Senior Manager, AI & Data Platform

We believe small businesses are at the heart of our communities, and championing them is worth fighting for. We empower small business owners to manage their finances fearlessly, by offering the simplest, all-in-one financial management solution they can't live without.

About the RoleThe Senior Manager, AI and Data Platform is a leader with deep expertise in data platforms, DataOps, and AI/ML infrastructure. This role is accountable for ensuring the reliable and efficient operation of both data and AI systems at Wave, with a focus on maintaining secure, scalable platforms that meet the evolving needs of the business. They will manage a team of Data Engineers and ML Engineers, driving the development, deployment, and monitoring of AI models and a modern CDC-based data stack, while also implementing DataOps practices to streamline and automate data workflows. Additionally, this role includes oversight of data and AI operations, ensuring that models perform optimally and that our infrastructure remains robust and future-proof.

Here’s How You Make an Impact:

• AI and Data Platform Evolution: Lead the development and optimization of a secure, scalable AI and data platform that supports Wave’s growth, managing data ingestion, our data lake, and AI/ML infrastructure on AWS.
• DataOps Implementation: Lead the adoption and integration of DataOps practices to automate and optimize data workflows, ensuring data quality, lineage, and availability across the platform. Align DataOps with AI/ML initiatives to support continuous improvement and scalability.
• Architectural Oversight: Continuously evolve Wave’s data, DataOps and AI/ML architecture by reviewing, recommending, and implementing changes, integrating new tools, and ensuring thorough documentation.
• AI Model Management: Oversee the full lifecycle of ML models, including training, deployment, monitoring, and optimization, while managing our portfolio of generative AI applications.
• Collaboration and Partnership: Collaborate closely with internal technology partners (Compliance, Engineering, IT, Security) and external partners like AWS to align initiatives with organizational goals.
• Data and AI Integrity: Ensure data and AI model quality, lineage, and integrity across the platform through robust systems and processes.
• Governance and Compliance: Implement and maintain governance processes that address stakeholder needs, emphasizing security, transparency, and efficiency.
• Project Management: Lead the team in scoping, prioritizing, and executing data and AI projects, setting clear goals, tracking progress, and removing obstacles.
• Mentorship and Best Practices: Mentor the team in best practices for data engineering and AI/ML operations, conducting regular 1-on-1s, setting goals, and holding the team accountable.
• Stakeholder Management: Represent the team with confidence and transparency, managing relationships across all data and AI functions.

You Thrive Here By Possessing the Following:

• 7+ years in data and AI/ML, including 5+ years in data platform architecture (data pipelines, governance, and architecture).
• 5+ years managing teams of data and/or AI/ML professionals, with a track record of leading cross-functional teams and complex projects.
• Advanced SQL skills for querying large, complex datasets.
• Proficient in Python, with experience in data frame-based libraries (Pandas, Dask, Polars) and AI/ML libraries (TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of DataOps practices, including automated data pipelines, data quality monitoring, and CI/CD for data.
• Experienced with AWS services (S3, Redshift, RDS, DynamoDB, SageMaker).
• Strong understanding of distributed computing (Apache Spark) and hands-on experience with AWS Glue.
• Solid grasp of MLOps practices, including CI/CD for AI/ML and maintaining evolving data and AI system architectures.
• Familiar with data pipeline tools like Kafka, dbtCloud, Terraform, and Kubernetes.
• Expertise in DevOps and Infrastructure as Code (IaC) with Terraform HCL.
• Proven ability to collaborate with internal partners (Compliance, Engineering, IT, Security) and external partners (AWS) to align initiatives with organizational goals.
• Experienced in Agile team leadership using Scrum, with skills in sprint performance reporting, backlog grooming, and alignment with OKRs and KPIs.
• Success in setting, meeting, and exceeding quarterly OKRs, with consistent KPI reporting.
• Committed to mentoring through regular 1-on-1s, setting goals, and providing constructive feedback.
• Effective communicator, able to convey complex technical matters visually and verbally.
• Proactive, autonomous project manager with a strong ability to partner with business and engineering stakeholders from ideation to execution.

Nice to Have:

• Generative AI Expertise: Expertise in generative AI, including understanding key techniques and applications.
• RAG, LLM, and Agentic Patterns: Familiarity with Retrieval-Augmented Generation (RAG), Large Language Model (LLM) fine-tuning, and agentic GenAI patterns.
• AWS Bedrock and LangChain: Experience deploying and managing generative AI with AWS Bedrock, LangChain, or similar platforms.
• Data Privacy and Compliance: Experience implementing data privacy and compliance solutions, especially with AI Management Systems like ISO 42001.
• Third-Party Tools: Experience with Stitch, Segment, and integrating third-party data tools into platforms.
• Cross-Industry Experience: Knowledge or experience in Payroll, Banking, Fintech, Payments Processing, or Accounting industries where data and AI/ML are critical.
• Data Product Management: Experience managing data product lifecycles, including versioning, monitoring, and continuous improvement.