Principal Applied AI Engineer, Finance

Reposted Yesterday
35 Locations
In-Office or Remote
194K-341K Annually
Senior level
Artificial Intelligence • Big Data • Cloud • Machine Learning • Software
The Role
The Principal Applied AI Engineer will lead the design of AI systems for finance, focusing on predictive modeling, intelligent automation, and software engineering best practices. They will oversee AI initiatives, mentor technical teams, and ensure compliance with financial standards and practices.
Summary Generated by Built In

Genesys empowers organizations of all sizes to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Genesys Cloud, the AI-powered Experience Orchestration platform, organizations can accelerate growth by delivering empathetic, personalized experiences at scale to drive customer loyalty, workforce engagement, efficiency and operational improvements.

We employ more than 6,000 people across the globe who embrace empathy and cultivate collaboration to succeed. And, while we offer great benefits and perks like larger tech companies, our employees have the independence to make a larger impact on the company and take ownership of their work. Join the team and create the future of customer experience together.

Principal Applied AI Engineer, Finance

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.

The ideal candidate is both a strategic technical leader and hands-on builder—capable of architecting complex AI systems with a software engineering mindset, influencing organizational direction, and delivering measurable business impact. You will drive innovation in Generative AI, lead the evolution toward agentic AI systems, and establish best practices across modeling, deployment, and governance in a finance context.

Key ResponsibilitiesAgentic 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.

Key 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.

  • 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.

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.


Compensation:

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location. This role might also be eligible for a commission or performance-based bonus opportunities.  

$193,600.00 - $340,600.00

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

Click here to view a summary overview of our Benefits.

If a Genesys employee referred you, please use the link they sent you to apply.

About Genesys:

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. To learn more, visit www.genesys.com.

Reasonable Accommodations:

If you require a reasonable accommodation to complete any part of the application process, or are limited in your ability to access or use this online application and need an alternative method for applying, you or someone you know may contact us at [email protected].

You can expect a response within 24–48 hours. To help us provide the best support, click the email link above to open a pre-filled message and complete the requested information before sending. If you have any questions, please include them in your email.

This email is intended to support job seekers requesting accommodations. Messages unrelated to accommodation—such as application follow-ups or resume submissions—may not receive a response.

Genesys is an equal opportunity employer committed to fairness in the workplace. We evaluate qualified applicants without regard to race, color, age, religion, sex, sexual orientation, gender identity or expression, marital status, domestic partner status, national origin, genetics, disability, military and veteran status, and other protected characteristics.

Please note that recruiters will never ask for sensitive personal or financial information during the application phase.

Skills Required

  • 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

Genesys Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Genesys and has not been reviewed or approved by Genesys.

  • Strong & Reliable Incentives Annual bonuses are described as consistently funded and meaningful, elevating total compensation. Structured variable pay and regular payouts reinforce confidence in incentives across numerous roles.
  • Leave & Time Off Breadth Open (unlimited) PTO, volunteer time off, and company recharge days create flexible time-away options. Remote-friendly policies and occasional holiday shutdowns add to the sense of generous time off.
  • Parental & Family Support Paid parental leave with no waiting period, fertility support, and adoption assistance signal strong family-oriented benefits. These offerings stand out as modern and comprehensive within the package.

Genesys Insights

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The Company
HQ: Daly City, CA
6,774 Employees
Year Founded: 1990

What We Do

Every year, Genesys® delivers more than 70 billion remarkable customer experiences for organizations in over 100 countries. Through the power of the cloud and AI, our technology connects every customer moment across marketing, sales and service on any channel, while also improving employee experiences. Genesys pioneered Experience as a Service℠ so organizations of any size can provide true personalization at scale, interact with empathy, and foster customer trust and loyalty. This is enabled by Genesys Cloud™, an all-in-one solution and the world’s leading public cloud contact center platform, designed for rapid innovation, scalability and flexibility. Visit www.genesys.com.

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