Enjins

AI Engineer

• Partner with C-level stakeholders to design AI roadmaps that aren't just 'projects,' but scalable technical assets that drive core business value.
• Ensure the long-term health of deployed solutions by implementing rigorous MLOps standards, keeping our 'engines' high-performing and maintainable.
• Lead the AI Engineering team alongside other Leads, fostering a culture of technical excellence and pragmatic innovation.
• Involve yourself in business-critical decisions on team growth, innovation roadmaps, and account management.
• Within 1 Month: Complete Enjins leadership onboarding and become a certified cloud practitioner.
• Within 3 Months: Own the technical roadmap for at least one client engagement, from architecture to production.
• Within 6 Months: Drive meaningful client velocity and build relationships with C-level stakeholders.

Lead AI Engineer

• Act as a hands-on engineer embedded within client teams, designing and deploying end-to-end AI/ML systems from proof-of-concept to production.
• Own a feature or deployment pipeline on client projects, demonstrating technical mastery and end-to-end responsibility.
• Spearhead the adoption of MLOps/LLMOps best practices - feature stores, model monitoring, pipeline orchestration — to ensure client systems are scalable and reliable.
• Collaborate with Data Scientists and Software Engineers to design and implement robust data pipelines and model APIs.
• Bridge the gap between data science and business value by translating technical findings into clear, actionable insights for non-technical stakeholders.
• Identify new tools, methods, and processes that work best — and share them with the team.
• Help in the interview process for additional AI Engineers joining Enjins' growing team.
• Have meaningfully accelerated your client's velocity.