AI/ML Engineer

Responsibilities

• Contribute to the development and delivery of AI and machine-learning solutions for client engagements, including generative AI and agent-based capabilities.
• Implement AI workflows, services, and integrations that work alongside data and application platforms.
• Apply established AI techniques, patterns, and tools to solve well-defined problems.
• Participate in design discussions, reviews, and team feedback sessions.
• Collaborate with data engineers and application engineers to support production-ready AI solutions.
• Follow responsible AI practices, including awareness of data usage, bias, transparency, and privacy considerations.
• Write clear, maintainable code and supporting documentation.
• Continue developing skills in AI, machine learning, and production delivery practices.

Requirements

• 2+ years of experience building or supporting AI or machine-learning solutions.
• Experience using Python for AI or machine-learning development.
• Familiarity with machine learning, generative AI, or agent-based approaches.
• Experience working with structured or unstructured data for AI use cases.
• Basic understanding of model evaluation, performance considerations, and limitations.
• Exposure to deploying or supporting AI solutions in production or near-production environments.
• Familiarity with AWS and/or Azure services.
• Understanding of foundational data engineering concepts, such as data pipelines and data quality.
• Ability to communicate technical concepts clearly within a team and with client stakeholders.

Preferred Qualifications

• Experience with LLM platforms or tools such as Amazon Bedrock, Azure AI Foundry, or similar.
• Exposure to MLOps practices, including model versioning or monitoring.
• Experience working alongside data engineering teams on shared solutions.
• AWS, Azure, or entry-level AI/ML certifications.
• Databricks or Snowflake certifications.
• Previous consulting or client-facing experience.