Job Description:
• Designs and owns end-to-end AI solutions, including LLM-based applications, classical machine learning models, and hybrid approaches.
• Builds and operates complex AI systems such as agentic workflows, retrieval-augmented generation (RAG) platforms, and decision-support solutions.
• Evaluates ambiguous business problems and determines appropriate AI patterns, modeling techniques, and system architectures.
• Defines and implements evaluation strategies, metrics, and feedback loops to measure model effectiveness and business impact.
• Leads the development of data pipelines, feature strategies, and evaluation datasets required to support AI systems.
• Owns production readiness, including performance, reliability, cost, observability, and failure handling.
• Identifies and mitigates risks related to bias, hallucination, data leakage, and unintended AI behavior.
• Collaborates cross-functionally with product management, platform teams, and stakeholders to guide solution design and delivery.
• Mentors and provides technical guidance to other team members.
• Contributes to the establishment and evolution of AI engineering standards, patterns, and best practices.
Requirements:
• Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related technical field, or equivalent practical experience.
• Five or more years of professional experience spanning software engineering, data science, machine learning engineering, or AI system development.
• Advanced proficiency in software engineering, including Python, APIs, testing, and system design.
• Advanced proficiency in one or more large scale data platform such as Snowflake, Databricks, Amazon Redshift, Microsoft Synapse, or similar.
• Strong applied knowledge of machine learning and artificial intelligence concepts, evaluation techniques, and failure modes.
• Hands-on experience designing, building, and deploying LLM based systems using enterprise grade platforms and frameworks.
• Experience with one or more AI orchestration frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar.
• Deep understanding of data quality, feature relevance, and model behavior across structured and unstructured data.
• Experience deploying, monitoring, and iterating on AI systems in production environments.
• Ability to make and defend technical tradeoff decisions balancing accuracy, cost, risk, and scalability.
• Strong communication and leadership skills, with the ability to influence technical direction and mentor others.
Benefits:
• Generous paid time off
• Top-tier medical, dental and vision benefits
• Health & wellness support
• Paid volunteer hours