We're hiring an exceptional Applied AI Scientist to join our team!
In this role, you'll design and deploy enterprise-grade AI agents that drive real business impact across core functions – Sales, Marketing, Customer Success, Customer Support, Risk, and Finance. You'll be building agentic systems that execute complex, multi-step business workflows end-to-end. The ideal candidate is a hands-on builder with deep AI expertise who thrives on turning complex business problems into reliable, production-grade AI systems.
In This Role, You Will Be Responsible For:
Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions – including lead qualification and outreach (Sales & Marketing), churn reduction(Customer Success), and Ticket deflection (Support).
Agentic Architecture & Orchestration: Owning the end-to-end agent stack – from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails, and audit trails suited for an enterprise fintech environment.
Knowledge Systems: Building and maintaining RAG pipelines that ground agents in proprietary knowledge – product documentation, customer data, financial records, and internal playbooks – using vector databases, hybrid search, and re-ranking.
Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact – then iterating on agent behavior based on real usage data and stakeholder feedback.
Cross-Functional Collaboration: Partnering with stakeholders across the company to define agentic use cases, translate business requirements into technical features, and deliver products that create measurable ROI – from data preprocessing through product deployment.
In this role, you'll design and deploy enterprise-grade AI agents that drive real business impact across core functions – Sales, Marketing, Customer Success, Customer Support, Risk, and Finance. You'll be building agentic systems that execute complex, multi-step business workflows end-to-end. The ideal candidate is a hands-on builder with deep AI expertise who thrives on turning complex business problems into reliable, production-grade AI systems.
In This Role, You Will Be Responsible For:
Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions – including lead qualification and outreach (Sales & Marketing), churn reduction(Customer Success), and Ticket deflection (Support).
Agentic Architecture & Orchestration: Owning the end-to-end agent stack – from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails, and audit trails suited for an enterprise fintech environment.
Knowledge Systems: Building and maintaining RAG pipelines that ground agents in proprietary knowledge – product documentation, customer data, financial records, and internal playbooks – using vector databases, hybrid search, and re-ranking.
Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact – then iterating on agent behavior based on real usage data and stakeholder feedback.
Cross-Functional Collaboration: Partnering with stakeholders across the company to define agentic use cases, translate business requirements into technical features, and deliver products that create measurable ROI – from data preprocessing through product deployment.
Requirements:
Bachelors degree in Computer Science, Engineering or a related field, with focus on AI.
3+ years of hands-on experience in AI/ML engineering, ideally within the fintech industry or a related sector, with a track record of deploying AI agents or agentic workflows in production
Proficiency in Python and SQL for data manipulation, analysis, and AI system building.
Deep experience with LLMs and prompt engineering, including systematic evaluation of enterprise AI solutions
Experience with building RAG systems and Conversational chatbots – Advantage
Experience with cloud platforms (AWS preferred) for deployment and AI-Ops practices.
Analytical Mindset: You bring strong statistical reasoning and business acumen, with the ability to critically assess AI solutions and their real-world impact.
Project Management: You can manage and prioritize multiple tasks, balancing short-term and long-term goals to deliver timely, high-impact results.
Bachelors degree in Computer Science, Engineering or a related field, with focus on AI.
3+ years of hands-on experience in AI/ML engineering, ideally within the fintech industry or a related sector, with a track record of deploying AI agents or agentic workflows in production
Proficiency in Python and SQL for data manipulation, analysis, and AI system building.
Deep experience with LLMs and prompt engineering, including systematic evaluation of enterprise AI solutions
Experience with building RAG systems and Conversational chatbots – Advantage
Experience with cloud platforms (AWS preferred) for deployment and AI-Ops practices.
Analytical Mindset: You bring strong statistical reasoning and business acumen, with the ability to critically assess AI solutions and their real-world impact.
Project Management: You can manage and prioritize multiple tasks, balancing short-term and long-term goals to deliver timely, high-impact results.
This position is open to all candidates.
