Lead AI/ML Engineer

The work we do has an impact on millions of lives, and you can be a part of it.We help protect our customers against life’s uncertainties. Regardless of where you work within the company, you’ll be helping provide protection and peace of mind when our customers need it most.
Protective is seeking a Lead AI/ML Engineer to join the Data & AI Platform team, focused on owning the development, maintenance, and adoption of tooling and frameworks for data scientists across the organization, with a strong emphasis on artificial intelligence (AI), large language models (LLMs), and agentic frameworks. This role will closely collaborate with the Lead Data Platform Engineer for deployment and integration of solutions and the Cloud Data Architect to define best practices and standards. The Lead AI/ML Engineer will drive the creation and adoption of scalable, cloud-native tooling to empower data scientists to build, test, and monitor advanced AI models efficiently while ensuring alignment with enterprise architecture and platform strategies.

HIGH LEVEL DUTIES

• Own the design, development, and adoption of cloud-based tooling and frameworks for AI-driven workflows, focusing on LLMs and agentic frameworks, ensuring scalability, reproducibility, and usability.  
• Collaborate closely with the Lead Data Platform Engineer to integrate and deploy AI solutions into the DataHub platform, ensuring seamless operationalization.  
• Partner with the Cloud Data Architect to define and implement best practices, standards, and governance for AI model development, particularly for LLMs and agentic systems.  
• Drive the adoption of standardized tooling for model development, testing, and monitoring by data scientists across the organization.  
• Lead the implementation of MLOps and AIOps practices for AI model lifecycle management, working with the Lead Data Platform Engineer to automate deployment pipelines.  
• Promote best practices for AI development, including prompt engineering, model interpretability, responsible AI, and agentic framework design, in alignment with architectural standards.  
• Provide technical mentorship to data scientists, fostering expertise in AI tooling and adoption of standardized frameworks.  
• Ensure governance and compliance for AI models, collaborating with the Cloud Data Architect to address fairness, transparency, and regulatory requirements.  
• Monitor and optimize the adoption and performance of AI tooling, ensuring alignment with business needs and platform reliability.

SPECIFIC DUTIES

• Own the development of a cloud-native MLOps/AIOps framework for training, fine-tuning, validating, and monitoring AI models, including LLMs and agentic frameworks, ensuring ease of adoption by data scientists.  
• Build and maintain reusable AI libraries and templates for common use cases (e.g., prompt engineering, LLM fine-tuning, Retrieval-Augmented Generation (RAG), agentic task orchestration).  
• Drive adoption of best practices for LLM experimentation (e.g., prompt optimization, context window management) and agentic system design, in collaboration with the Cloud Data Architect.  
• Create tooling for explainability and interpretability of LLMs and agentic systems, aligning with architectural standards for stakeholder trust and compliance.  
• Collaborate with the Lead Data Platform Engineer to automate AI model deployment pipelines using cloud-native tools (e.g., Azure ML, Databricks MLflow, Hugging Face).  
• Develop monitoring solutions to track model performance, drift, and bias, working with the Lead Data Platform Engineer to integrate with DataHub monitoring systems.  
• Partner with the Cloud Data Architect to establish AI governance frameworks, including model documentation, versioning, and responsible AI policies for LLMs and agentic systems.  
• Facilitate integration of AI workflows with the DataHub, collaborating with the Lead Data Platform Engineer to ensure seamless access to curated data domains for LLM training and agentic system inputs.  
• Work with the Lead Data Platform Engineer to optimize data pipelines for AI use cases, including vector databases and embeddings for LLMs and RAG systems.  
• Own the development and adoption of agentic frameworks for autonomous task execution and multi-agent collaboration, ensuring alignment with platform deployment capabilities.  
• Document and promote best practices for cloud-based AI tools (e.g., Jupyter, PySpark,  LlamaIndex, MCP, A2A), in collaboration with the Cloud Data Architect.  
• Lead the adoption of advanced AI techniques (e.g., few-shot learning, chain-of-thought prompting, multi-modal LLMs), ensuring compatibility with platform infrastructure. 

ROLE REQUIREMENTS

• 7-10 years of experience in AI/ML engineering, with at least 3 years in cloud-based AI environments and hands-on work with LLMs and agentic frameworks.  
• 3+ years of experience with MLOps/AIOps practices, focusing on tooling for model development and monitoring.  
• 5+ years of proficiency in Python (e.g., Pandas, Scikit-learn, TensorFlow, PyTorch, Hugging Face Transformers) and SQL.  
• 3+ years of experience with cloud platforms (Azure Databricks or similar platform preferred) 
• Strong experience with PySpark for large-scale data processing, feature engineering, and embeddings for LLMs.  
• 3+ years of experience with CI/CD pipelines and version control (e.g., Git, Azure DevOps) for AI tooling integration.  
• Deep understanding of machine learning, generative AI, LLMs, and agentic frameworks, including techniques like fine-tuning, RAG, and multi-agent systems.  
• Hands-on experience with LLM frameworks (e.g., LangChain, LlamaIndex, AutoGen) and prompt engineering for tasks like text generation, summarization, and reasoning.  
• Experience building AI tooling for production environments, collaborating on containerization (e.g., Docker, Kubernetes) with platform engineers.  
• Strong knowledge of AI governance, responsible AI, and ethical considerations for LLMs (e.g., bias mitigation, hallucination control), aligned with architectural standards.  
• Excellent communication and collaboration skills to work with the Lead Data Platform Engineer, Cloud Data Architect, and cross-functional stakeholders.  
• Proven ability to mentor data scientists and drive adoption of AI tooling and frameworks.  
• Experience with big data tools (e.g., Hadoop, Spark, Kafka) and data orchestration platforms (e.g., Airflow, Databricks Workflows).  
• Familiarity with vector databases (e.g., Pinecone, Weaviate) and infrastructure as code for AI workloads is a plus. 

Employee Benefits:  We aim to protect the wellbeing of our employees and their families with a broad benefits offering. In addition to offering comprehensive health, dental and vision insurance, we support emotional wellbeing through mental health benefits and an employee assistance program. Work/life balance is important and Protective offers a variety of paid time away benefits (e.g., paid time off, paid parental leave, short-term disability, and a cultural observance day). The financial health of our employees is just as important as physical and emotional health.  Some of the financial wellbeing benefits include contributions to healthcare accounts, a pension plan, and a 401(k) plan with Company matching. All employees are encouraged to protect their overall wellbeing by engaging in ProHealth Rewards, Protective’s platform to improve wellbeing while earning cash rewards.   
Eligibility for certain benefits may vary by position in accordance with the terms of the Company’s benefit plans.
Accommodations for Applicants with a Disability:If you require an accommodation to complete the application and recruitment process due to a disability, please email martina.winston@protective.com. This information will be held in confidence and used only to determine an appropriate accommodation for the application and recruitment process.
Please note that the above email is solely for individuals with disabilities requesting an accommodation.  General employment questions should not be sent through this process.
We are proud to be an equal opportunity employer committed to being inclusive and attracting, retaining, and growing an inclusive workforce.