Principal Applied AI Engineer, Finance

Genesys® empowers more than 8,000 organizations worldwide to create the best customer and employee experiences. With agentic AI at its core, Genesys Cloud™ is the AI-Powered Experience Orchestration platform that connects people, systems, data and AI across the enterprise. As a result, organizations can drive customer loyalty, growth and retention while increasing operational efficiency and teamwork across human and AI workforces. Genesys is Great Place to Work® certified in 17 countries, with 94% of employees proud to work there. To learn more, visit www.genesys.com.

Introduction

Genesys is looking for a Principal Applied AI Engineer to lead the design and delivery of next-generation AI and predictive models that will transform financial decision-making at scale. This role merges advanced machine learning, agentic AI, and software engineering, focusing on production-grade AI systems, intelligent automation, and predictive modeling within a finance context.

Genesys empowers over 8,000 organizations worldwide to create superior customer and employee experiences using its AI-Powered Experience Orchestration platform, Genesys Cloud™. Join us in moving AI from possibility to production in real-world enterprise environments.

Responsibilities

Agentic AI & Generative Systems

• Architect and lead the development of agentic AI systems to automate and augment finance workflows (e.g., forecasting, reporting, decision support).
• Design and implement multi-agent systems leveraging LLMs, tool-use frameworks, and orchestration patterns (e.g., RAG, model chaining, dynamic prompting).
• Translate cutting-edge research in LLMs and agentic AI into scalable, production-ready solutions.
• Establish guardrails, evaluation frameworks, and responsible AI practices for safe, compliant, and reliable outputs.
• Design fault-tolerant, observable agent systems with clear failure modes and recovery strategies.

Predictive Modeling & Customer Behavior Forecasting

• Lead the design and implementation of advanced predictive models, including time series forecasting and attrition prediction across customer segments.
• Develop interpretable, production-grade models that drive retention strategies and financial planning.
• Define and standardize evaluation metrics, validation frameworks, and monitoring systems for model performance and drift detection.
• Translate complex predictive insights into actionable recommendations for finance and business leaders.

Software Engineering & AI System Architecture

• Design and build scalable AI/ML systems with a strong emphasis on software engineering best practices (modular design, APIs, CI/CD, testing).
• Lead end-to-end development from concept to production, ensuring robustness, scalability, and maintainability.
• Develop and integrate AI services into internal applications and workflows, including light front-end/back-end components where needed.
• Drive adoption of modern tooling (e.g., containerization, orchestration, cloud-native architectures).

Operationalization & Model Lifecycle Leadership

• Establish and enforce MLOps best practices for deployment, monitoring, retraining, and governance of AI systems.
• Ensure systems meet enterprise standards for security, compliance (e.g., SOX), and auditability.
• Develop advanced feature engineering strategies capturing behavioral, financial, and temporal signals.

Technical Leadership & Strategy

• Set technical direction for AI/ML initiatives across the finance organization.
• Lead complex, cross-functional projects and mentor other data specialists.
• Work alongside stakeholders across finance, IT, and product to adopt AI-driven solutions.
• Contribute to long-term AI strategy, identifying opportunities to drive efficiency and innovation.

Requirements

• 8+ years of experience in data science, software engineering, and AI engineering, with significant experience deploying production systems.
• Proven track record of building production AI systems used at scale.
• Deep expertise in predictive modeling, including time series forecasting and customer churn modeling.
• Advanced proficiency in Python and strong experience with ML/AI frameworks and system design.
• Hands-on experience with LLMs, including prompt engineering, fine-tuning, and evaluation techniques.
• Strong experience with cloud platforms (preferably AWS), distributed systems, and MLOps practices.
• Experience working with financial data and compliance-aware modeling.
• Strong software engineering foundation, including API development, containerization (Docker/Kubernetes), and CI/CD pipelines.

Nice to Have

• Expertise in building production agentic AI frameworks, including multi-agent orchestration, tool-using agents, and autonomous workflows.
• Experience building RAG-based systems, vector databases, and semantic search architectures.
• Demonstrated ability to lead large-scale AI initiatives and influence technical strategy.
• Deep understanding of responsible AI practices, including model alignment, guardrails, and bias mitigation.
• Exceptional communication skills, with the ability to translate complex technical concepts into business value.
• Track record of mentoring and elevating technical teams in high-impact environments.

Benefits

• Medical, Dental, and Vision Insurance.
• Telehealth coverage.
• Flexible work schedules and work-from-home opportunities.
• Development and career growth opportunities.
• Open Time Off in addition to 10 paid holidays.
• 401(k) matching program.
• Adoption Assistance.
• Fertility treatments.

About Company

Genesys® empowers more than 8,000 organizations worldwide to create the best customer and employee experiences. With agentic AI at its core, Genesys Cloud™ is the AI-Powered Experience Orchestration platform that connects people, systems, data, and AI across the enterprise. This helps organizations drive customer loyalty, growth, and retention while increasing operational efficiency and teamwork across human and AI workforces. Genesys is Great Place to Work® certified in 17 countries, with 94% of employees proud to work there.

How to Apply

After applying, the Talent Acquisition team will review your application. If your background aligns with the role, a Talent Acquisition Partner will schedule a Zoom interview. You will then meet the hiring manager and other interview team members. The process typically involves no more than five interviews. The team will follow up with final steps after interviews are complete. Every application is reviewed by a person. Response times may vary, but you will be kept informed throughout the process.