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Protocol Intelligence
Data-driven signals on your job's competitivenessStrong employer brand, popular ML/AI domain, broad required skillset, and likely metro hiring increase applicant competition.
Requires deep GenAI, LLM, and production ML experience, so candidates from other domains have low transferability.
Multiple explicit years requirements and many mandatory GenAI, cloud, and framework skills make shortlisting highly strict.
Job Description
Structured overview of role & requirementsAbout This Role
Design and develop AI-driven, cloud-native applications and intelligent automation workflows using Python, SQL/NoSQL databases, and cloud platforms (Azure/GCP/AWS).
Build, integrate, test, and deploy enterprise-grade GenAI, Agentic AI, LLM, and RAG-based solutions to improve operational accuracy and reduce manual effort.
Collaborate with stakeholders and engineering teams to translate requirements into scalable, secure, production-ready solutions ensuring code quality, CI/CD, testing, and compliance with AI governance standards.
Minimum Requirements
Graduate degree or equivalent experience.
10+ years overall professional experience in software engineering, cloud application development, automation, or AI solution delivery.
5+ years hands-on experience with .NET, Python, SQL, and enterprise application development.
4+ years hands-on experience delivering AI projects involving Agentic AI, LLM, GenAI, or RAG in production; experience with Azure and/or GCP cloud platforms.
Ideal Candidate Profile
Experienced in full lifecycle delivery of enterprise AI/ML, automation, and cloud-native solutions with strong engineering fundamentals including APIs, microservices, and secure development.
Proficient in using AI engineering tools like GitHub Copilot and AI frameworks such as LangGraph, LangChain, and knowledge of embedding/vector DB technologies.
Able to operate effectively in large, complex organizations collaborating cross-functionally and ensuring compliance with enterprise AI governance and delivery standards.