Middle AI/ML Engineer (GenAI, AWS)

TL;DR

Middle AI/ML Engineer (GenAI, AWS): Design, build, and deploy production ML solutions for clients with an accent on generative AI, LLM applications, RAG systems, and agentic workflows. Focus on optimizing models, implementing MLOps pipelines, and leveraging AI coding tools for efficient development.

Location: Medellín, Bogotá, Bucaramanga, Cali, Barranquilla (Colombia)

Company

AWS Premier Consulting Partner and AI consultancy with 15+ years of experience, 400+ engineers, partnering with Anthropic, Cohere, and AWS to build production AI for global enterprises.

What you will do

• Design and deliver ML pipelines from experimentation to production, build and optimize supervised, unsupervised, and generative AI models.
• Deploy and monitor models, track performance, prevent drift, contribute to LLM applications including RAG systems and agent workflows.
• Use AI coding tools daily, build with agent frameworks like Bedrock AgentCore, Strands, CrewAI, integrate or build MCP servers.
• Mentor junior engineers, provide code reviews, collaborate with DevOps, Data Engineering, and Solutions Architects.
• Stay current with ML research and GenAI, propose process improvements, participate in architectural discussions.

Requirements

• Solid ML knowledge: supervised/unsupervised algorithms, deep learning (CNNs, RNNs, Transformers), depth in NLP, CV, Recommendation, or Time Series.
• LLM/GenAI experience: building apps with OpenAI/Anthropic/Hugging Face, RAG design, vector DBs (OpenSearch, Pinecone), prompt engineering.
• Agentic engineering: proficient with AI coding tools (Claude Code, Cursor), building agents with orchestration frameworks, MCP understanding.
• AWS: SageMaker, Lambda, Bedrock; MLOps: MLflow/W&B, CI/CD, model monitoring; Python (async, OOP), pandas, NumPy, SQL, Docker.
• 1–3 years ML engineering experience, production ML deployment, team/client projects, Bachelor's/Master's in CS/Data Science/Math or equivalent; Fluent English (B2+).

Nice to have

• AWS certifications, Kubernetes, GraphRAG or custom MCP servers, open-source contributions on agentic systems.

Culture & Benefits

• Remote-first culture, work on projects across LATAM, North America, Europe.
• Premium AI tooling (Claude Code, Cursor, hirify.global AI toolkit), mentorship from seniors, clear growth path to Senior/Tech Lead.
• Learning budget for courses/certifications/conferences, health benefits, competitive salary based on competencies.