
Senior GenAI Product Engineer
3 days ago
We are seeking a seasoned professional to drive GenAI project initiatives, leveraging technical leadership and hands-on product engineering expertise. This is a 12-month contract role with strong potential for extension and possible conversion to a permanent position.
About the Role:
This challenging role combines technical leadership (50%) with hands-on product engineering (50%), demanding strong expertise in full-stack development and Generative AI technologies.
The ideal candidate will possess excellent stakeholder management skills and maintain a strong focus on quality, compliance, and scalable solutions.
Key Responsibilities:
- Audit vendor GenAI solutions for architecture, code quality, scalability, and security.
- Lead design and development aligned with ethical AI standards and best practices.
- Conduct architecture reviews across GenAI and full-stack platforms.
- Define and implement engineering standards, tools, and frameworks regionally and globally.
- Establish GenAI QA processes and share key metrics with stakeholders.
- Mentor teams as a GenAI coach, promoting ethical AI and prompt engineering practices.
- Support vendor selection to integrate leading GenAI technologies.
- Drive end-to-end delivery with a focus on quality, timelines, and risk mitigation.
Required Skills and Qualifications:
- Generative AI Expertise: Experience with LLMs, prompt engineering, LLMOps, and frameworks such as LangChain or LangGraph.
- Architecture & Code Review: Ability to audit and assess vendor solutions for scalability, security, and quality.
- Ethical AI Practices: Familiarity with Responsible & Ethical AI design principles.
- DevOps & CI/CD: Experience with Git-based workflows, code reviews, and CI/CD pipelines.
- Leadership & Coaching: Proven ability to mentor cross-functional teams and advocate best practices.
- Stakeholder Management: Skilled in managing cross-regional stakeholders.
- Product Delivery: Capable of driving end-to-end solution delivery with risk mitigation.
- Cloud & Agile: Exposure to cloud platforms (AWS/Azure) and Agile/Scrum methodologies.
- Education: Bachelors in CS, IT, or related field; AI/ML coursework or specialization preferred.
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