(1113180) Senior AI Agent Engineer

Position Overview: As AI continues to evolve, this role requires the ability to quickly learn new technology and build AI Agents to create alerts and automate workflows. The majority of the organization's structured data resides in Snowflake, and this position will apply AI to identify supply chain disruptions and drive corrective action to prevent backorders on parts. This role will focus on strengthening capabilities in agent architecture, orchestration, security, integrations, evaluation, and operationalization, while establishing best practices that can be reused across multiple AI programs and use cases. The Senior AI Agent Engineer will also share knowledge with and upskill current team members on the latest Dataiku Agentic AI technology. Key Contributions &

Responsibilities: Understand project and business objectives for each AI Agent initiative Write code in Snowflake and Dataiku to build AI Agents Test outputs and update code as needed to refine performance Establish reusable best practices for agent architecture, orchestration, and operationalization across AI programs Share knowledge and train team members on Dataiku Agentic AI technology

Education & Experience: Bachelor's degree in AI, Data Science, or Computer Science and 5-7 years of relevant experience, required Top 3 Skills Building AI Agents in Dataiku and Snowflake Cortex using structured data (critical) Workflow automation using Dataiku recipes and Python (programming logic) Experience with Lang Graph, Lang Chain, and CrewAI

Additional Skills Required: Multi-agent architecture and orchestration patterns Agent collaboration, planning, delegation, and workflow orchestration Reusable agent frameworks and reference architectures Security, access control, and governance Role-based access control (RBAC), personas, authorization models, and guardrails Auditability and compliance considerations Enterprise integrations and data access patterns Integration with Microsoft Teams, Share Point, email, PDFs, and enterprise data sources Event-driven and batch processing architectures API and workflow integration best practices Agent evaluation, testing, and observability Offline and online evaluation methodologies Groundedness, relevance, hallucination detection, and task-success measurement Automated regression testing, monitoring, observability, and performance tracking Prompt engineering and agent design patterns Prompt optimization techniques, reusable prompts, skills, tools, and agent design frameworks Human-in-the-loop workflows Approval processes for high-impact business decisions Escalation paths, feedback loops, and continuous improvement mechanisms Dataiku application development and user experience Dataiku Web Apps, UX design, and production-ready front-end development Best practices for enterprise adoption and usability Deployment, operationalization, and scalability Deployment automation, monitoring, and governance Cost and performance optimizationLLM selection and deployment strategies Latency, token consumption, and operational cost management Performance tuning and optimization best practices Team Player Desired Strong communication skills MCP experience in multi-agent systems to coordinate agent-to-agent communication is desired but not required 401(k) Dental insurance Vision Insurance Disability insurance Employee assistance program Health insurance Health savings account Life insurance Paid time off Paid Holidays Salary Expectations: $120,000-125,000 annually