Senior AI Engineer

Argano

. Partner with clients to map business processes and workflows, identify automation opportunities, and translate them into AI agent solutions .

Posted 11/11/2026full-timeRemote • Mexico, ColombiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying AI agents on Azure, utilizing C# and Python for development, and applying DevOps practices. Proven ability to analyze business processes, implement automation solutions, and communicate effectively with diverse stakeholders.

Highest-signal resume keywords

AI Agent DevelopmentC# ProgrammingPython ProgrammingAzure AI FoundryDevOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Business Process AnalysisMicroservices ArchitectureMonolithic ArchitectureRetrieval-Augmented GenerationModel SelectionOrchestration ToolsVector DatabasesLLM EvaluationPrompt EngineeringEnterprise Implementations

Soft Skills

Communication SkillsStakeholder Management

Tools & Technologies

Azure AI SearchSemantic KernelLangChainAutoGenAWSGoogle Cloud

Certifications & Qualifications

Azure AI EngineerAWS Solutions Architect

Industry Keywords

Enterprise SecurityIdentity ComplianceAutomation OpportunitiesCloud PlatformsAI Practices

Tech Stack

Tools & technologies

AWSAzureCloudMicroservicesPython

About the role

Key responsibilities & impact

Partner with clients to map 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
Build Retrieval-Augmented Generation solutions using vector search, hybrid search, chunking strategies, and re-ranking
Lead and contribute to enterprise implementations from requirements through production rollout and ongoing support
Develop services and integrations primarily in C# and Python, following DevOps standards
Make architectural decisions across microservice and monolithic systems and integrate AI capabilities into client environments
Evaluate and select models, tools, and frameworks; test and monitor agent quality, safety, cost, and performance
Document solutions and communicate technical concepts to technical and non-technical stakeholders

Requirements

What you’ll need

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, including source control, CI/CD pipelines, infrastructure as code, and 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
Experience with agent frameworks and orchestration tools such as Semantic Kernel, LangChain, or AutoGen (preferred)
Familiarity with vector databases and search platforms such as Azure AI Search, pgvector, or Pinecone (preferred)
Experience with LLM evaluation, prompt engineering, and responsible AI practices (preferred)
Cloud or AI certifications such as Azure AI Engineer or AWS Solutions Architect (preferred)
Experience with enterprise security, identity, and compliance requirements (preferred)