Sr. Data Engineer

Sr. Data Engineer

Requirements

• 2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)
• Strong software engineering background with experience in Python, PyTorch, TensorFlow, or JAX.
• 2+ years of experience building and pushing code into production.
• 2+ years of relevant work experience solving data problems using data technologies (e.g., Hadoop, Hive, Kafka, Redis, NoSQL, RDBMS).
• 2+ years of experience training and deploying Machine Learning models into production.
• Hands-on experience with LLMs (e.g., GPT, Claude, Mistral), vector databases (e.g., FAISS, Pinecone), and orchestration tools (e.g., LangChain, LangGraph, Autogen).
• Experience building AI applications on top of enterprise-scale data systems.

Responsibilities

• Design and implement scalable, high-performance data pipelines for both structured and unstructured data.
• Build and maintain internal APIs and data services to securely expose and serve data and ML model outputs.
• Champion best practices in data quality, governance, observability, and performance optimization.
• Develop, train, and fine-tune AI/ML models for business use cases such as classification, recommendation, NLP, and computer vision.
• Build and optimize LLM-based applications using prompt engineering, fine-tuning, and retrieval-augmented generation (RAG).
• Drive model evaluation, experimentation, A/B testing, and continuous learning pipelines.
• Enable Agentic AI systems by building infrastructure that supports autonomous workflows, orchestration, and decision-making loops.
• Collaborate closely with data scientists, product managers, and software engineers to integrate intelligent systems into scalable production environments.

Preferred Qualifications

• 3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD)