Non-negotiable:
AGENTIC multi agent build
Must have built RAG and autonomous agents
Minimum Qualifications
- BS and MS in Computer Science, Software Engineering, or a related field; PhD in AI, ML, or a related domain strongly preferred.
- 15+ years of software engineering experience, with 5+ years of focused, hands-on work with Large Language Models (LLMs), Agentic AI, and generative AI systems.
- Demonstrated success leading the design, development, and deployment of production-grade AI/ML systems, including large-scale inference, context management, and continuous learning.
Technical Expertise
- Deep expertise in backend systems and distributed architecture; Python required; additional fluency in languages such as C#, C++, Go, or Rust are a plus.
- Extensive experience with agent frameworks, memory/contextual planning systems, and orchestration of long running, stateful agents
- Strong command of cloud-native development, microservices, and MLOps pipelines (e.g., with Azure, Google Cloud Platform, AWS).
- Architect-level skill in breaking down complex, emergent problems into scalable, modular, and maintainable systems.
- Applied experience integrating RLHF, embedding models, RAG (retrieval-augmented generation), and vector databases into modern applications.
PREFERRED SKILLS:
Fintech / e-commerce experience
Prior work with cloud-native MLOps (AWS, Google Cloud Platform, Azure)
Microservices and scalable AI infrastructure
Design and build intelligent, autonomous systems that directly enhance the customer experience, enabling AI-powered interactions, personalized repayment journeys, intelligent support agents, and the foundation for a new generation of AI-first products in a dynamic, regulated fintech environment.
Prototype quickly, scale deliberately, evaluating emerging frameworks and models, running experiments, and hardening the most promising approaches for production deployment in real-world financial systems.
Collaborate across engineering, product, design, compliance, and applied research to identify high-impact use cases and deliver intelligent systems that are resilient, secure, and deeply aligned with user needs.
Architect the AI foundation, selecting and integrating the right mix of LLMs, orchestration frameworks, vector databases, memory strategies, and tooling to give our agentic systems both intelligence and structure.
Champion and evangelize AI-powered engineering, establish and uphold best practices across performance, observability, scalability, and responsible AI, ensuring that everything we build operates with trust, regulatory compliance, and enterprise-grade reliability at scale.
Build fast and learn faster, operating with urgency, deploying frequently, and using real feedback from customers and stakeholders to iterate and improve continuously.
Stay at the frontier of agentic AI, tracking new developments across academia and industry, and selectively introducing promising techniques that align with our mission to deliver intelligent, adaptive, and customer-centric fintech experiences.
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