Location
New York, USA
Salary
$200,000–$300,000 per year
Company
UMA is partnering with a fast-growing technology company that builds intelligent software for advanced engineering environments and data-intensive operations.
What you will do
•Build production AI systems, including agent infrastructure, retrieval pipelines, evaluation frameworks, and intelligent workflows.
•Develop AI-powered engineering tools for investigating anomalies, identifying root causes, and analysing complex system behaviour.
•Work with large-scale datasets such as time-series data, telemetry, logs, and operational information.
•Design scalable backend infrastructure for reliable, production-ready AI applications.
•Take ideas from zero to one through rapid prototyping, testing, and improvement based on customer feedback.
•Collaborate directly with customers and influence product and engineering decisions.
Requirements
•5+ years of software engineering experience, including experience building AI or machine learning products deployed in production.
•Strong software engineering fundamentals, particularly in backend development, distributed systems, or data-intensive applications.
•Experience working with large datasets, time-series data, data infrastructure, or ML systems.
•Hands-on experience developing and deploying AI-powered applications.
•Experience taking products from early-stage ideas through to production.
•Comfort working in ambiguous environments, making technical decisions, and taking ownership.
•Strong problem-solving skills and an interest in understanding real customer challenges.
Nice to have
•Experience with AI agents, LLM applications, RAG, retrieval pipelines, or evaluation frameworks.
•Experience with telemetry, observability platforms, or time-series databases.
•Experience in robotics, aerospace, autonomous systems, industrial technology, or other hardware-related environments.
•Experience in early-stage startups, founding engineering teams, or new product development teams.
Culture & Benefits
•Work on zero-to-one AI products and influence what gets built.
•Make technical decisions and take ideas from early prototypes through to production.
•Work directly with customers and the people using the software.
•Address complex engineering environments where performance, reliability, and precision are critical.
