Role Overview :

As a Lead Engineer for AI/ML, you will spearhead the design and deployment of intelligent systems that drive business value through predictive modeling and generative AI. You will work closely with cross-functional product teams, data scientists, and stakeholders to translate complex business requirements into high-performance technical solutions. Your daily efforts will focus on architecting scalable AI pipelines, refining LLM-based applications, and ensuring the seamless integration of machine learning models into production environments, directly influencing the efficiency and innovation capabilities of our client platforms.

Key Responsibilities :

- Architect and deploy end-to-end machine learning pipelines that automate decision-making processes for enterprise clients.

- Lead the development and fine-tuning of Large Language Models (LLMs) and RAG-based chatbots to enhance user interaction and information retrieval accuracy.

- Establish robust CI/CD workflows for AI/ML models to ensure rapid, reliable, and automated deployment cycles.

- Collaborate with engineering teams to optimize model performance, latency, and scalability within cloud-native environments.

- Mentor junior engineers and provide technical oversight on best practices for code quality, model governance, and system architecture.

- Evaluate emerging AI technologies and frameworks to maintain a competitive edge in product offerings and internal toolsets.

Required Skillset :

- Demonstrated expertise in building and deploying production-grade Machine Learning and Artificial Intelligence solutions with 8-12 years of relevant industry experience.

- Advanced proficiency in Python and deep experience in architecting Generative AI applications, specifically utilizing LLMs and RAG chatbot frameworks.

- Proven ability to manage cloud infrastructure on Azure or AWS, with a strong focus on CI/CD automation and MLOps best practices.

- Exceptional analytical and problem-solving skills, with the ability to communicate complex technical concepts to non-technical stakeholders effectively.

- Strong leadership capabilities, including experience in guiding technical teams and fostering a culture of continuous improvement and innovation.

- A degree in Computer Science, Engineering, or a related quantitative field, combined with the ability to thrive in a fast-paced, collaborative environment in Hyderabad.