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Popular fullstack title, mid-level experience band, metro location and ML specialization increase competition.
Full-stack plus ML skills transfer well, though enterprise payments domain adds moderate specificity.
Multiple mandatory technical skills (ML production, full-stack, cloud, RAG, compliance) make filters strict.
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Design, develop, and deploy scalable AI/ML solutions integrated with enterprise-grade web and backend systems using full-stack technologies (MEAN/MERN/Java).
Build and operationalize machine learning models and Retrieval-Augmented Generation (RAG) pipelines that support high-volume, real-world business applications.
Collaborate with cross-functional teams to ensure enterprise compliance, security, and robust monitoring of AI/ML solutions in production environments.
4+ years of experience in Machine Learning, Data Science, or AI combined with prior full-stack development experience in enterprise environments.
Proficient in Python and JavaScript or Java; experience deploying ML models into production systems at scale.
Strong understanding of microservices architecture, REST APIs, and distributed systems; experience with GenAI models like GPT or LLaMA and prompt engineering.
Work Location: Mohali or Gurugram; Full-time onsite role with work-from-office requirement.
Experienced professional who transitioned from full-stack development to AI/ML roles with hands-on deployment experience in enterprise settings.
Comfortable operating in highly regulated, structured, and process-driven enterprise environments requiring governance, compliance, and security adherence.
Technical influencer able to contribute to architecture and technology strategy while working effectively with cross-functional teams across product, data engineering, DevOps, and security domains.