AI Engineer - Agentic Systems

AI Engineer — LLMs, GenAI & Agentic Systems

BON CREDIT (Bhim Digital, Inc.)
📍 Remote (India preferred) | ⏳ 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

Quick intro chat

Deep dive into AI systems you’ve built

Technical interview

Final product & culture conversation