Lead Software Engineer GenAI Development and Exploration
Location : India
Experience : 5–10 Years
Primary Skillset : Generative AI Services, Machine Learning, Python, Cloud, MLOps, Prompt Engineering
About the Role :
We are seeking a visionary and hands-on Lead Software Engineer to drive Generative AI development and exploration initiatives within our technology innovation team. This role is ideal for someone passionate about applying GenAI to real-world enterprise challenges and who enjoys building proof-of-concepts, production-ready solutions, and scalable AI platforms.
Key Responsibilities :
- Lead the design and development of Generative AI applications, including LLM-based solutions, document intelligence, summarization, chatbot development, and intelligent automation.
- Evaluate and integrate GenAI services and APIs (e.g., Vertex AI, OpenAI, Anthropic, HuggingFace, etc.) into existing or new platforms.
- Build scalable backend services and data pipelines to support AI / ML workloads.
- Explore and validate use cases across multiple business functions for GenAI application and automation opportunities.
- Mentor junior engineers on GenAI design patterns, best practices, and engineering discipline.
- Partner with data scientists, product teams, and business stakeholders to define requirements, build MVPs, and iterate toward enterprise-scale solutions.
- Champion MLOps practices for GenAI model deployment, monitoring, and lifecycle management.
- Contribute to technical research, architecture recommendations, and the long-term GenAI roadmap.
Qualifications :
Bachelor's or Master's degree in Computer Science, AI / ML, Data Science, or related field.8+ years of experience in software engineering with 2–3 years working directly with AI / ML models or GenAI solutions.Strong experience with Python, cloud platforms (especially GCP Vertex AI), and ML frameworks.Hands-on experience with LLMs, prompt engineering, fine-tuning, and embeddings.Experience in building and integrating GenAI services in real-time or batch applications.Solid understanding of machine learning lifecycle, data preprocessing, and deployment pipelines.Familiarity with CI / CD pipelines, API development, and cloud-native architectures.Excellent communication, collaboration, and stakeholder management skills.Skills Required
Python, MLops, Cloud, Machine Learning