
Staff AI Engineer
Required skills
- LLM
- RAG
- Agents
- Credit Workflows
- Prompt Design
- Tool Use
- Orchestration
- System Evaluation
- Production Infrastructure
- APIs
Nice to have
- Human-in-the-loop systems
- Feedback loops
- Long-horizon agentic task execution
- Financial systems
- Risk modeling
- Decision automation
Role summary
We are seeking experienced AI Engineers to build and scale intelligent agents from the ground up. You will be instrumental in designing and deploying LLM-powered agents using RAG for credit workflows, working directly with customers to co-develop AI solutions, and owning production infrastructure. Responsibilities include architecting backend systems, evaluating and optimizing AI applications for accuracy, latency, and reliability, and contributing to core platform design and engineering best practices. The ideal candidate has 8-12+ years of software engineering experience, with 2-3+ years in AI/ML systems, LLM agents, or RAG systems, proficiency in Python, and experience with cloud infrastructure (GCP preferred).
- 8-12+ years of software engineering experience
- 2-3+ years of hands-on experience building AI/ML systems , 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
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