The company is seeking a highly skilled AI/ML Engineer with 4 to 7 years of experience to design, develop, and integrate AI-powered solutions into our SaaS products. The ideal candidate will have strong expertise in Python, Object-Oriented Programming concepts, Large Language Models (LLMs), and modern AI frameworks.

This role involves working on end-to-end AI integrations, conversational AI systems, retrieval augmented generation workflows, and scalable AI microservices. You will collaborate closely with product, engineering, and architecture teams to build intelligent features that improve user experience and business efficiency.

Qualifications :

- Bachelors degree in Computer Engineering, Computer Science, Artificial Intelligence, or a related field.

- 4 to 6 years of experience in AI/ML engineering or related software development roles.

- Strong understanding of Object-Oriented Programming concepts and software engineering principles.

- Proficiency in Python for AI and backend development.

- Hands-on experience with Vector Databases and semantic retrieval systems.

- Experience working with LangChain and conversational AI frameworks.

- Minimum 3 years of recent exposure to Large Language Models (LLMs), Gen-AI, and end-to-end AI integration on workflows.

- Experience integrating AI capabilities into SaaS products.

- Strong understanding of microservices architecture and distributed systems.

- Excellent analytical, debugging, and problem-solving skills.

Key Responsibilities :

- Build and maintain scalable AI services using Python and microservices architecture.

- Develop conversational AI solutions using modern LLM frameworks and orchestration tools such as LangChain.

- Work on end-to-end LLM integrations, including prompt engineering, retrieval workflows, and inference optimization.

- Design and manage Vector Database integrations for semantic search and retrieval-based applications.

- Collaborate with product and engineering teams to identify AI use cases and translate them into scalable technical solutions.

- Optimize AI workflows for performance, scalability, and reliability in production environments.

- Participate in architecture discussions and contribute to AI platform design decisions.

- Ensure proper documentation, testing, and deployment of AI features and services.

- Stay updated on emerging trends and advancements in AI, machine learning, and Generative AI.