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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 brand, mid-level generalist AI title, metro location, and broad skill requirements create high competition.
Medium — core LLM, MLOps, and cloud skills transfer across industries, but GCP/vertex and code-translation specifics raise moderate domain bias.
High due to explicit 4–7 years requirement, mandatory cloud/AI certification, and specific GCP/LLM/MLOps skills.
Job Description
Structured overview of role & requirementsAbout This Role
Architect, build, and deploy production-grade AI products automating complex engineering workflows and accelerating software transformation.
Design intelligent systems leveraging NLP and LLMs to modernize legacy codebases and technical documentation.
Build scalable AI microservices on Google Cloud Platform managing cost and performance optimization.
Minimum Requirements
4 to 7 years of hands-on experience in end-to-end AI/ML product development including generative AI and software automation systems.
Bachelor's or Master's degree in Computer Science, AI, Data Science, Software Engineering, or related quantitative field.
At least one recognized cloud or AI certification (e.g., Google Cloud Professional Machine Learning Engineer).
Strong expertise in Google Cloud Platform (GCP) services including Vertex AI, Cloud Run, BigQuery, Cloud Functions, and GKE.
Ideal Candidate Profile
Experienced in designing and deploying AI solutions in complex enterprise environments with measurable impact on automation and cost efficiency.
Proficient in generative AI, LLM frameworks, prompt engineering, MLOps, and AI cost monitoring/FinOps on GCP.
Skilled in cross-functional collaboration to translate complex requirements into scalable AI products, with strong emphasis on quality, scalability, and innovation.