Principal AI / ML Engineer

Key Responsibilities

• Design and architect AI/ML solutions to address business problems, setting the technical direction and architectural patterns for the team.
• Lead the hands-on development of applications, services, APIs, and reusable components that deliver and operate data science solutions.
• Rapidly develop proof-of-value (POV) applications and prototypes to validate concepts with business stakeholders.
• Work directly with business stakeholders, data scientists, and engineers to understand requirements and identify high-value opportunities.
• Build interactive AI-powered applications, covering both traditional machine learning and modern Generative AI or Agentic AI use cases.
• Design end-to-end solutions that combine structured data, unstructured data, business rules, semantic search, and LLM capabilities.
• Establish and enforce engineering practices for deploying, operating, and monitoring ML/AI solutions in production, including standards for CI/CD, automated testing, and versioning.
• Lead architecture, design, and code reviews, serving as the final escalation point for complex technical decisions.
• Mentor other engineers, promote engineering best practices, and build the team's depth in cloud architecture, software development, and MLOps.
• Serve as a trusted technical advisor during project intake and solution evaluation discussions.

Required Qualifications
Education: A bachelor's degree and 10+ years of experience in a related field, or a Master's degree and 8+ years of experience in a related field.
Experience: Proven background in end-to-end application development, preferably transitioning from a Software Engineering role into AI/ML Engineering. Experience should include AI/ML solution architecture, solution design, and proof-of-value development. Must possess experience in model operationalization and AI-powered workflow automation.
Technical Skills:

• Programming expertise in Python, SQL, and React.js.
• Knowledge of AI/ML concepts including Machine Learning, Generative AI, and Agentic AI systems.
• Understanding of Semantic Search, Retrieval Augmented Generation (RAG), LLMs, and fine-tuning techniques.
• Experience with API-driven solution development, data enrichment, and classification.
• Familiarity with data engineering fundamentals and an understanding of distributed platforms like Spark/PySpark.
• Knowledge of traditional data science concepts (EDA, model development, analytics).

Preferred Qualifications

• Experience building AI-powered internal business applications.
• Experience evaluating governance, risk, and AI guardrail requirements.
• Knowledge of Databricks functionalities such as MLFlow, foundation models, model serving, and Unity AI capabilities.
• Experience with Azure-based AI deployments.
• Experience supporting both research-oriented and engineering-oriented AI teams.
  Equal Opportunity Employer:
  We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law