Responsibilities
- Lead the development of technology and platform for the company's AI/ML engineering needs, ensuring functional richness, reliability, performance, and flexibility.
- Design the architecture and lead the implementation of AI/ML infrastructure, platform, and services.
- Challenge the status quo to drive better technical solutions in the broad risk area of Wex.
- Guide your team to leverage data and AI tools for high productivity and quality, demonstrating thought leadership.
- Partner with senior engineers across Wex to understand business needs and develop effective technical solutions.
- Collaborate with information security teams to ensure data security and privacy.
- Work with solutions architecture and LOB teams on integrations of AI/ML platforms, ensuring reliable execution.
- Engage with external partners to evaluate complementary technologies and services.
- Create and manage roadmaps, project plans, and commitments.
- Report on development, quality, operations, and system performance to management.
- Drive the technical vision and strategy for AI/ML infrastructure aligned with business needs, in partnership with Data Science, ML Engineering, and operations teams.
- Set high standards, provide technical guidance, training, and mentorship to engineering teams, fostering a culture of continuous learning and innovation.
- Establish clear, measurable quality goals using data-driven approaches.
- Partner with security and SRE teams to meet security requirements, SLOs, and error budgets.
- Take financial responsibility for your team.
- Ensure accountability for delivering quality results through OKRs.
- Advise senior leadership on complex issues and lead teams through initiatives to achieve organizational OKRs.
- Provide strategic technical leadership on business initiatives using deep industry and technical expertise.
Qualifications & Experience
- Deep technical leadership in software engineering with the ability to meet business needs.
- 15-20 years of experience in large-scale software design and development.
- Strong skills in chosen programming languages with willingness to learn Java and Python.
- Experience in building supervised and unsupervised machine learning models; reinforcement learning experience is a plus.
- Experience with LLM models is advantageous.
- Broad understanding of distributed computing frameworks like Ray and Spark.
- Hands-on experience with Kubernetes and Terraform.
- Experience with Sagemaker is a plus.
- Comprehensive understanding of cloud architecture tools (S3, EMR, Kubernetes, Lambda) with AWS and Azure experience preferred.
- Deep technical expertise in architecture, deployment, and production operations; familiar with agile development and best practices.
- Extensive experience with Big Data, large-scale data platforms, AI, and ML.
- Strong expertise in CI/CD automation.
- Leadership experience in engineering and agile practices.
- Excellent analytical and problem-solving skills.
- Understanding of payment organizations is a plus.
- Mentorship skills for contributors at various levels.
- Ability to promote transparency and visibility across teams.
- Strong communication skills.
- Commitment to continuous improvement.
- Bachelor's degree in Computer Science or related field; higher degrees are a plus.
Leadership & Personal Characteristics
- Collaborative, engaging leadership style with good listening skills, humility, empathy, and transparency.
- Advocate for high standards, progress, and ethical integrity.
- Ability to operate effectively in a fast-paced, entrepreneurial environment.
- Effective communicator capable of articulating a compelling vision.
- High intellectual curiosity and learning agility.
- Skilled in driving change through influence and managing stakeholders in complex environments.
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