Senior AI Engineer

About the Role

We are looking for a Senior AI Engineer who combines strong software engineering fundamentals with hands-on experience building AI agents for real business problems. In this client-facing role, you will work directly with customers to understand their business processes and workflows (finance, customer service, supply chain), then design, build, and deploy enterprise-grade AI solutions that automate and improve them. This role is based in Mexico or Colombia. 

The ideal candidate is an organized self-starter who is equally comfortable in a discovery workshop with a client and in a code editor building agent orchestration, retrieval pipelines, and cloud infrastructure.

What You'll Do

• Partner with clients to map existing business processes and workflows, identify automation opportunities, and translate them into AI agent solutions.
• Design, build, and deploy AI agents on Azure (including Azure AI Foundry), with a working understanding of agent runtime, orchestration, models, and tooling.
• Build Retrieval-Augmented Generation (RAG) solutions, applying appropriate retrieval techniques (e.g., vector search, hybrid search, chunking strategies, re-ranking) to ground model responses in enterprise data.
• Lead and contribute to enterprise implementations, from requirements through production rollout and ongoing support.
• Develop services and integrations in multiple languages, primarily C# and Python, following DevOps standards (CI/CD, infrastructure as code, automated testing, monitoring).
• Make sound architectural decisions across microservice and monolithic systems, and integrate AI capabilities into existing client environments.
• Evaluate and select models, tools, and frameworks; test and monitor agent quality, safety, cost, and performance.
• Document solutions and communicate technical concepts clearly to both technical and non-technical stakeholders.

Required Qualifications

• Proven experience working directly with clients, with strong communication and stakeholder-management skills.
• Background in business process or workflow analysis in at least one domain such as finance, customer service, or supply chain.
• Software development background with experience in both microservices and monolithic architectures.
• Proficiency in multiple programming languages, including C# and Python.
• Working knowledge of DevOps standards and practices (source control, CI/CD pipelines, infrastructure as code, observability).
• Experience building RAG solutions and applying retrieval techniques.
• Experience building AI agents on Azure, including Azure AI Foundry.
• Hands-on experience with at least one additional major cloud platform (AWS or Google Cloud); working experience with at least two of the three major clouds.
• Understanding of agent runtime, orchestration, model selection, and tooling.
• Experience delivering enterprise implementations.
• Highly organized, self-directed, and able to manage multiple priorities with minimal supervision.

Preferred Qualifications

• Experience with agent frameworks and orchestration tools (e.g., Semantic Kernel, LangChain, AutoGen).
• Familiarity with vector databases and search platforms (e.g., Azure AI Search, pgvector, Pinecone).
• Experience with LLM evaluation, prompt engineering, and responsible AI practices.
• Cloud or AI certifications (e.g., Azure AI Engineer, AWS Solutions Architect).
• Experience with enterprise security, identity, and compliance requirements.

Core Competencies

• Client focus: Builds trust, listens well, and turns business needs into practical solutions.
• Technical breadth: Comfortable across languages, clouds, and architectural styles.
• Ownership: Takes initiative and drives work from idea to production.
• Organization: Plans carefully, tracks details, and delivers on commitments.
• Communication: Explains complex AI concepts clearly to varied audiences.