Genesys

Principal Applied AI Engineer, Finance

Genesys$193K — $340K *
Finance & Insurance
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 8+ years of experience in data science, software engineering, and AI engineering with a focus on production systems.
  • Proven track record of building scalable production AI systems.
  • Deep expertise in predictive modeling, particularly time series forecasting and customer churn modeling.
  • Advanced proficiency in Python and experience with ML/AI frameworks and system design.
  • Hands-on experience with LLMs involving prompt engineering and evaluation.
  • Strong familiarity with cloud platforms (preferably AWS), distributed systems, and MLOps practices.
  • Experience in financial data modeling with compliance awareness.
  • Solid software engineering foundation in API development and CI/CD pipelines.

Responsibilities

  • Lead the development of agentic AI systems that enhance financial workflows like forecasting and decision support.
  • Design multi-agent systems using LLMs and related orchestration frameworks.
  • Translate advanced AI research into scalable production solutions.
  • Establish best practices for responsible AI ensuring safety and compliance in outputs.
  • Design robust agent systems with built-in failure recovery strategies.
  • Implement predictive models for customer behavior and financial planning.
  • Drive adoption of modern tooling for scalable AI/ML system development.

Benefits

  • Medical, Dental, and Vision Insurance.
  • Telehealth coverage.
  • Flexible work schedules and remote work opportunities.
  • Professional development and career growth opportunities.
  • Open Time Off plus 10 paid holidays.
  • 401(k) matching program.
  • Adoption Assistance and Fertility treatments.
Full Job Description
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 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.
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

About Genesys

Genesys is a cloud-based customer experience and call center solution provider. The company was founded in 1990 and is headquartered in Daly City, California. Genesys provides customer experience solutions that include contact center and workforce optimization software, as well as analytics and artificial intelligence capabilities. The company serves a variety of industries, including banking, healthcare, insurance, and telecommunications. Genesys has more than 10,000 customers in over 100 countries.
Learn more about Genesys
Size
5,000 employees
Industry
Founded
1990

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