About the role

What will you do at Obin AI?

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

● Owning agentic AI strategy across the company's product suite; sets governance

standards for agent evaluation, safety and autonomy.

* Recognized technical authority in multi-agent systems; publishes reusable

blueprints/reference architectures; represents the company externally

(conferences, open source, technical publications).

* 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:

* 10-15+ years of software engineering experience

* 5-8+ years of hands-on experience building AI/ML systems/frameworks ,

LLM-based agents and/or RAG systems in production

* Logging, evaluating, optimizing AI applications

* Sets architecture for agentic AI systems across products; solves ambiguous

problems inherent to non-deterministic systems (context pollution, runtime

state handoffs, safety).

* Expert in agent-to-agent (A2A) orchestration protocols, self-correcting agent

loops, prompt-routing middleware; drives AI safety/reliability practices and

evaluation standards; mentors senior engineers.

* 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

Which skills does this role require?

Agentic AIRAGPythonMulti-agent systemsCloud infrastructureAPI developmentPrompt engineeringOrchestration logicAI safetyPerformance optimizationBackend systemsTechnical leadershipMentoringPrincipal AI EngineerOrchestrationAPIBackendCredit workflowsObservabilityScalabilityMachine learningInfrastructureTechnical roadmapSoftware engineeringData sourcesPerformance tuningGovernanceMachine LearningLLMsProduct StrategyA/B Testing

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