Asks for

The ad says“Architect and maintain backend systems and APIs that connect to data sources and customer platforms. Ensure high availability, performance, and observability.”
The ad says“Architect and maintain backend systems and APIs that connect to data sources and customer platforms. Ensure high availability, performance, and observability.”
The ad says“● Proficiency in Python and experience with modern AI/ML frameworks and cloud infrastructure (GCP preferred)”
The ad says“Build agentic systems using LLMs and RAG to automate complex credit workflows. This includes prompt design, tool use, orchestration logic, and system evaluation.”
The ad says“● Logging, evaluating, optimizing AI applications”
The ad says“● Logging, evaluating, optimizing AI applications”
The ad says“Build agentic systems using LLMs and RAG to automate complex credit workflows. This includes prompt design, tool use, orchestration logic, and system evaluation.”
The ad says“Build agentic systems using LLMs and RAG to automate complex credit workflows. This includes prompt design, tool use, orchestration logic, and system evaluation.”
The ad says“● Proficiency in Python and experience with modern AI/ML frameworks and cloud infrastructure (GCP preferred)”
The ad says“Build agentic systems using LLMs and RAG to automate complex credit workflows. This includes prompt design, tool use, orchestration logic, and system evaluation.”
The ad says“● Strong intuition around system architecture, performance, and scaling”
The ad says“Build agentic systems using LLMs and RAG to automate complex credit workflows. This includes prompt design, tool use, orchestration logic, and system evaluation.”
The ad says“Build agentic systems using LLMs and RAG to automate complex credit workflows. This includes prompt design, tool use, orchestration logic, and system evaluation.”

The Role:

We're looking for AI Engineers who can help us build and scale intelligent agents from the ground up. You’ll join our team as one of our earliest hires. You'll work directly with the founders (ex-Google) and own key technical decisions from day one.

You’ll be

● Designing and Deploying LLM-Powered Agents

Build agentic systems using LLMs and RAG to automate complex credit workflows. This includes prompt design, tool use, orchestration logic, and system evaluation.

● Working Directly with Customers

Partner with technical and non-technical stakeholders at major credit firms to understand workflow pain points and co-develop AI solutions that directly tie to ROI.

● Owning Production Infrastructure

Architect and maintain backend systems and APIs that connect to data sources and customer platforms. Ensure high availability, performance, and observability.

● Evaluating and Optimizing Systems

Balance accuracy, latency, reliability, cost, and explainability in our agentic systems. Lead rigorous experimentation and improvement cycles.

● Contributing to Core Platform Design

Define technical architecture, build reusable infrastructure for agent deployment, and shape the foundation of Obin’s AI engineering best practices.

● Setting Culture and Standards

Help define Obin’s engineering culture, hiring bar, and long-term technical roadmap

We believe great AI Engineers come from diverse backgrounds and are unified by deep curiosity, pragmatism, and engineering excellence.

Experience Required:

● 3-5+ years of software engineering experience

● 1+ years of hands-on experience building LLM-based agents and/or RAG systems in production

● Logging, evaluating, optimizing AI applications

● Proficiency in Python and experience with modern AI/ML frameworks and cloud infrastructure (GCP preferred)

● Experience with cloud infra (preferably GCP) and APIs

● Hunger to move fast, own outcomes, and build something enduring

● Strong intuition around system architecture, performance, and scaling

● Clear communication, especially in ambiguous, high-stakes problem spaces

Bonus:

● Experience with human-in-the-loop systems, feedback loops, and long-horizon agentic task execution

● Background in financial systems, risk modeling, or decision automation

● Familiarity with PydanticAI, LlamaIndex, Google ADK, Claude Agent SDK, or similar frameworks

● You’ve built or contributed to an internal AI platform or reusable LLM tooling

Base compensation range:

$150,000 - $180,000

Plus Annual Bonus + Equity

Asks for

Values