Principal Applied AI Engineer, Finance

About the role

We are seeking a Principal Applied AI Engineer to lead the design and delivery of next-generation AI and predictive models that transform financial decision-making at scale. This role sits at the intersection of advanced machine learning, agentic AI, and software engineering, with a strong focus on production-grade AI systems, intelligent automation, and predictive modeling.

Responsibilities

• Agentic AI & Generative Systems Architect and lead the development of agentic AI systems that automate and augment finance workflows (e.g., forecasting, reporting, and 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 to ensure 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.

Qualifications

• 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.
• 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.

What Sets You Apart

• 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
Paid volunteer time
August Free Fridays
Well-being resources and regionally tailored programs for employees and their families
Great Place to Work® certification in 17 countries and 94% of employees proud to work at Genesys