AI Automation Engineer - Internal Platform

phData is a dynamic and innovative leader in the modern data stack, partnering with major cloud data platforms to deliver cutting-edge services and solutions. They are seeking an AI Automation Engineer to join their Platform team, where the role involves collaborating with business stakeholders to design and implement AI-driven solutions that enhance operational efficiency.

Responsibilities:

• Partner with business groups to identify AI/automation opportunities
• Assess feasibility (viability, data, integration, ROI, readiness) and help prioritize work across a portfolio of ideas
• Translate business problems into clear solution designs and implementation plans
• Communicate recommendations in a way that is understandable to both technical and non‑technical stakeholders
• Design, configure, and refine AI‑driven applications and agents (RAG, prompt design, agent workflows) for internal and occasional client use
• Build on platforms like Glean, Microsoft Copilot, and Snowflake Intelligence to orchestrate end‑to‑end agentic workflows (e.g., retrieval, reasoning, actions, and hand‑offs)
• Implement guardrails, monitoring, and evaluation patterns so agents are safe, reliable, and helpful
• Implement workflow automation using RPA, scripting, and low‑code/no‑code tools to remove manual, repetitive steps from business processes
• Integrate systems and data sources through APIs and connectors to enable smooth, end‑to‑end execution
• Operate and optimize automations over time for performance, reliability, and cost
• Build automation and AI workflows using modern engineering practices (version control, code review, testing, CI/CD), with a focus on maintainability and reusability
• Contribute to shared patterns, templates, and documentation that make it easier to roll out new AI agents and automations
• Work with cross‑functional teams (Platform, Analytics, Operations, Sales, Delivery, Finance, IT) to deliver solutions that align with business priorities
• Participate in agile planning and ceremonies to keep work visible, prioritized, and on track
• Share best practices on AI agents and workflow automation across the organization
• Track and experiment with emerging AI/automation tools, and bring forward ideas for pilots and improvements
• Help evaluate and operate secure, governed cloud AI services

Requirements:

• 4‑year Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field (or equivalent practical experience)
• 3+ years of professional experience building and deploying AI‑powered workflows and/or automation solutions in a business environment
• Hands‑on experience with AI‑driven tools or platforms (e.g., Glean, Microsoft Copilot, Snowflake Cortex/Intelligence, or similar) and/or building AI‑assisted workflows
• Demonstrated experience with process automation (e.g., RPA, Power Automate, scripting, workflow tools) to streamline business processes
• Experience integrating systems via APIs and connectors, and working with enterprise or SaaS applications
• Solid software or scripting background (e.g., Python preferred, or similar) sufficient to build and maintain production‑oriented workflows, automations, and simple services
• Familiarity with professional software development workflows: Git‑based source control, basic branching strategies, and code review
• Exposure to agile development practices and collaborative team environments
• Basic experience deploying or using cloud services and APIs for AI workloads (AWS, Azure, or Google Cloud)
• Strong analytical and problem‑solving skills, with a demonstrated ability to assess business processes and identify automation/AI opportunities
• Excellent communication skills for explaining technical concepts and trade‑offs to both technical and non‑technical audiences
• Ability to adapt to evolving technology landscapes and work collaboratively in multidisciplinary teams
• Familiarity with data engineering concepts (ETL/ELT, data pipelines, data warehousing)
• Familiarity with the Snowflake Data Platform and modern cloud data ecosystems
• Experience with business intelligence tools like Sigma Computing
• Experience in the data and AI professional services industry
• Experience conducting structured opportunity assessments, business cases, or cost‑benefit analysis for AI/automation initiatives
• Certifications in AI, RPA, workflow automation, or cloud platforms (AWS, Azure, GCP)
• Knowledge of data governance, responsible AI principles, and regulatory considerations for sensitive or regulated industries