AI Solutions Architect (AWS)

TL;DR

AI Solutions Architect (AWS): Designing and delivering end-to-end ML and agentic AI solutions for enterprise clients with an accent on AWS-based architecture, MLOps/LLMOps/AgentOps practices, and client-facing pre-sales solution design. Focus on architecting scalable RAG and multi-agent systems, integrating MCP, and producing technical proposals and POC demonstrations that win new business.

Location: Medellín, Antioquia; Cali, Valle del Cauca; Bucaramanga Metropolitan Area; Bogotá, Capital District

Company

hirify.global is a global AI and cloud consulting company helping enterprises turn AI and data into production-ready business solutions.

What you will do

• Lead technical discovery sessions and translate business problems into feasible ML solutions.
• Design end-to-end ML and agentic AI architectures and author technical proposals (scope, timeline, cost, and resources).
• Architect agentic AI solutions using autonomous decision-making, tool orchestration, and LLM-based workflows (including RAG agents, multi-agent systems, and tool-using agents).
• Plan MCP integration strategies and evaluate agent frameworks (e.g., LangGraph, Claude Agent SDK) for client use cases.
• Build POC demonstrations and advise on build-vs-buy decisions, including AgentOps needs (monitoring, evaluation, cost optimization).
• Serve as the primary technical point of contact across the project lifecycle and collaborate with delivery teams for smooth handoffs.

Requirements

• 6–8+ years of experience in ML or data science roles.
• Proven client-facing technical experience, including leading pre-sales or discovery engagements.
• Deep understanding of the full ML lifecycle from data ingestion through production deployment.
• Strong experience architecting LLM-based applications, including agentic systems, with agent design patterns, state management, and orchestration frameworks.
• Hands-on experience with the Claude ecosystem (Claude Code, Claude Agent SDK) and working knowledge of MCP architecture.
• Advanced AWS ML and data services experience (SageMaker, Bedrock, Lambda, ECS) plus serverless architecture experience (API Gateway, Step Functions).

Culture & Benefits

• Remote-first environment with flexible working hours aligned to your local time zone.
• Budget for medical insurance; paid sick leave, vacation, and public holidays.
• Clear career path toward Practice Leadership or Principal Architect roles.
• Training programs and full support for AWS and other professional certifications, plus a learning budget and conference attendance.
• Access to the latest AI tools and subscriptions; equipment and tools provided.