Site Reliability Engineer

Schonfeld•New York, NY

25d•$150,000 - $225,000

About The Position

We’re looking for a Site Reliability Engineer to join our AI Technology team and play a critical role in ensuring the stability and scalability of the firm’s internal Agentic AI platform. This is a high-impact, hands-on engineering position where you’ll contribute code, automation workflows, observability, metrics, and support users as issues arise. You’ll work in a dynamic, fast-paced environment where product requirements evolve, and business stakeholders are deeply engaged.

Requirements

5+ years of professional cloud automation or site reliability engineering experience, or similar
Familiarity with software development best practices and experience creating applications in Python
Experience working creating and integrating REST APIs, and event-driven and asynchronous architectures
Experience working with both relational (Postgres, MySQL) and NoSQL databases (DynamoDB, Elastic Search)
Experience with AWS cloud services (S3, OpenSearch, DynamoDB, etc.), Kubernetes-driven deployments, Github Actions, and modern CI/CD pipelines
A passion for AI, creative ideas for how it can be a tool for problem solving and productivity
A thoughtful approach to problem-solving; ability to break down complex issues methodically
Excellent communication skills; Able to translate technical concepts for non-technical stakeholders

Nice To Haves

Experience developing agentic AI applications, harnesses, MCP servers, and workflows
Familiarity with or experience building AI agents, Retrieval-Augmented Generation (RAG) pipelines, or agentic tools
Experience with observability tooling such as DataDog

Responsibilities

Set the reliability standards for Enterprise AI, defining Service Level Objectives (SLOs), error budgets, and custom incident response runbooks.
Own the observability, incident response, reliability, and scalability of our AI platform.
Ensure that our agents, gateways, LLM proxies, and RAG pipelines operate with high availability, accuracy, and financial efficiency.
Support users in a dedicated help channel when issues arise — investigating root causes, providing solutions, monitoring the status of upstream dependencies, and communicating updates back to users.
Be involved in the team’s code quality and best practices, identify gaps in development lifecycles, and continuously improve both the core platform and how developers build with it.