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# Senior GCP ML Engineer

- **Company:** OpenKyber LLC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Computing, Data Validation, Software Product Management, Software Safety, Google Cloud, Large Language Models, Prompt Engineering, Generative AI, Information Technology, Machine Learning Operations
- **Published:** May 13, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=cb95d33700685842

## About the Role

Do you have experience in MLOps?, * Bachelor's degree in Engineering, Computer Science, or equivalent

 * 10 15 years of experience with significant product management exposure
 * 5 + yr Experience leading large-scale AI/ML or cloud-based product initiatives
 * 5 + yrs Strong understanding of LLMs, agentic systems, RAG pipelines, and MLOps
 * 5 + yrs Ability to engage deeply with engineering teams on technical topics
 * Strong communication skills for technical and non-technical stakeholders
 * Experience working in fast-paced, cross-functional environments
 * Strong analytical and data-driven decision-making skills
 * Proven ability to influence without direct authority

Nice to Have:

 * Experience working with enterprise-scale production environments
 * Familiarity with observability and incident management tools
 * Experience in prompt engineering and LLM evaluation frameworks
 * Exposure to AI safety, governance, and compliance standards
 * Prior experience mentoring product managers or leading product communities
 * Knowledge of cloud platforms such as AWS or Google Cloud in AI contexts

## Description

Job Description: About Your Role: As an AI Product Manager, you will define the strategy, roadmap, and execution for Generative AI agentic solutions. Your mission is to reduce risk and cost in complex production environments by translating operational challenges into innovative AI-driven solutions. You will collaborate with engineering, production support, and application teams to deliver high-impact, reliable, and safe AI products.
Day to Day Job Duties:

 * Define product vision, strategy, and roadmap for agentic AI systems
 * Translate user pain points into product requirements, user stories, and success metrics
 * Lead end-to-end lifecycle for LLM-based products from discovery to iteration
 * Establish evaluation frameworks for LLMs and prioritize RAG pipelines, prompt engineering, and validation loops
 * Drive integrations with observability, incident management, and deployment systems
 * Conduct user research and translate production challenges into roadmap priorities
 * Own AI safety, governance, reliability, and fallback strategies
 * Define and monitor KPIs such as cost, latency, and user satisfaction
 * Own data and knowledge strategy including RAG pipeline and data validation
 * Lead product design reviews and promote data-driven experimentation
 * Mentor teams on AI product management and best practices


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