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AI Automation Engineer - Internal Platform

icon building Company : Phdata
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Job Description - AI Automation Engineer - Internal Platform

Join phData, a dynamic and innovative leader in the modern data stack. We partner with major cloud data platforms like Snowflake, AWS, Azure, GCP, Fivetran, Pinecone, Glean, and dbt to deliver cutting-edge services and solutions. We're committed to helping global enterprises overcome their toughest data challenges. 


phData is a remote-first global company with employees based in the United States, Latin America, and India. We celebrate the culture of each of our team members and foster a community of technological curiosity, ownership, and trust. Even though we're growing extremely fast, we maintain a casual, exciting work environment. We hire top performers and allow you the autonomy to deliver results.



Recognized as an award-winning workplace in the US, India, and LATAM


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 Attributes for Success



  • Consultative Mindset: Enjoys engaging with business teams to understand the “why” behind requests, asks thoughtful questions, and proposes solutions that address root causes.

  • Agent & Automation‑Oriented: Comfortable designing AI agents and automated workflows, and understands when to apply AI, when to apply automation, and when to combine both.

  • Ownership & Follow‑Through: Takes end‑to‑end responsibility for solutions—from initial assessment through launch and ongoing optimization.

  • Bias Toward Action: Moves work forward with urgency and purpose; does not let ambiguity stall progress and actively looks for ways to improve how work gets done.

  • Collaborative & Influential: Builds trust across teams and stakeholders; can communicate clearly, influence decisions, and navigate competing priorities.

  • Curious & Growth‑Oriented: Stays current with rapidly evolving AI/automation trends and tools; brings new ideas and approaches to the team.

  • Resilient & Adaptable: Thrives in a fast‑paced, evolving environment; stays composed under pressure and adjusts plans as circumstances change.


Why phData



  • Work on a high‑impact internal AI and automation platform that directly shapes how phData operates, sells, and delivers for its customers.

  • Help define how we run phData on data and AI, collaborating closely with stakeholders across Operations, Sales, Delivery, Finance, and IT.

  • Build on a modern cloud data and AI stack (Snowflake, AWS, Sigma Computing, Glean, GitHub Copilot, and more) with strong support for experimentation and improvement.

  • Collaborate with experienced data, analytics, and AI practitioners, and play a key role in expanding our internal AI and automation capabilities.

  • Enjoy a remote‑friendly culture with a distributed team across the globe.

Original job AI Automation Engineer - Internal Platform posted on GrabJobs ©. To flag any issues with this job please use the Report Job button on GrabJobs.
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