Automation Architect (Agentic & RPA)

Location: Guatemala, El Salvador

Work style: Hybrid

Modality: Full-time

Who We Are

Welcome to TELUS Digital — where innovation drives impact at a global scale. As an award-winning digital product consultancy and the digital division of TELUS, one of Canada’s largest telecommunications providers, we design and deliver transformative customer experiences through cutting-edge technology, agile thinking, and a people-first culture.

With a global team across North America, South America, Central America, Europe, and APAC, we offer end-to-end expertise across eight core service areas: Digital Product Consulting, Digital Marketing Services, Data & AI, Strategy Consulting, Business Operations Modernization, Enterprise Applications, Cloud Engineering, and QA & Test Engineering.

About the Role

The Automation Technical Architect partners with Automation Strategists and Business Analysts to convert business process designs into detailed, build-ready technical architecture across RPA and Agentic AI solutions.

This role is responsible for assessing client environments, evaluating existing toolsets and infrastructure, and designing the optimal automation architecture for each process. The Architect ensures that every solution is fully specified — technically sound, scalable, secure, and aligned to the client’s current-state ecosystem.

The defining mandate of this role is clear: Produce system-level architecture designs that engineering teams can build from without redesign.

Key Responsibilities:

Business-to-Architecture Translation

• Work alongside Automation Strategists and Business Analysts to review process maps, BPMN diagrams, and opportunity assessments.

• Identify automation breakpoints and classify components as:

  • Deterministic (RPA / rules-based)

  • AI-driven / probabilistic (Agentic AI, LLM workflows)

• Convert business workflows into detailed technical architecture diagrams.

• Define orchestration logic, integration flows, and system dependencies.

Current-State Assessment & Architecture Alignment

• Assess client technical environments, including:

  • Existing RPA platforms

  • AI toolsets

  • API capabilities

  • Data architecture

  • Infrastructure and cloud environments

• Evaluate constraints and opportunities within current architecture.

• Propose optimal automation architecture aligned with client enterprise standards.

• Recommend tooling decisions when gaps exist.

This role must balance ideal design with real-world constraints.

Build-Ready Architecture Design (Primary Accountability)

• Produce detailed system-level architecture diagrams including:

  • System components

  • APIs and integration points

  • Data flows

  • Orchestration engines

  • Queues and event triggers

  • AI agents and memory layers

  • Security controls

  • Logging and monitoring frameworks

  • Dev/Test/Prod deployment topology

  • Sensitive data flows

  • External API calls (including LLM endpoints)

  • Data residency considerations

  • Storage and retention policies

• Clearly define integration contracts and system interactions.

• Clearly distinguish where PII is processed, stored, or transmitted.

• Specify compliance constraints impacting system design.

• Document non-functional requirements (scalability, performance, security).

If engineering has to reinterpret or redesign the architecture, this role has not succeeded.

Engineering Handoff & Technical Governance

• Conduct structured architecture walkthroughs with engineering teams.

• Provide clarification and technical guardrails during build.

• Review implementation for adherence to architectural design.

• Prevent scope drift and architectural degradation during delivery.

Communication, Facilitation & Technical Leadership

• Lead whiteboarding sessions with Business Analysts, Automation Strategists, engineers, and client stakeholders to translate business processes into technical solution designs.

• Facilitate structured architecture workshops to align on system boundaries, integration patterns, orchestration logic, and implementation approach.

• Clearly present and defend architectural decisions to engineering teams, enterprise IT stakeholders, and security review boards.

• Conduct detailed architecture walkthroughs prior to build to ensure engineering alignment and eliminate ambiguity.

• Communicate tradeoffs between deterministic automation (RPA) and AI-driven approaches, articulating rationale, risks, and scalability implications.

• Partner closely with delivery leads and engineering managers to ensure architectural intent is preserved throughout implementation.

• Contribute to team capability development by mentoring engineers and reinforcing architectural standards and best practices.

Hybrid RPA & Agentic AI Architecture

• Design integrated automation ecosystems combining:

  • RPA bots

  • Agentic AI workflows

  • LLM-based decision layers

  • Human-in-the-loop escalation

• Define guardrails, confidence thresholds, and evaluation mechanisms.

• Ensure AI solutions are observable, secure, and compliant.

Security, Data Privacy & Compliance Architecture

• Assess data sensitivity and regulatory constraints (e.g., GDPR, HIPAA, SOC 2, regional data residency requirements) during solution design.

• Embed privacy-by-design principles into automation and Agentic AI architectures.

• Define:

  • Data minimization strategies

  • Encryption in transit and at rest

  • Role-based access controls

  • Secrets management and credential vaulting

  • Logging and audit trails

• Design guardrails for LLM-based systems to prevent:

  • Data leakage

  • Prompt injection

  • Unauthorized data exposure

• Ensure AI and RPA solutions align with client security review processes and governance standards.

   

What Success Looks Like

• Architecture designs are accepted by engineering with minimal rework.

• Solutions deploy without mid-build structural redesign.

• Automation components are reusable and standardized.

• Client IT teams approve architecture without major revisions.

• Hybrid RPA + Agentic AI systems scale cleanly in production.

Required Qualifications:

• 7+ years of experience in solution architecture, intelligent automation, or enterprise system design, with a track record of delivering production-grade solutions.

• 3+ years of hands-on experience designing and implementing enterprise RPA solutions at scale.

• 1–3 years of experience integrating AI/LLM capabilities into automation workflows or enterprise applications.

• Demonstrated experience (multiple full lifecycle implementations) producing architecture designs that progressed from assessment through production deployment.

• Experience leading technical workshops, architecture whiteboarding sessions, and cross-functional design reviews in enterprise environments.

• Proven ability to translate business process diagrams (BPMN, swimlane, or equivalent) into detailed, build-ready technical architecture artifacts that engineering teams can execute without redesign.

• Hands-on experience designing and deploying enterprise automation solutions using at least one major RPA platform (UiPath, Automation Anywhere, or Blue Prism), including orchestration design, queue management, environment strategy (Dev/Test/Prod), and governance controls.

• Experience assessing current-state client environments, including existing toolsets, integration capabilities, infrastructure constraints, and security requirements, and designing fit-for-purpose automation architectures within those constraints.

• Experience integrating AI capabilities into automation workflows, including exposure to LLM APIs (OpenAI, Azure OpenAI, Vertex AI, or similar), OCR, NLP, or related services. Familiarity with concepts such as Retrieval-Augmented Generation (RAG), prompt design, human-in-the-loop workflows, and AI guardrails.

• Strong understanding of enterprise integration patterns, including RESTful APIs, microservices, middleware, event-driven architecture, and secure data exchange across CRM, ERP, data platforms, and legacy systems.

• Demonstrated experience designing solutions under data security and regulatory constraints (e.g., GDPR, data residency requirements), including encryption standards, access controls, credential management, logging, and auditability.

• Experience presenting and defending architectural designs to engineering teams, enterprise IT stakeholders, and security review boards.

• Strong communication and facilitation skills, with the ability to lead whiteboarding sessions, conduct architecture walkthroughs, and clearly articulate trade-offs between deterministic automation and AI-driven solutions.

• Demonstrated curiosity and ongoing learning in emerging automation and AI technologies.

What’s in it for you:

• Private medical and life insurance from day one

• Budget for professional growth (certifications)

• Schedule flexibility.

• Extra bonus based on performance.