Hiring -GEN AI/LLM Engineers- only Imm Joiners

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.