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.
Originally posted on Himalayas