About the Company
Liquidity is the world's leading AI-powered private credit firm, pioneering a new standard in growth capital through a nexus of the sharpest minds in private credit and technology. With a global reach and regional expertise in every key market across North America, Europe, APAC and MENA, Liquidity supports visionary growth and mid-market companies in 45+ sectors, deploying multi-billion-dollar capital with unmatched speed, precision and adaptability. Powered by breakthrough decision science technology that deploys growth capital faster than any firm in capital markets history, Liquidity clears the path for innovative companies to move further, faster and at scale. Built on trust, Liquidity is backed by leading financial institutions including MUFG Bank Ltd., Spark Capital and KeyBank.
About the Role
We are looking for a Senior AI/ML Engineer to research, architect, develop, test, and deploy production-ready agentic AI systems that solve real business problems. You will work across the full lifecycle of autonomous AI solutions, from design and development through production deployment and continuous improvement. This role is suited for engineers who balance innovation with pragmatism, build iteratively from MVPs, design systems with appropriate guardrails and human oversight, and care deeply about delivering measurable business value through reliable, trustworthy AI agents.
Responsibilities
• Research, architect, develop, test, and deploy autonomous AI systems with measurable business impact
• Build agents with guardrails, validation layers, and human-in-the-loop workflows for critical decisions
• Develop using orchestration frameworks (LangGraph, Agno, AutoGen) to coordinate multi-step agent workflows
• Implement feedback mechanisms and monitoring to detect anomalies and improve agent behavior through iteration
• Develop robust APIs and services using Python (async, advanced design patterns) and FastAPI
• Design event-driven architectures (AWS Lambda, Step Functions, RabbitMQ) and deploy containerized services via Kubernetes
• Implement error handling, fallback mechanisms, and retry logic to ensure agents recover gracefully in production
• Establish observability using Langfuse, CloudWatch, and Datadog to track agent performance, costs, and failure modes
Qualifications
• 8+ years Software/AI experience, including 2-4 years in production Agentic AI & LLM orchestration.
• Tech Stack: Advanced Python (FastAPI, Async), AWS (Serverless/Containers), Docker, K8s, and CI/CD.
• Data: Expertise in Postgres, Neo4j, MongoDB, and Vector DBs.
• Strong problem-solving and communication skills.
• Master’s degree, Fintech background, FastMCP, Data Pipelines (ETL), or Observability tools (Datadog/Langfuse).
