AI Automation Engineer - Internal Platform

AI Automation Engineer - Internal Platform

At phData, the Platform team builds and operates our internal Intelligence Platform, powering our Operations, Sales, Delivery, and Finance teams with data, analytics, and AI‑driven insights. We provide the core data and technology foundation that helps phData run efficiently and make better decisions every day.

We are seeking an AI Automation Engineer to join our Platform team. This role is a hands‑on technical partner to business groups across the organization. The ideal candidate has experience with AI agents and workflow automation and can assess feasibility, design solutions, and deliver measurable outcomes that create efficiencies and solve real business problems.

As an AI Automation Engineer, you will work directly with business stakeholders to understand their challenges, evaluate whether AI agents, automation, or a combination of both is the right approach, and then design and deliver end‑to‑end solutions. This is a growth‑oriented role for those passionate about using AI and automation to drive impact in how we run phData on AI.

What You’ll Do

Business Engagement & Feasibility Assessment

• 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.

AI Agent & Workflow Development

• 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.

Automation & Efficiency

• 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.

Development Practices & Quality

• 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.

Collaborative Delivery & Cross‑Functional Engagement

• 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.

Strategic Support & Growth

• 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.

Required Experience

• 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.

Prefer Any of the Following

• 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.

Key Attribu