AI Engineer – AI Architect

This is a fully remote position, open to applicants in Colombia.

📋 Description

• Define the architecture of AI systems that align with business goals and support long-term scalability.

• Transform ambiguous AI opportunities into well-structured technical methodologies.

• Create modular and extensible AI platforms that can accommodate both experimental and production workloads.

• Set standards for architecture decision records (ADRs) and technical documentation.

• Oversee the design and implementation of machine learning systems, model services, and inference pipelines.

• Develop scalable workflows for training, evaluation, and deployment.

• Architect strategies for data ingestion, feature engineering, and model serving.

• Ensure the reliability, observability, and performance enhancement of AI systems.

• Design and implement comprehensive AI pipelines and agentic orchestration frameworks.

• Establish LLMOps best practices, including CI/CD, prompt versioning, and real-time model observability.

• Optimize the performance of distributed inference systems and retrieval-augmented generation (RAG).

• Ensure the AI infrastructure meets security, compliance, and GPU/token cost-efficiency standards.

• Transition research prototypes into production-ready systems.

• Define evaluation metrics, validation procedures, and rollout strategies.

• Enhance iteration speed through tooling and automation.

• Mentor junior and mid-level AI engineers.

• Conduct code reviews and uphold engineering standards.

• Guide teams in balancing trade-offs related to performance, scalability, cost, and complexity.

• Collaborate with product, engineering, and executive stakeholders to shape AI roadmaps.

• Present technical strategies and system trade-offs to non-technical audiences.

• Align AI projects with business value and measurable outcomes.

⛳️ Requirements

• Applications from outside Colombia will not be accepted for this position.

• A minimum of 5 years of experience in AI/ML engineering or applied machine learning is required.

• Proven track record in designing and deploying production AI systems.

• Strong background in software engineering (Python or similar languages).

• Experience with distributed systems and scalable data architectures is essential.

• In-depth knowledge of MLOps, model lifecycle management, and AI infrastructure.

• Experience in building and maintaining machine learning pipelines and automated deployment workflows.

• Strong problem-solving capabilities and architectural decision-making skills.

• Demonstrated leadership and mentoring experience.

• Excellent communication skills for engaging with both technical and executive stakeholders.

• Nice to have: experience with generative AI, LLM systems, or retrieval-augmented architectures.

• Nice to have: exposure to multi-agent or agentic AI systems.

• Nice to have: experience with cloud-based AI platforms and infrastructure-as-code.

• Nice to have: background in consulting or professional services environments.

• Nice to have: experience designing AI systems in regulated or security-sensitive fields.

• Nice to have: hands-on AWS experience supporting cloud-native or AI/ML production systems.

• Nice to have: AWS certifications (Associate or Professional level) or equivalent practical expertise in AWS.

🏝️ Benefits

• Specialized training through the Advanced AWS Partnership and AWS Patterns Partnership.

• Early access to emerging cloud capabilities.

• Access to advanced engineering resources.

• Professional growth opportunities.

• Collaboration with experienced architects and senior engineers.

• Hands-on experience with complex problem-solving and real-world AI outcomes.