Bachelor's degree (BS or above) in Computer Science, Data Science, AI Engineering, or technical equivalent
3 to 5+ years of applied AI/ML solution development experience
3+ years of software development experience using the Python ecosystem
Experience dealing with uncleaned real-world data
Requirements:
Lead architecture, design, strategy, and implementation of agentic AI systems for goal-driven decision-making under real-world constraints
Translate product and customer requirements into production-grade AI system designs
Drive rapid deployment iterations while maintaining reliability and safety; participate in peer reviews of designs and code
Define platform standards and collaborate with domain experts and cross-functional teams to improve development procedures and resolve technical problems
Job description
Leading the architecture, design, strategy, development and implementation of agentic AI systems capable of goal-driven decision-making, planning, and action under real-world constraints
Translate product and customer requirements into production grade AI system designs
Drive rapid iteration of deployment while maintaining system reliability and safety
Participating in peer-reviews of solution designs and related code
Working with teammates to dive efβiciencies to development procedures
Analyzing and resolving technical problems
Deβining standards for the platform to deliver AI solutions
Balance learning-based approaches with deterministic or rules-based components where appropriate
Support customer-facing and sales technical discussions when AI and platform expertise is required
Requirements
BS or above in Computer Science, Data Science, AI Engineering or technical equivalent.
3 to 5+ years in applied AL / ML solution development
3+ years Software Development experience using the Python ecosystem
An agile self-starter with a software craftsmanship mindset and the ability to act on their own initiative and self-direct.
Experience dealing with uncleaned real-world data.
Experience working with domain experts to improve problem definitions, metric selection, and feature selection.
Experience working with a globally distributed team in different time zones.
Advantageous Experience/Skills:
2+ years building agentic AI using common frameworks / MCP
At least 1+ years developing RL agent/ LLMs & RAG/ anomaly prediction & forecasting solutions
2+ years IoT and Timeseries data manipulation
2+ years AWS cloud and/or Docker
Proficiency with MLOps
Digital twins, physical models / simulators, or model-based RL
Experience using AI for industrial process control
