Senior Software Engineer (AI/ML)
Summary
Build and deploy production-grade AI systems, including agentic workflows, RAG pipelines, and LLM integrations using Python, TensorFlow, and PyTorch.
Responsibilities
- Design, build and deploy production-grade machine learning and Generative AI systems.
- Architect agentic and multi-agent solutions including tool and function calling workflows.
- Create Retrieval-Augmented Generation (RAG) pipelines that ground outputs in enterprise data.
- Improve prompt design, safety and response quality through testing and iteration.
- Define evaluation approaches, metrics and benchmarks for model and system performance.
- Integrate AI capabilities into existing platforms with data engineers, platform teams and stakeholders.
- Uphold engineering standards through code reviews, testing, documentation and debugging.
Requirements
- Python proficiency and hands‑on use of machine learning and deep learning frameworks such as TensorFlow and PyTorch.
- Experience building with Large Language Models (LLMs) including orchestration frameworks, agents and reasoning patterns.
- Experience designing and implementing Retrieval-Augmented Generation (RAG) systems for enterprise knowledge and search.
- Knowledge of data preparation, feature engineering, model selection and production performance considerations.
- Understanding of core machine learning math including probability, linear algebra and optimization.
- Familiarity with software engineering practices including Git, testing strategies and maintainable code.
- Strong problem-solving with the ability to diagnose and resolve complex ML and GenAI system issues.