GenAI Engineer

About Habilelabs

At HabileLabs Pvt. Ltd., headquartered in Jaipur, we are a premier software product development and IT service provider, dedicated to helping businesses thrive in the digital era. Since 2016, we have been at the forefront of delivering innovative software and IT solutions that transform digital presence, automate processes, and enhance operational efficiency. Our expertise lies in developing engaging web and mobile applications, while leveraging cutting-edge technologies such as AI and cloud computing to provide exceptional value to our clients.

With a team of over 200 talented professionals, we are passionate about delivering excellence in every project. Our solutions are designed to not only meet but exceed client expectations, ensuring seamless operations and empowering businesses with a competitive edge. Our global presence, including offices in Canada, the USA, Gurugram, and Mumbai, enables us to serve more than 160 clients across the globe, with a remarkable 95% client retention rate.

Job Description: AI Engineer

Position Title: AI Engineer

Experience Level: 4-6 years

Employment Type: Full-time

Department: Engineering

Required Qualifications

Technical Expertise

• 4–6 years of professional experience in AI/ML engineering, with focus on LLM-based applications or agentic systems
• Deep proficiency in Python and hands-on experience with AI/ML frameworks (LangChain, Hugging Face, PyTorch, TensorFlow)
• Proven experience building or optimizing Retrieval-Augmented Generation (RAG) systems
• Hands-on experience with LLM architectures and working with models of 7B+ parameters
• Practical knowledge of small language models (SLMs) and model quantization/optimization techniques
• Familiarity with MCP servers or similar integration protocols for LLM tools
• Proficiency with version control (Git) and CI/CD pipelines
• Knowledge of containerization (Docker) and cloud platforms (AWS, Azure, or GCP)
• Understanding of database systems (relational and vector databases)
• Solid understanding of ML lifecycle: model training, evaluation, validation, and deployment
• Experience with prompt engineering, in-context learning, and few-shot learning techniques
• Understanding of evaluation metrics and benchmarking frameworks for LLM systems
  
  

• Experience with open-source LLM frameworks and models (LLaMA, Mistral, Phi, etc.)
• Hands-on experience with vector databases and semantic search optimization
• Background in building production-grade agentic systems at scale
• Familiarity with prompt frameworks, chain-of-thought techniques, and structured outputs
• Experience with model serving platforms (vLLM, Ray Serve, TorchServe)
• Knowledge of AI safety, model alignment, and responsible AI practices
• Contributions to open-source AI/ML projects
• Experience with multi-modal models or advanced retrieval techniques
• Familiarity with organizational process automation and enterprise AI deployment
• Experience designing and implementing multi-agent systems or agentic AI frameworks