AppZen delivers the world’s leading AI platform for modern finance teams. Starting with business spend, we automate manual process, uncover problems, and optimize decision making for enterprises around the globe, including one-fourth of the Fortune 500. Our platform combines patented deep learning, computer vision, and semantic analysis with intelligence from thousands of online data sources to understand financial transactions in business context and make decisions before those transactions happen. AppZen is a must have for CFOs and their teams to reduce spend, achieve compliance, and streamline process.
We’ve taken off this year! Since we released our platform in 2016, over 1,500 enterprises have standardized on AppZen, including three of the top ten banks, four of the top ten media companies, three of the top ten pharmaceutical manufacturers, two of the top five aerospace companies, and five of the top ten software providers. We were a Gartner Cool Vendor last year, have been recognized as one of the fastest-growing technology companies in the market, and we just announced $50 million in Series C funding.
As a hands-on engineering leader for AI & ML Engineering you will lead, manage, and inspire engineering teams developing next-generation AI platforms and infrastructure. You will guide architecture, design, and delivery of complex distributed software and systems. You are passionate about solving technical challenges while delivering incredible customer value powered by our leading AI Platform.
- Build, grow, and retain top talent globally by inspiring, challenging, and mentoring the engineering organization
- Lead professional development to build experts in current technologies and become notable authorities in the industry
- Be a champion for AI/ML vision and its effect on productivity, scalability, and efficiency for data science
- Create overall technical strategy that compliments key technologies, needs, and opportunities that drive customer value
- Continuously develop and report on critical engineering and business success metrics
- Interact with engineering and cross functional stakeholders to assess priorities and strategic needs for the organization
- Define and manage roadmaps for software and infrastructure development
- Identify, create, and execute high impact projects and bring to a successful conclusion
- Improve scaling and tooling
- Triage external requests
Skills and Requirements:
- BS/MS in Computer Engineering or Computer Science
- 10+ years of experience leading globally distributed, highly-technical teams in both solid-line and matrixed environments
- Practical understanding or hands on experience in Machine Learning models, tools, and libraries such as such as pandas, numpy, scikit-learn, and keras in a production environment
- Experience in real-time execution of machine learning models, and the scale concerns of such systems
- Experience in building complex, real-time software systems involving data and machine learning
- Excellent written and verbal communication skills in a technical and non-technical environment
- Ability to rapidly prototype and evaluate customer applications and interaction methodologies
- Solid understanding of standard methodologies for architecture design, solution development, and enterprise implementations based on leading frameworks and platforms
- Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Knowledge in large scale data systems, offline batch processing, online stream processing and queueing systems