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Tier-1 brand, metro location, and mid-level GenAI/full-stack ML deployment role create high competition.
Core GenAI and ML engineering skills transfer across industries but industrial deployment raises domain specificity.
Multiple mandatory years, specific LLM experience, and production ML deployment requirements increase strictness.
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Lead the design, development, and deployment of enterprise-grade Generative AI solutions in a cloud environment.
Own the full lifecycle of AI projects from translating business needs into technical problems to operationalizing agentic AI systems.
Collaborate with IT, PRE, and business teams to ensure successful integration and maintenance of AI/ML solutions within existing software architecture.
Bachelor’s degree in Computer Science, Data Science, Statistics, Physics, Mathematics, Engineering, or related field.
5+ years of professional experience in software engineering, machine learning, or data-focused roles.
3+ years hands-on experience developing and deploying machine learning solutions using Python, PySpark, or Scala.
1+ years direct experience building solutions with Large Language Models (LLMs), agentic frameworks (e.g., LangChain), or related Generative AI technologies.
Experience applying ML and AI to solve large-scale, real-world industrial problems using high-volume, diverse data sources.
Strong programming skills including interface development for data visualization and insight extraction from complex datasets.
Proven ability to communicate complex technical concepts clearly to leaders and cross-functional teams and manage projects in ambiguous, fast-paced environments.