AI Engineer

About the Role

We are building a Generative AI-driven financial intelligence platform designed to help users from novice investors to experienced market participants make smarter financial decisions.

This is not a surface-level LLM integration role. We are looking for a strong Machine Learning Engineer who can work across classical ML + LLM systems, contribute to a multi-agent architecture, and build production-grade AI systems where data correctness and reliability are critical.

If you are a core ML engineer who thinks in systems not scripts this role is for you.

Key Responsibilities

• Design, build, and deploy production-grade ML systems
• Work on multi-model / multi-agent AI architecture
• Integrate classical ML models with LLM-based components
• Build and evaluate recommendation systems & predictive models
• Ensure data integrity and sanity checks (critical in finance)
• Own full lifecycle: Research Experimentation Evaluation Production
• Optimize models for scalability, reliability, and performance
• Collaborate closely with product and engineering teams

Required Skills & Experience

Core Machine Learning

• Strong foundation in supervised learning, recommendations, predictive modeling
• Solid understanding of statistics & mathematical fundamentals
• Experience designing ML systems beyond basic model training
• Strong evaluation methodology knowledge

LLM & AI Systems

• Experience working with LLM-based systems
• Exposure to multi-agent or multi-model systems preferred
• Understanding of system-level architecture involving LLMs
• Experience beyond basic RAG implementations

Note: Only prompt engineering or surface-level RAG experience will not be sufficient.

Programming & Engineering

• Strong Python skills
• Strong data structures & problem-solving ability
• Ability to write clean, production-quality code
• Understanding of system design and scalability principles

Ideal Candidate Profile

• 26 years of relevant experience in ML/AI
• Strong tenure stability (2.54 years preferred in roles)
• Product company experience preferred
• Fintech domain exposure is a strong advantage
• Experience building systems end-to-end (ownership mindset)
• Strong engineering fundamentals (non-negotiable)

Red Flags (What We Avoid)

• Only prompt engineering experience
• Only RAG-based implementation without ML depth
• Service-based background with limited ownership
• Frequent job switching (<1.5 years per role)
• Weak coding fundamentals

What We Offer

• Opportunity to build AI systems from scratch in a high-impact domain
• Ownership-driven culture
• Exposure to cutting-edge Generative AI architecture
• Fast feedback and high learning environment