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GenAI specialization reduces pool, but mid-level nature and known global employer increase competition.
Technical GenAI skills transfer across industries, though enterprise manufacturing domain familiarity moderately matters.
Explicit 5+ years plus hands-on GenAI, Python, and production deployment requirements.
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Own end-to-end design, development, and operationalization of Generative AI (GenAI) and Large Language Model (LLM) solutions for defined use cases.
Build and deploy GenAI applications including RAG pipelines, prompt orchestration, and agent workflows with Python automation, ensuring production reliability, scalability, and compliance with enterprise AI policies.
Collaborate with business and technical partners to translate needs into scalable AI solutions, mentor AI engineers, and drive adoption through continuous improvement and feedback integration.
Bachelor's degree in Computer Science, Engineering, Data Science, or equivalent practical experience.
Minimum 5 years professional experience in software engineering, AI/ML, or applied data systems.
Strong proficiency in Python and experience building production-grade services.
Hands-on experience designing and deploying GenAI / LLM-based applications.
Experienced in operationalizing GenAI/LLM solutions end-to-end with a strong technical and architectural judgment.
Skilled in collaborating across business and technical teams to translate use cases into scalable AI solutions with clear communication of tradeoffs.
Comfortable mentoring technical teams and guiding non-software practitioners on GenAI-powered tools and low-code/no-code methods.