AI Engineer

Essential Duties & Functions

• Design and build AI-powered applications and integrations across a variety of use cases
• Lead implementation of small- to medium-scale AI solutions, with contribution to larger enterprise initiatives
• Translate business requirements into scalable, supportable technical architectures
• Design and implement data pipelines for AI/ML use cases (ingestion, transformation, and delivery)
• Prepare and manage datasets for AI consumption, including cleansing, normalization, and feature engineering
• Ensure data quality, lineage, and readiness for model training and inference
• Apply best practices for handling sensitive data, including PII and regulated data
• Evaluate and apply appropriate AI/ML (regression models, NLP, LLMs, Multi-modal models, embedding models, etc.) approaches based on use case
• Design and implement retrieval systems, including Retrieval-Augmented Generation (RAG)
• Apply agentic AI patterns and architectures to enable multi-step reasoning and orchestration
• Support training, fine-tuning, and optimization of models where applicable
• Implement techniques such as model distillation, quantization, and performance tuning
• Balance cost, performance, and accuracy in model selection and deployment
• Build and integrate AI capabilities into enterprise systems, APIs, and workflows
• Design scalable, secure architectures for AI services and applications
• Ensure solutions are production-ready, maintainable, and aligned to enterprise standards
• Engage with business stakeholders to gather and refine requirements
• Clearly articulate technical concepts, trade-offs, and solution approaches
• Validate requirements and translate them into actionable technical plans

Qualifications

• Bachelor’s degree in a related field and 5+ years experience in software engineering, data engineering, or AI/ML engineering - or equivalent combination of education and experience.
• Experience with multi-paradigm databases (vector, graph, DBMS, document, etc.)
• Hands-on experience developing AI/ML solutions in production environments
• Proficiency in Python and common AI/ML frameworks and tools
• Excellent verbal and written communication skills, with the ability to convey technical concepts clearly and effectively
• Strong critical thinking and problem-solving skills
• Able to collaborate effectively with business stakeholders, technical teams, and cross-functional partners
• Self-motivated with the ability to work independently and manage competing priorities
• Strong experience building data pipelines and working with structured and unstructured data
• Experience with cloud platforms (e.g., Azure, AWS, or GCP), including AI and data services, Azure is preferred
• Solid understanding of data security principles and handling of sensitive data
• Demonstrated ability to work independently, manage projects, and make impactful technology recommendations.