Business Systems - Systems Analyst(PM) Job 388-1

What You Will Be Doing

• Closely work with engineering and product management to deliver and drive strategic roadmap execution
• Collaborate with engineering on sprint planning, stand ups, sprint review and retrospective
• Use Jira dashboard and bug database queries to help with various reporting
• Work closely with the engineering team on various KPIs to improve overall execution process and deliverable
• Integral member of Vision AI development and productization workflow
• Facilitate clear communication channels between all stakeholders and members of the leadership to align project goals and resolve dependencies proactively

What We Need To See

• Bachelors in Electrical Engineering or Computer Science or equivalent experience
• 6+ years of end-to-end Program Management experience in a similar or related role
• Excellent verbal, written, interpersonal and presentation skills
• Proficient in Agile project management methodologies
• Experience with Atlassian suite (e.g., Jira, Confluence) to the point that you can comfortably guide an engineering team on how to use these tools and implement in an agile, scrum manner
• Proven track record of being well organized, detail oriented, have excellent listening skills, in the fast paced, high-uncertainty environment, adapting quickly to rapid breakthroughs and amidst technical volatility
• Able to think long-term and build consensus to make programs successful
• Outstanding skills in prioritizing and building alignment

Ways to Stand Out from the Crowd

• Program Management experience with Vision AI or AI application development including data acquisition and labeling to model training, optimization, and edge deployment
• Strong understanding of Embedded Systems (familiarity with Nvidia GPUs is a plus)
• Deep understanding of Software Product Life Cycle to develop production grade AI applications
• AI adoption in Program Management to optimize workflows and increase team velocity
• Experience managing the unique challenges of AI programs, such as, model accuracy KPIs, and "human-in-the-loop" validation processes