projects.
• Challenges encountered during production deployments.
• How their AI systems were utilized in actual business workflows.

Profiles that primarily showcase AI experimentation, tutorials, or proof-of-concept work without evidence of real project delivery may not be considered. Applicants are required to include brief details of at least one AI project they have successfully implemented in a production environment.

Why Join Vsquare Systems

• Opportunity to engage with real enterprise AI implementations.
• Exposure to global enterprise clients and their challenging projects.
• Work on advanced AI automation and agentic AI systems.
• Collaborate closely with experienced data engineering and AI architecture teams.