Gerente Asociado Arquitectura de AI

CWP Panama's AI Transformation & Advanced Analytics area is accelerating the adoption of intelligent automation across all business functions (commercial, network, customer experience, finance, operations). The AI Automation Architect is a senior individual contributor responsible for designing end-to-end AI-powered automation architectures that leverage AWS (Bedrock, SageMaker, Step Functions, Lambda, EventBridge) to transform complex business processes into scalable, governed, and measurable intelligent workflows.

This role bridges the gap between business objectives and technical execution, defining the technology stack, data pipelines, agentic AI frameworks, and deployment guardrails for enterprise-grade automation in a Telecom environment. The architect will map automation opportunities to eTOM process areas (Fulfillment, Assurance, Billing) and existing BSS/OSS systems to maximize ROI and minimize integration risk.

The ideal candidate combines deep technical expertise in cloud-native AI systems with strategic thinking, strong stakeholder management, and the ability to articulate complex architectures to both engineering teams and C-Level executives.

Architecture & Intelligent Workflows

• 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

Model & Stack Selection (AWS/Bedrock-Centric)

• Evaluate and select Foundation Models via Amazon Bedrock (Claude, Titan, Llama, Mistral) based on cost, latency, and task-fit analysis
• Define integration patterns: RAG (Bedrock Knowledge Bases), fine-tuning (SageMaker), prompt engineering, and hybrid approaches
• Design vector storage strategies using Amazon OpenSearch Serverless or Aurora pgvector for enterprise knowledge retrieval
• Conduct build-vs-buy analysis for automation components, favoring AWS-native services over third-party when comparable

System Integration (Telco BSS/OSS)

• 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

Governance, Security & FinOps

• Establish AI governance frameworks: model performance monitoring (drift detection), bias detection, explainability, and human-in-the-loop controls
• Ensure compliance with Panama data protection regulations (Ley 81 de Proteccion de Datos Personales) and ASEP Telecom regulatory requirements
• 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)

Stakeholder Management & Delivery

• 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
• Mentor data engineers and ML engineers on best practices for production AI system design

Education / Qualifications

• Bachelor's degree in Computer Science, Data Science, Software Engineering, or related technical field (required)
• Fully proficient in English and Spanish (written and verbal) - both languages used daily
• AWS certifications strongly preferred: Solutions Architect Professional, Machine Learning Specialty, or AI Practitioner

Experience

• 5+ years of experience in software architecture, ML engineering, or AI solutions design
• 1+ years hands-on with LLM-based systems (RAG, agents, prompt engineering, fine-tuning)
• Demonstrated 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

Technical 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
• Strong project management skills in Agile environments (Scrum/Kanban)