AI Engineer

WHAT WE EXPECT OF YOU

SUMMARY

We are building the next generation of AI-powered capabilities across our data platform. As an AI Engineer, you will be a hands-on technical contributor who configures, orchestrates, and scales production-grade AI systems using platforms like Snowflake Cortex Agents, Claude. The role spans generative AI features, autonomous agentic workflows, and intelligent business process automation. You will work at the intersection of rapidly evolving AI platforms and real-world enterprise data, partnering closely with data engineers, analysts, product managers, and business stakeholders to deliver solutions that make a real difference.

ESSENTIAL DUTIES AND RESPONSIBILITIES

• Agent orchestration and configuration
• Configure and deploy AI agents using managed platforms such as Snowflake Cortex Agents, Claude API, and extend them with custom tools and integrations where the platform falls short.
• Design multi-agent workflows including task handoffs, tool use, and human-in-the-loop escalation paths.
• Data platform integration
• Connect AI agents to modern data platforms such as Snowflake or Databricks with appropriate access controls, and work within existing pipeline infrastructure rather than building parallel systems.
• Evaluation, observability, and cost
• Define success criteria, build evaluation frameworks, and run structured tests before any system goes to production.
• Monitor agent behavior in production and manage inference cost versus output quality trade-offs across managed platforms.
• Monitor token utilization across agent workflows and advise teams on cost control and efficient platform usage.
• Privacy, security, and responsible AI
• Apply GDPR, CCPA, and internal governance requirements across the full agent lifecycle, covering data access, logging, and outputs. Treat privacy-by-design as an architectural constraint from the start, not a review step at the end.
• Work with legal and compliance as a technical partner, and build fairness, explainability, and human oversight into agent workflows.
• Translate AI capabilities and limitations clearly to non-technical stakeholders and contribute to internal guidelines so other teams can work with AI systems confidently and safely.

QUALIFICATIONS

• Knowledge Areas/Experience
• 5 or more years in software or data engineering, with at least 1 year working with LLM-based or agentic systems in production.
• Hands-on experience configuring and deploying agents on at least one managed platform such as Cortex Agents, Claude API, Bedrock, or Azure AI Foundry, with a track record of connecting AI to real business processes rather than demos.
• Python, REST APIs, MCP and event-driven architectures. Experience with prompt design, agent behavior configuration, and tool and function calling within managed platform frameworks.
• Proficiency with at least one cloud data platform such as Snowflake, or Databricks, and a solid understanding of data access patterns and governance sufficient to design agents that respect data boundaries.
• Ability to build lightweight CI/CD pipelines for deploying and updating agent configurations and working knowledge of what major AI platform providers offer, where their limits are, and when it makes sense to combine them.
• Experience with front end development and design tools like Figma; enough to shape how AI-powered interfaces look and feel, even if design is not your primary craft.
• Working knowledge of GDPR, CCPA, and internal data governance requirements, with demonstrated ability to apply privacy-by-design principles in system architecture and to engage legal and compliance teams as a technical partner.
• Background in robotic process automation or business process management
• Multimodal agent workflows
• Open-source contributions in the AI and ML space
• A degree in Computer Science, Data Science, or a related field is preferred
• Relevant cloud or AI certifications such as AWS ML Specialty, Azure AI Engineer, or Snowflake SnowPro are a plus, though demonstrated hands-on experience carries more weight than credentials alone
• Demonstrates strong judgment in determining when to leverage managed AI platforms and when custom engineering solutions are more appropriate
• Works independently, defines practical approaches to ambiguous problems, and advances initiatives with a high degree of ownership
• Approaches privacy, security, and governance as core engineering responsibilities throughout the solution lifecycle
• Consistently considers fallback design, monitoring, and human oversight before production deployment, and communicates system behavior clearly to technical and non-technical audiences
• Bridges a strong user-centered mindset, with careful attention to the usability, clarity, and overall experience of the solutions built
• Maintains current knowledge of the evolving AI platform landscape and applies emerging capabilities thoughtfully to improve solution design and delivery
• Strong Microsoft Office skills, particularly Excel and PowerPoint
• Highly developed verbal and written communication skills with the ability to influence at leadership levels
• Demonstrable proficiency in data analysis and assessment abilities
• Highly organized, attention to details and strong follow-through
• A positive energetic attitude

CORE COMPETENCIES

• Accountability
• Adaptability
• Communication
• Critical Thinking
• Inclusion
• Professionalism
• Teamwork & Collaboration