Cotiviti is seeking an experienced Manager, Engineering- AI to lead their data engineering team. The role involves overseeing the development of data architecture and engineering strategies leveraging AI, while providing guidance and support to team members.
Responsibilities:
- Will quickly possess an understanding of Cotiviti and is adept at working across organizational boundaries partnering with Business Leads and Functional Product Managers while maintaining a strategic perspective regarding IT architecture and business needs
- Drive, develop, and implement a data engineering architecture leveraging AI to ensure alignment with company performance objectives
- Drive, develop and implement templates, reference architectures and patterns with respect to implementing modern data engineering architecture pipelines connecting data sources on prem and within the cloud
- Partner with Architecture and Product teams and contribute to the data product strategy, enhance data literacy of the several data assets within Cotiviti
- Stay on top of the AI trends to ensure that we are leveraging them to ensure data engineering team efficiency, productivity and architectural relevance
- Responsible for managing internal stakeholders and speaking with the client on behalf of the organization as needed
- Responsible for managing and evaluating staff performance for professional development of the staff members to include: conducting objective-setting goals, coaching, assessment, and mentoring activities
- The Manager will have significant latitude in defining results, selecting alternatives, and taking action across a range of products
- Will have primary knowledge, control, and influence of IT decisions for his/her area of responsibility, including optimizing service costs through a mix of internal and external resources for all aspects of development
- Working with the HIPAA Privacy and Security Officer and HIPAA Security Compliance team, ensuring all information systems and networks operate according to internal standards, external accrediting agency standards, regulatory agencies and legal requirements. In coordination with key personnel, develop and implement the following plans: disaster plan, emergency mode operation plan, backup plan, physical security plan, personnel security plan, access policies, and others. Ensure each plan is tested and revise plans as necessary to ensure data integrity, confidentiality, and availability
- Hire, develop, coach, lead and retain top-tier talent, with a focus on building and improving a team and culture that is able to assist in employing best in class practices to support and drive high levels of internal and external customer satisfaction
- Complete all responsibilities as outlined in the annual performance review and/or goal setting
- Complete all special projects and other duties as assigned
- Must be able to perform duties with or without reasonable accommodation
Requirements:
- Bachelor's degree or equivalent work experience
- 7+ years of total data engineering/IT/Project Management experience out of which at least 2 years must be management experience
- 2+ years' experience leading small to mid-size projects through application of Project Management methodologies and artifacts
- 4+ years' experience with data sets, Hadoop, Spark and/or other data integration/ETL tools like databricks, AWS tech stack, snowflake etc
- 2+ years of experience working on AI engineering concepts and tools like RAG, Prompt Engineering, Langchain, LangGraph etc
- Familiarity with ML Ops and LLM Ops capabilities and tools like Datarobot
- 2+ years of hands-on experience in software development and database management
- Proficiency in Microsoft Office Suite
- Experience with healthcare data preferably in a data operations role
- Experience working in an Agile environment