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O-I

Envigado, co

AI Solutions Engineer.

FULL TIMEDATA & ML

The AI Solutions Engineer designs, builds, deploys, and operates enterprise AI solutions that improve decisions and automate business processes across O-I. The role combines large language models, AI agents, enterprise data, APIs, applications, and workflows to deliver secure, governed, reliable, and measurable business outcomes. The engineer partners with business, data, security, and technology teams to move opportunities from concept to production and support adoption at scale.

PRINCIPAL ACCOUNTABILITIES

  • The role turns business opportunities into production-ready AI solutions, translating into clear AI use cases, requirements, business cases, success measures, and implementation plans.
  • Design and build AI agents, agentic workflows, AI-enhanced applications, decision-support solutions, and feedback loops for defined business processes.
  • Configure agent instructions, reasoning patterns, tools, memory, enterprise knowledge retrieval, structured outputs, and human-in-the-loop controls.
  • Determine when to use a single agent, multi-agent orchestration, traditional automation, analytics, or a combination of approaches.
  • Integrate AI solutions with Microsoft Fabric, enterprise data platforms, APIs, applications, documents, and business systems.
  • Develop reusable platform components, including agent templates, prompt patterns, tool libraries, API and MCP connectors, authentication patterns, monitoring capabilities, and source control frameworks with automated testing and deployment.
  • Ensure solutions are scalable, secure, reliable, observable, and aligned with enterprise architecture, data governance, cybersecurity, privacy, and responsible AI requirements.
  • Apply authorization boundaries, auditability, approval controls, and safeguards that prevent inappropriate autonomous actions, especially for consequential business transactions.
  • Elaborate data and business processes mining analysis to validate opportunities, identify root causes, and recommend practical implementation alternatives.
  • Monitor solution quality, data quality, adoption, business value, and operational performance; refine solutions based on evidence and user feedback.
  • Document solution designs, technical specifications, configurations, tests, controls, deployment procedures, training materials, and support requirements.
  • Support change management, user education, and responsible adoption of AI across the organization.
  • Manage multiple assignments, communicate effort estimates, status, and risks clearly, and provide production support during critical periods.
  • Learn and maintain comprehensive understanding of business functions and processes.
  • Stay current on relevant AI, agentic AI, automation, data, and software-engineering practices and recommend improvements to O-I's capabilities
  • Bachelor’s degree in artificial intelligence, data science, computer science, data analytics, software engineering, information systems, business intelligence, business analytics or related disciplines.
  • At least three years of relevant experience in AI engineering, software engineering, data engineering, analytics engineering, automation, or a closely related discipline.
  • Hands-on experience developing and deploying generative AI applications, AI agents, retrieval-augmented generation, or AI-enabled workflows and decision automation in a production environment.
  • Proficiency in Python and SQL; experience with APIs, software development practices, source control, testing, and CI/CD.
  • Experience with Azure and Microsoft AI technologies, such as AI Foundry, Copilot or comparable technologies (i.e. Claude, OpenAI, Grok); working knowledge of Microsoft Fabric or comparable Lakehouse and data-platform technologies.
  • Understanding of orchestration patterns, tool use, memory, knowledge retrieval, evaluation, guardrails, observability, and human approval patterns for AI agents.
  • Knowledge of enterprise data integration, data lakes, lakehouses, data warehouses, semantic models, dimensional modeling, ontologies, knowledge graphs, data mining, workflow automation, decision intelligence.
  • Understanding of identity, access control, data privacy, cybersecurity, responsible AI, and audit requirements for enterprise solutions.

We are an equal opportunity employer and welcome applications from all qualified candidates, including people with disabilities.

REPORTING RELATIONSHIPS

Position reports to the Reporting & Analytics Lead.

TRAVEL REQUIREMENTS

Minimal travel required for this position - less than 5%.

Hybrid Work Model: We provide a flexible work arrangement, requiring employees to be on-site at our office in Centro Comercial Viva, Envigado for 2 days per week, with the remaining 3 days working from home.

Pay
Not stated
Where
Envigado, co
Work
Not stated
Type
Full time
Posted
30 Oct, 2026
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