What You’ll Do (Core Responsibilities) 

• Build and deploy automations using tools such as n8n, UiPath RPA, Glean, and other agentic frameworks as adopted to streamline operations and improve workflow efficiency. 

• Develop, test, and maintain AI agents and workflow automations that connect data, systems, and teams to eliminate manual effort and improve accuracy. 

• Collaborate with Operations Enablement, Delivery teams, and AI leadership to translate high-level strategies and architectural designs into working, scalable solutions. 

• Analyze and improve processes before automating — identifying bottlenecks, redundancies, and optimization opportunities. 

• Implement event-driven workflows and API integrations to enable system-to-system communication and human-in-the-loop automation patterns. 

• Support orchestration and testing of agentic interactions, including Model Context Protocol (MCP) and Agent-to-Agent (A2A) patterns where applicable. 

• Document, test, and maintain automations with a focus on reliability, observability, and compliance with governance and security standards. 

• Collaborate cross-functionally to ensure automations align with enterprise data, workflow, AI and security policies. 

• Measure automation outcomes (time saved, error reduction, throughput gains, client & revenue impact) and communicate results to stakeholders. 

• Participate in showcases and demos to share automation successes, reusable patterns, and best practices across teams. 

What Success Looks Like (6-12 Month Outcomes) 

• Delivery of multiple high-value automations and AI workflows that significantly reduce cycle times, improve accuracy, or remove manual work within Delivery and Operations. 

• Creation of a shared library of automation patterns and connectors that can be reused across departments. 

• Demonstrated contributions to the AI-First Roadmap milestones, including process optimization, automation enablement, and operational transformation. 

• Widespread adoption of approved AI CoE toolchains (e.g., Glean, UiPath, n8n) across operational teams. 

• Embedded process improvement discipline within automation delivery. 

Qualifications 

• 2–4 years of experience in automation engineering, process improvement, or RPA development. 

• Proficiency with low-code/no-code automation platforms (n8n, UiPath, Power Automate, Make, Zapier, etc.) and basic scripting (Python, JavaScript preferred). 

• Working knowledge of APIs, event-driven architectures, and data integration. 

• Experience supporting process mapping or Lean/Six Sigma initiatives a plus. 

• Exposure to AI-driven workflows, enterprise search, or agentic orchestration frameworks preferred. 

• Strong analytical mindset with the ability to design, test, and iterate on automation solutions. 

• Excellent communication and documentation skills for global collaboration (Medellín, Pune, and other locations). 

Skills & Mindsets 

• Client-first mindset — passionate about creating, testing, and deploying secure, scalable, and cost-efficient solutions for internal and external clients. 

• Operational thinker — understands how processes and systems interact within Delivery and Operations. 

• Continuous improvement orientation — looks for ways to simplify, optimize, and evolve workflows before automating. 

• Collaborative executor — works seamlessly across technical and business teams. 

• Evidence-driven — measures results and uses data to guide refinement. 

Why This Role Matters Now 

As Ansira advances its AI-First Roadmap, the ability to execute automation at scale is essential to achieving measurable business transformation. The AI Automation Engineer bridges strategic vision with on-the-ground delivery — building automations that simplify complex workflows, enhance accuracy, and free up time for higher-value work. 

This role ensures that every automation and process improvement contributes directly to operational excellence and the scalable success of Delivery and Operations.