AI Architect - (LATAM CANDIDATES ONLY)

 

We are a U.S. company with a strong presence in LATAM and across 20+ countries around the world. Some of our key near-shore BPO services include: smart-sourcing, dedicated or cluster teams, managed IT services, software outsourcing, and top ERP & CRM solutions—driven by our practices across many industries, including Higher Education.

 

Responsibilities

-Design and define the end-to-end architecture for AI and machine learning solutions across the organization.

-Lead the design, development, and deployment of scalable AI systems, including predictive models, generative AI, and intelligent automation.

-Define AI platform architecture including data pipelines, model training environments, MLOps frameworks, and model deployment strategies.

-Collaborate with data scientists, data engineers, and software engineers to translate business requirements into scalable AI solutions.

-Evaluate and select appropriate AI/ML frameworks, tools, and cloud services to support enterprise AI initiatives.

-Establish best practices for model development, governance, monitoring, and lifecycle management.

-Design architectures for integrating AI capabilities into enterprise applications, APIs, and business workflows.

-Ensure AI solutions meet requirements for performance, scalability, security, and compliance.

-Lead technical decision-making related to model infrastructure, LLM integration, vector databases, and AI orchestration frameworks.

-Drive the adoption of responsible AI practices, including model explainability, bias mitigation, and ethical AI principles.

-Guide teams on AI architecture patterns such as RAG (Retrieval Augmented Generation), AI agents, and multi-model orchestration.

-Support AI innovation by evaluating emerging technologies and identifying opportunities for competitive advantage.

 

Qualifications

-Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.

-4- 6 years of experience in software engineering, data engineering, or machine learning systems.

-2+ years designing or implementing AI/ML architectures at scale.

-Strong experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.

-Experience designing solutions with Generative AI and Large Language Models (LLMs).

-Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud.

-Experience implementing MLOps practices including model versioning, CI/CD pipelines, monitoring, and governance.

-Strong understanding of data architectures including data lakes, feature stores, and real-time data pipelines.

-Experience with AI integration patterns such as APIs, microservices, and event-driven architectures.

-Knowledge of vector databases, embeddings, and semantic search architectures.

-Strong problem-solving skills and the ability to translate complex business problems into AI solutions.

-Excellent communication skills with the ability to explain complex AI concepts to both technical and non-technical stakeholders.

 -Advanced English proficiency skills (C1) required.