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Genesys

Principal Applied AI Engineer, Finance

Genesys

Principal Applied AI Engineer leading design and delivery of AI systems transforming financial decision-making. Overseeing advanced predictive models and software engineering practices in finance context.

Posted 5/20/2026full-timeRemote • Maine, Massachusetts, Montana, New York, Rhode Island • 🇺🇸 United StatesLead💰 $193,600 - $340,600 per yearWebsite

Tech Stack

Tools & technologies
AWSCloudDistributed SystemsDockerKubernetesPython

About the role

Key responsibilities & impact
  • Architect and lead the development of agentic AI systems that automate and augment finance workflows.
  • Design and implement multi-agent systems leveraging LLMs, tool-use frameworks, and orchestration patterns.
  • 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.
  • 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.
  • Design and build scalable AI/ML systems with a strong emphasis on software engineering best practices.
  • Develop and integrate AI services into internal applications and workflows.

Requirements

What you’ll need
  • 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.

Benefits

Comp & perks
  • 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

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools
predictive modelingtime series forecastingcustomer churn modelingPythonML frameworksAI frameworksprompt engineeringfine-tuningAPI developmentcontainerization
Soft Skills
leadershipcommunicationorganizational skillsproblem-solvingcollaboration