AI Solutions Architect
Calling All Upstarters!
AI SOLUTIONS ARCHITECT WANTED!
We are Upstart 13. We are humble, hungry, and competent people who are radically changing the expectations and experience of outsourcing for all participants by challenging barriers that create inequality and by bringing down borders in technology for people everywhere. We’re all about delivering value and doing big things. We have become a game changer for teams around the world who look to Upstart’s services as a differentiator.
Job Description
We are seeking a Senior AI / Cloud Architect (Azure) located in Latin America to lead the technical vision and architecture for a strategic enterprise AI engagement built on the Microsoft Azure ecosystem. This is a senior, account-dedicated role responsible for defining and evolving the architecture of AI-enabled enterprise solutions, leveraging large language models, enterprise data, and Microsoft Azure services.
The role emphasizes integrating AI capabilities into scalable cloud-native systems rather than focusing purely on model development. This engagement is scaling from a single pilot team toward a multi-team, multi-tenant platform, requiring an architect who can design solutions that are secure, scalable, observable, and reusable across the organization.
The role is 70% architectural leadership and 30% hands-on technical contribution. You will partner closely with the Delivery Lead, engineering teams, and client stakeholders to define architecture, guide technical decisions, and ensure successful integration between AI capabilities and the client’s enterprise data ecosystem. Although this role has no formal people management responsibilities, it requires strong technical leadership and influence across both internal engineering teams and senior client stakeholders. As the primary architecture authority for the engagement, you will be responsible for maintaining architectural standards, decision records, and implementation guidance that enable long-term scalability while minimizing operational risk and knowledge silos.
Responsibilities
AI Architecture Leadership
Own the end-to-end architecture of AI-enabled systems, including backend services, data pipelines, and integration with AI components.
Define architectural standards, best practices, and reusable patterns across the platform.
Evaluate architectural trade-offs involving scalability, cost, performance, and maintainability.
Define the long-term platform strategy incorporating AI capabilities in collaboration with leadership.
Evaluate emerging AI technologies and frameworks, introducing them where they add business value.
Design reusable capabilities that support multi-team adoption and system scalability.
Maintain architectural decision records and technical documentation.
Agentic AI & Enterprise Data
Design system architectures that incorporate AI capabilities such as retrieval, orchestration, and service integration.
Guide the implementation of Retrieval-Augmented Generation (RAG) solutions leveraging enterprise data.
Design integrations between backend systems, APIs, data platforms, and AI services.
Define practical evaluation approaches for AI-enabled features, focusing on performance, reliability, and cost.
Design observability and monitoring strategies for AI-enabled applications.
Architect scalable data ingestion, processing, and indexing pipelines to support AI use cases.
AI Platform & Cloud Architecture
Design scalable Azure-based architectures leveraging cloud-native patterns and AI services where appropriate.
Collaborate with infrastructure and security teams to ensure secure and resilient deployments.
Partner with stakeholders on Responsible AI, privacy, and governance considerations.
Define deployment strategies across development, testing, and production environments.
Guide identity and authentication strategies for enterprise systems integrations.
AI Engineering & Delivery Enablement
Define best practices for application lifecycle management across AI-enabled systems.
Drive adoption of Infrastructure-as-Code, CI/CD pipelines, and automated testing.
Improve operational excellence through monitoring, observability, and deployment automation.
Establish reusable templates and architectural accelerators.
Hands-On Technical Contribution
Contribute to the design and implementation of backend services, APIs, and data pipelines that integrate AI capabilities.
Review architecture and code for distributed systems and AI integrations.
Support troubleshooting of complex production issues.
Contribute to proof-of-concepts and critical implementations.
Technical Leadership
Mentor engineers on AI architecture, LLM best practices, and enterprise AI design patterns.
Provide architectural guidance across engineering teams without formal authority.
Present architectural recommendations and technical roadmaps to senior client stakeholders.
Identify technical risks and capability gaps, recommending improvements to engineering leadership.
Qualifications
Technical Skills:
10+ years of professional experience in software engineering, including designing and architecting enterprise software solutions.
3+ years of experience designing and delivering production AI solutions leveraging Large Language Models.
Strong experience designing enterprise AI systems using Retrieval-Augmented Generation (RAG), agentic AI, tool calling, prompt orchestration, and multi-agent workflows.
Hands-on experience with Python and modern backend frameworks such as FastAPI or equivalent.
Experience with Azure AI services, including Azure AI Foundry, Azure AI Search, Azure OpenAI, or equivalent AI platforms.
Experience building AI applications using frameworks such as Semantic Kernel, AutoGen, Microsoft Agent Framework, LangGraph, LangChain, or similar orchestration frameworks.
Strong understanding of enterprise data integration, APIs, vector databases, semantic search, and knowledge management architectures.
Experience designing AI evaluation, monitoring, observability, and governance strategies.
Strong understanding of Azure architecture and cloud-native application design.
Experience implementing CI/CD pipelines and Infrastructure-as-Code.
Familiarity with cloud security, identity management, RBAC, and enterprise governance principles.
Soft Skills:
Strong technical leadership with the ability to influence engineering teams and executive stakeholders.
Ability to translate business objectives into scalable AI architectures.
Excellent problem-solving and architectural decision-making skills.
Strategic mindset combined with hands-on execution.
Excellent written and verbal communication skills.
Comfortable operating in client-facing environments with evolving requirements.
Ability to navigate ambiguity and establish technical direction for complex AI initiatives.
Bonus Skills:
Experience with Microsoft Fabric and Power BI semantic models.
Experience with Chainlit, Streamlit, or similar AI application frameworks.
Experience with AI evaluation tools such as Azure AI Foundry Evaluations, Promptfoo, Ragas, or DeepEval.
Familiarity with Responsible AI practices, model governance, content safety, and AI risk management.
Experience with vector databases such as Pinecone, Azure AI Search, Weaviate, or pgvector.
Azure certifications such as AZ-305, AI-102, or other AI/cloud architecture certifications.
Why Upstart13?
We put people first at Upstart 13! We believe the world is filled with amazing people and we are willing to go to great lengths to seek out others who share our values to join our cause of bringing down borders in technology for people everywhere.
We develop leaders at Upstart 13, we focus on what matters to do meaningful work, we own our shit, we stay curious, and we understand responsibility leads to giving. We do big things together!
Perks:
Job type: long-term, full-time job.
Fully remote.
USD competitive salary.
20+ Paid time off days.
Are you ready to join our cause? Be sure to ask, “why 13?”
- Department
- Software Development
- Role
- Software Architect
- Remote status
- Fully Remote
- Employment type
- Full-time
Colleagues
About Upstart 13
We strategize, solve, and build solutions to business problems with AI, data, and software—grounded in strategic clarity.
From boardroom to build, we connect strategy to execution using all available intelligence—human and otherwise—to help companies achieve efficiency, growth, and competitive advantage.