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Remote role with broad full-stack plus LLM deployment requirements raises candidate competition moderately.
Specialized LLM, cloud, and customer-facing deployment skills reduce transferability across unrelated industries.
Requires 7+ years, mandatory GCP certification, and specific LLM deployment experience, tightening shortlisting filters.
Drive end-to-end technical delivery of complex AI deployments including prototyping, building, and production rollout with measurable adoption and workflow impact.
Collaborate closely with Sales, Engineering, Product, and other internal teams to identify opportunities, design agentic solutions, and shape stakeholder and customer experiences.
Own hands-on coding (60%+) and technical scoping while balancing trade-offs across scope, speed, and quality, ensuring delivery and facilitating adoption at multiple organizational levels including CXOs.
5+ years working with Google Cloud Platform (GCP) or Azure/AWS; professional GCP certification is mandatory.
7+ years of engineering or technical deployment experience involving customer or stakeholder-facing roles.
Proven experience designing and deploying scalable solutions on GCP preferred; hands-on coding skills in Python, JavaScript, or comparable stacks required.
Experience building or deploying systems powered by large language models or generative AI; understanding of model impact on product experience required.
Experienced in fast-paced, ambiguous environments, able to drive solutions from ambiguity to operational simplicity and make runtime adjustments without impacting customer experience.
Strategic thinker with architectural mindset familiar with AI-driven business workflows; capable of influencing and working with leadership up to CXO level.
Strong operational execution skills with a full-stack technical approach, combining hands-on development skills and ability to codify working patterns for scalability and repeatability.