Gerente Asociado Arquitectura de AI

Job Summary

CWP Panama's AI Transformation & Advanced Analytics area is accelerating the adoption of intelligent automation across all business functions. The AI Automation Architect designs end-to-end AI-powered automation architectures leveraging AWS services to transform complex business processes into scalable, governed, and measurable intelligent workflows.

Responsibilities

• Design scalable AI automation architectures on AWS, leveraging Bedrock Agents, Step Functions, Lambda, and EventBridge for workflow orchestration
• Define agentic AI frameworks that combine Foundation Models with tool-use, memory, and multi-step reasoning capabilities
• Create reference architectures and reusable patterns for common Telco automation scenarios (e.g., network fault resolution, customer intent routing, billing disputes)
• Establish architecture standards, documentation practices, and technical debt management for AI systems
• Align AI automation architectures with existing Telco infrastructure: BSS (billing, CRM, order management) and OSS (network management, fault correlation, service assurance)
• Map automation opportunities to eTOM Level 2/3 processes to ensure organizational alignment and prioritization
• Design API layers and event-driven integrations between AI systems and legacy platforms
• Collaborate with IT and Network teams to ensure production-grade connectivity, latency requirements, and failover strategies
• Establish AI governance frameworks: model performance monitoring (drift detection), bias detection, explainability, and human-in-the-loop controls
• Define PII handling protocols, data classification, and access control policies for AI pipelines
• Implement FinOps practices for AI workloads: cost allocation, token usage monitoring, model cost-per-inference optimization
• Design security guardrails for LLM deployments (prompt injection mitigation, output filtering, audit trails)
• Collaborate with CDO, CTO, VP Network, VP Commercial, and Security teams to prioritize automation opportunities using Size-of-the-Prize vs. Complexity frameworks
• Translate technical architectures into executive-friendly narratives for business case approval and budget allocation
• Define success metrics (automation rate, cycle time reduction, cost-per-transaction, NPS impact) and measurement frameworks
• Lead technical design reviews, architecture decision records (ADRs), and proof-of-concept validations

Requirements

• Bachelor's degree in Computer Science, Data Science, Software Engineering, or related technical field
• Experience: 5+ years of experience in software architecture, ML engineering, or AI solutions design
• Hands-on experience with LLM-based systems (RAG, agents, prompt engineering, fine-tuning)
• Experience designing and deploying production AI/ML systems on AWS (Bedrock, SageMaker, Lambda)
• Experience with event-driven architectures and workflow orchestration (Step Functions, EventBridge, or equivalent)
• Track record of translating business requirements into scalable technical architectures with measurable ROI
• Experience working with cross-functional teams (engineering, product, business, security) in complex organizations

Qualifications

• Proficient in English and Spanish (written and verbal)
• AWS certifications: Solutions Architect Professional, Machine Learning Specialty, or AI Practitioner preferred
• Strong executive communication skills - ability to present architecture decisions and trade-offs to C-Level stakeholders
• Strong project management skills in Agile environments (Scrum/Kanban)

Skills & Abilities

• LLM & AI Orchestration: Proficiency with Amazon Bedrock (Agents, Knowledge Bases, Guardrails), and multi-model orchestration patterns
• Cloud Architecture: Deep expertise in AWS services (Lambda, Step Functions, EventBridge, API Gateway, SQS/SNS, DynamoDB, S3)
• Data Pipelines: Experience with vector databases (OpenSearch Serverless, pgvector), data lakes, and analytics platforms (Redshift, Athena, QuickSight)
• Infrastructure as Code: Terraform, CloudFormation, or CDK for reproducible AI infrastructure deployments
• Programming: Python (primary), with working knowledge of Node.js/TypeScript for serverless functions
• Strong executive communication skills - ability to present architecture decisions and trade-offs to C-Level stakeholders
• Complex change management and ability to drive AI adoption in organizations with legacy processes