Agentic AI Engineer

Location: NYC-Metro; hybrid work required

Base compensation: $190,000–$250,000 annually, plus annual bonus and equity.

Company

hirify.global builds production-ready agentic AI systems for financial services, enabling regulated institutions to automate workflows within governance and audit controls.

What you will do

• Design and deploy LLM-powered agents using RAG, prompt engineering, tool use, orchestration logic, and system evaluation.
• Partner with technical and non-technical stakeholders at major credit firms to understand workflow challenges and co-develop ROI-focused AI solutions.
• Architect and maintain backend systems and APIs connecting data sources and customer platforms.
• Optimize agentic systems across accuracy, latency, reliability, cost, explainability, and observability.
• Build reusable infrastructure for agent deployment and contribute to the core AI engineering platform and architecture.
• Help define engineering standards, hiring expectations, and the long-term technical roadmap.

Requirements

• 5+ years of software engineering experience.
• 1+ year of hands-on experience building LLM-based agents and/or RAG systems in production.
• Experience logging, evaluating, and optimizing AI applications.
• Proficiency in Python and experience with modern AI/ML frameworks, cloud infrastructure, and APIs; GCP is preferred.
• Strong understanding of system architecture, performance, and scaling.
• Clear communication and the ability to own outcomes in ambiguous, high-stakes problem spaces.

Nice to have

• 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.
• Experience building an internal AI platform or reusable LLM tooling.

Culture & Benefits

• Work directly with the founders and contribute as one of the earliest hires.
• Opportunity to influence technical decisions, engineering culture, and platform standards from the start.
• Annual bonus and equity in addition to base compensation.
• Work on AI systems for regulated financial institutions with traceable and inspectable outputs.