A role focused on developing and deploying advanced AI solutions, including predictive models and autonomous agents, within the Finance domain of a SaaS company, requiring end-to-end engineering expertise and collaboration with cross-functional teams.
Key Responsibilities
Partner with product owners and finance experts to identify AI use cases in Accounts Receivable
Design and develop predictive models, generative AI features, and multi-agent systems for business problems
Build LLM-based copilots and autonomous agents with human-in-loop flows, security guardrails, and audit trails
Collaborate with software engineers and data scientists to integrate AI features into the product
Develop and maintain secure, scalable MLOps pipelines for training, deployment, and monitoring of AI models
Evaluate and improve model performance and user impact continuously
Requirements
7 years of AI ML engineering experience.
3 years of hands-on experience with LLM-based solutions.
1 year of experience building agentic systems that are production-ready, not POCs.
Strong understanding of multi-agent architectures, memory systems, tool-use, orchestration, routing, and safety guardrails.
Experience building autonomous or semi-autonomous agents with governance, logging, and human-in-loop flows.
Strong programming skills in Python preferred, R, or Java.
Experience with AI ML frameworks such as TensorFlow, PyTorch, and scikit-learn.
Solid understanding of predictive modeling, NLP, ML algorithms, and statistics.
Experience working in cloud environments such as AWS, Azure, or GCP with model deployment and data pipelines.
Knowledge of GitHub, GitLab, version control, and CI/CD practices.
Basic understanding of web fundamentals including HTTP, JSON, authentication, and REST APIs to integrate AI LLM solutions into the product.
Strong analytical and problem-solving skills.
Ability to communicate complex concepts clearly to non-technical partners.
Great collaboration and teamwork abilities.
Benefits & Perks
generous PTO
hybrid working options
company equity RSUs
comprehensive benefits
extensive parental leave
dedicated volunteer days
access to resources such as gym subsidies, counseling, and well-being programs
benefit from clear career paths, internal mobility, a dedicated learning program, and mentorship opportunities
connect and belong through inclusion and belonging programs
opportunity to work with a leading process mining technology
international team collaboration
empowered environment with open culture and autonomous teams
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