Artificial Intelligence Engineer III
Design, deliver, and own complex, production‑grade artificial intelligence systems that address ambiguous and high‑impact business problems. Apply advanced software, data science, machine learning, and LLM engineering expertise to build AI‑powered applications, model‑driven solutions, and intelligently automated workflows while ensuring reliability, measurability, security, and alignment with enterprise AI standards.
Responsibilities
- Design and own end‑to‑end AI solutions, including LLM‑based applications, classical machine learning models, and hybrid approaches.
- Build and operate complex AI systems such as agentic workflows, retrieval‑augmented generation (RAG) platforms, and decision‑support solutions.
- Evaluate ambiguous business problems and determine appropriate AI patterns, modeling techniques, and system architectures.
- Define and implement evaluation strategies, metrics, and feedback loops to measure model effectiveness and business impact.
- Lead the development of data pipelines, feature strategies, and evaluation datasets required to support AI systems.
- Own production readiness, including performance, reliability, cost, observability, and failure handling.
- Identify and mitigate risks related to bias, hallucination, data leakage, and unintended AI behavior.
- Collaborate cross‑functionally with product management, platform teams, and stakeholders to guide solution design and delivery.
- Mentor and provide technical guidance to other team members.
- Contribute to the establishment and evolution of AI engineering standards, patterns, and best practices.
Qualifications
- 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 platforms 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 trade‑off decisions balancing accuracy, cost, risk, and scalability.
- Strong communication and leadership skills, with the ability to influence technical direction and mentor others.
At Insperity, we celebrate the diversity of our employees and our leadership. Insperity is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status or any other characteristic protected by law.