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Tier-1 employer, mid-level GenAI role, metro location, and broad skillset requirements increase applicant competition.
GenAI engineering skills are broadly transferable across industries despite advisory context.
Explicit 3+ years, mandated GenAI frameworks, Python, cloud, and MBA requirement make filtering strict.
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Design, develop, and deploy AI-powered applications including prototypes and production-ready solutions using GenAI technologies.
Build and integrate AI solutions leveraging LLMs, RAG architectures, vector databases, AI agents, and APIs across cloud platforms.
Collaborate with architects, engineers, and business stakeholders to ensure scalable, efficient, and high-quality AI applications aligned with enterprise needs.
3+ years of relevant work experience in AI engineering or software development with GenAI technologies.
MBA degree is mandatory.
Strong proficiency in Python and experience with API frameworks such as FastAPI or Flask.
Hands-on experience with GenAI frameworks (e.g., LangChain, LlamaIndex) and major AI cloud platforms (Azure OpenAI, OpenAI, AWS Bedrock, etc).
Experienced in full lifecycle AI solution development from prototyping to enterprise deployment with a focus on generative AI technologies.
Proficient in software engineering, cloud-native development (Azure, AWS, GCP), containerization (Docker), and CI/CD practices.
Able to collaborate cross-functionally to build scalable, reliable, and cost-optimized AI products integrating with enterprise systems and applying responsible AI governance.