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Tier-1 brand, mid-level ML title, 3–5 years, metro location, and broad full-stack/LLM requirements drive high competition.
Core ML and full-stack skills transfer across industries, but marketing/GTM and enterprise security context raise sensitivity to medium.
Multiple explicit mandatory requirements (3–5 years, LLM/production experience, React, cloud, Docker/Kubernetes) increase strictness to high.
Develop AI-driven applications and workflow automation focused on marketing and go-to-market use cases.
Integrate large language models (LLMs), APIs, business rules, and data into scalable, cloud-native production systems.
Lead end-to-end technical initiatives including design, implementation, reviews, and ensuring reliability across full-stack and distributed systems.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
3–5 years of software engineering experience.
Proficiency in Java, Kotlin, Python, or Node.js with experience in building production applications using LLMs or prompt engineering.
Experience with React or modern frontend frameworks and cloud platforms such as AWS, Azure, or GCP.
Experienced in building and deploying AI agents or agent-based workflows, preferably with marketing or sales applications.
Knows event-driven distributed systems, containerization (Docker, Kubernetes), and data pipeline architectures.
Has familiarity with AI technologies like RAG, embeddings, vector databases, and enterprise security or data governance in production environments.