Senior AI Engineer (AI)

TL;DR

Senior AI Engineer (AI): Designing and delivering production-ready AI systems to power intelligent product experiences with an accent on implementation quality, scalability, and reliability. Focus on building LLM-powered features, retrieval systems, and agentic workflows in production.

Location: Must be based in Colombia or Brazil

Company

hirify.global is a product company focused on building intelligent product experiences across its platform.

What you will do

• Design, build, and operate AI systems and services for customer-facing products.
• Implement LLM pipelines, retrieval systems, and agentic workflows in production.
• Collaborate with product and engineering teams to transform business needs into shipped AI features.
• Improve observability, performance, reliability, and cost efficiency of AI systems.
• Contribute reusable components and high-quality engineering practices across the team.
• Troubleshoot production issues and participate in on-call support rotations.

Requirements

• Proven experience building and shipping customer-facing AI systems in production.
• Strong expertise in Generative AI, LLMs, RAG, evaluation, orchestration, and cost/latency optimization.
• Experience building agentic or multi-step AI systems with tools and external integrations.
• Strong programming skills in Python.
• Solid software engineering fundamentals in testing, observability, and production support.
• Ability to independently drive technical solutions from design through production rollout.

Nice to have

• Experience with AWS services (EC2, EKS, RDS, ELB), Terraform, and CI/CD setup.
• Proficiency with LangChain, LangGraph, LlamaIndex, or similar orchestration frameworks.
• Experience with AWS Bedrock, SageMaker, or other managed AI platforms.
• Knowledge of vector databases, embeddings, semantic search, and retrieval design.
• Experience mentoring engineers or owning technically complex projects.

Culture & Benefits

• Culture of empowerment where every person is heard and encouraged to shape the environment.
• Emphasis on strong engineering practices and high-quality delivery.
• Collaborative atmosphere working across product, engineering, and data teams.