Artificial Intelligence Engineer

Job Description

AI Engineer – LLMs, GenAI & Agentic Systems

BON Credit (Bhim Digital, Inc.)

📍 Palo Alto, California | ⏳ Full-time | 🚀 Start: Immediate

About BON Credit

BON CREDIT is building an AI-first consumer fintech that helps Americans get out of credit card debt- intelligently and consistently.

We’re not shipping another finance dashboard.

We’re building an always-on AI financial companion that understands users, builds plans, tracks progress, and nudges behavior – every single day.

This role isn’t about “supporting AI.”

You’ll be shaping how the product thinks, speaks, and acts.

What you’ll do

You’ll own the AI layer end-to-end and turn cutting-edge GenAI into a real product people trust.

• Build and scale BON CREDIT’s agentic AI systems
• Design workflows for financial planning, progress tracking, and motivation
• Create LLM-powered conversational experiences that feel calm, human, and trustworthy
• Build production-grade RAG pipelines using user data, financial logic, and rules
• Integrate LLM APIs with strong observability, safety, and reliability
• Partner closely with product & design to translate UX into AI behavior
• Continuously improve response quality, structure, and usefulness
• Ensure outputs are safe, compliant, and fintech-ready

What we’re looking for: Core skills

You don’t just use GenAI – you understand how it really works.

• Strong experience with Generative AI, LLMs, and ML fundamentals
• Hands-on building real user-facing AI products (not just demos)
• Deep understanding of:
• Prompt design, system prompts, tool calling, context management
• Embeddings, similarity search, ranking
• Where LLMs fail – and how to design around it
• Experience deploying LLM systems in production:
• Logging, monitoring, evaluation loops
• Cost, latency, and reliability trade-offs
• Proven work with:
• RAG pipelines
• Fine-tuning (and knowing when not to fine-tune)
• Feedback loops & human-in-the-loop systems

LLM systems & conversational AI

• Integrating LLM APIs into backend systems
• Tool/function calling and agent orchestration
• Designing multi-turn conversations that stay coherent
• Managing memory, context decay, and user state
• Building assistants that guide, not overwhelm

Bonus points if you…

• Explain complex AI behavior clearly to non-technical teammates
• Think in product outcomes, not just technical elegance
• Learn fast in ambiguity and love shipping
• Take feedback like a pro and iterate even faster

Hiring process

1. Quick intro chat
2. Deep dive into AI systems you’ve built
3. Technical interview
4. Final product & culture conversation