AI Engineer, Sr

Job Duties And Responsibilities

• Design, develop, validate and deploy AI driven solutions that support automation, predictive analytics, forecasting, and decision support across the business
• Build and maintain machine learning models and AI services used in production environments
• Design and orchestrate multi agent AI systems, including LLM based agents, agent routing and collaboration, and MCP enabled data and tool APIs for secure, scalable enterprise workflows
• Build and optimize LLM capabilities using retrieval augmented generation, model fine tuning, and interface integration to deliver reliable, high quality AI outputs in production environments
• Integrate AI capabilities with existing enterprise systems such as ERP, CRM, data platforms, and workflow tools
• Implement data pipelines and feature engineering processes to support reliable model training and inference
• Evaluate and integrate third party AI platforms, APIs, and tools where appropriate
• Establish best practices for model deployment, monitoring, performance tuning, and lifecycle management
• Support enterprise data governance by partnering with data owners to define data contracts and ensure data quality and consistency across pipelines
• Achieve AI solutions meet security, privacy, and responsible AI standards
• Collaborate with software engineers, data engineers, and IT teams to ensure scalable and maintainable implementations
• Measure and communicate business impact of AI solutions using clear metrics and outcomes
• Document system designs, models, and operational processes to support knowledge sharing and scalability
• Manage, lead, and/or assist various new or sustaining technology projects; perform light project management duties as required
• Stay current with applied AI trends and recommend practical innovations that align with business goals

Qualifications

• Programming languages: Python for building AI models, automation, and production services; SQL for working with structured data used in analytics, forecasting, and model inputs
• Strong understanding of data pipelines, feature engineering, and data quality fundamentals
• Experience integrating AI solutions with existing enterprise systems using APIs
• Familiarity with cloud-based AI services and deployment patterns
• Applied model evaluation and testing expertise, including prompt testing, experimentation and A/B testing, system integration testing and production monitoring
• Experience optimizing costs for LLMs and agentic systems in cloud environments, including inference efficiency, token usage, and model selection tradeoffs
• Knowledge of security, privacy, and responsible AI considerations in business environments
• Knowledge of software engineering best practices including version control, testing, and documentation

Education And Experience

• Bachelor’s degree in computer science, engineering, data science, mathematics, or a related technical field, or equivalent practical experience
• Over 8 years of relevant professional or technical engineering experience of increasing responsibility and difficulty of assignments
• Hands on experience with at least one machine learning framework such as scikit learn, PyTorch, or TensorFlow
• Practical experience using large language models via APIs for real world business use cases
• Experience designing and implementing AI driven automation or agentic workflows