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Strong employer brand, mid-level generalist AI+fullstack role, and hybrid location attract many qualified applicants.
Role requires combined AI/ML specialization and full-stack production experience, limiting cross-industry transferability.
Explicit 5–8 years requirement plus many mandatory AI, infra, and LLM skills enforces strict filtering.
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Design, build, and deploy production-ready AI infrastructure, ML models, and full-stack applications integrating Generative AI, Computer Vision, and NLP.
Architect Agentic AI workflows, RAG systems, and high-performance data pipelines for enterprise AI use cases.
Own application support including troubleshooting, incident management, performance monitoring, and stakeholder engagement for AI/ML production systems.
Bachelor’s degree required.
5–8 years of experience in AI architecture or ML development.
Mandatory skills: Python, AI/ML algorithms, NLP, Computer Vision, cloud AI platforms (e.g., Vertex-AI), Agentic AI and RAG framework expertise (LangChain, LlamaIndex), LLM fine-tuning (GPT, Claude, Llama), Docker, Kubernetes, SQL/NoSQL/Graph/Vector databases.
Experience with application support processes, incident management, and stakeholder management.
Experienced in end-to-end AI/ML system lifecycle including architecture, deployment, and operational support in production environments.
Able to independently manage AI infrastructure and full-stack development with strong business stakeholder engagement and release management.
Strong background in advanced Generative AI techniques, enterprise AI workflows, and robust data engineering to support scalable AI solutions.