3644 Senior AI Engineer

Sr. AI Engineer


The Sr. AI Engineer plays a key role in building and scaling applied artificial intelligence capabilities across the organization. This role focuses on delivering practical AI solutions that drive automation, improve decision making, and enable predictive insights across business functions such as supply chain, finance, operations, sales, and customer service. We value and encourage diversity in the workplace & women, minorities, and veterans are highly encouraged to apply. Thank you!


More about this role:


The AI Engineer, Sr will design, build, and deploy AI powered systems including predictive models, forecasting solutions, and agentic AI workflows. This is a hands-on engineering role that partners closely with business and technology teams to turn real world problems into scalable AI solutions. The role emphasizes production ready systems, responsible AI use, and measurable business impact rather than academic research.

• 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
• Ensure 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
• Manages, leads, and/or assists various new or sustaining technology projects; performs light project management duties as required.
• Stay current with applied AI trends and recommend practical innovations that align with business goals

• Programming languages:
  • Python for building AI models, automation, and production services
  • SQL for working with structured data used in analytics, forecasting, and model inputs
• Technical Skills:
  • 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
  • Understanding of software engineering best practices including version control, testing, and documentation
  • Knowledge of security, privacy, and responsible AI considerations in business environments
• Preferred Programming Languages:
  • JavaScript or TypeScript for integrating AI capabilities into web applications or internal tools
  • Bash or shell scripting for automation and deployment tasks
• Preferred Technical Skills:
  • Experience with agentic AI frameworks or orchestration tools such as LangChain, LlamaIndex, AutoGen, or MCP based patterns
  • Experience with cloud platforms such as Azure, AWS or GCP beyond basic usage
  • Familiarity or experience with Dynamics 365, Snowflake and Microsoft Fabric
  • Familiarity with MLOps practices including model monitoring, versioning, and lifecycle management
  • Experience with data pipeline and workflow tools such as Airflow, dbt, or cloud native orchestration services
  • Applied statistics and model evaluation skills, including experiment design and statistical validation, to ensure reliable and unbiased AI driven decision support and forecasting.
  • Experience evaluating and integrating third party AI platforms or vendors
  • Exposure to automation platforms, RPA tools, or workflow engines where AI is embedded into business processes
  • Familiarity with emerging AI regulations and auditability techniques
  • Ability to mentor or guide others on applied AI best practices

• Bachelor's degree in computer science, engineering, data science, mathematics, or a related technical field, or equivalent practical experience
• Successful candidates typically possess over 8 years of relevant professional or technical engineering experience of increasing responsibility and difficulty of assignments.
• Experience building and deploying applied AI or machine learning solutions in production environments
• 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