Senior Data/AI Engineer

Calling All Upstarters!

SENIOR DATA/AI ENGINEER 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 highly skilled Senior Engineer in Latin America with strong experience in data engineering and AI‑driven applications. The ideal candidate has a proven track record of building scalable backend systems, delivering production data pipelines, and implementing AI‑powered workflows.

This role is hands‑on and focused on designing, developing, and operating services that power intelligent, data‑driven features, including agentic workflows, retrieval‑augmented generation (RAG), and automated assistants, while ensuring that the underlying data foundations remain reliable, efficient, and secure.

You will collaborate closely with the Solution Architect and cross‑functional teams to deliver scalable, secure, and production‑ready systems across diverse technology stacks.

Responsibilities

AI‑Driven Backend Development

• Design and implement AI‑powered workflows such as agents, assistants, and tool‑enabled services.

• Build and maintain backend services using modern web frameworks and server‑side languages.

• Implement RAG‑style retrieval systems and contribute to prompt engineering and model interaction patterns.

• Integrate LLMs into production environments and develop scalable service layers around model inference and orchestration.

• Work with vector search technologies and embedding pipelines where needed.

Data Engineering & Analytics Enablement

• Design and operate ETL/ELT pipelines for batch, streaming, or hybrid workloads.

• Model data for analytics and application needs using best practices in schema design and storage optimization.

• Implement data quality, validation, auditing, and observability mechanisms.

• Ensure secure, reliable connectivity across cloud, on‑premise, and hybrid environments.

• Collaborate to define semantic business logic, reusable metrics, and shared data assets.

API & Integration Development

• Design and implement scalable APIs (REST, Queues, Events).

• Build integrations that connect AI systems to external applications, services, or platforms.

• Implement secure patterns for authentication, authorization, and secrets management.

• Ensure the overall backend architecture remains modular, maintainable, and extensible.

Database & Performance Optimization

• Write and optimize complex queries across relational and NoSQL databases.

• Design efficient schemas, indexing strategies, and caching solutions to support high‑performance AI/data workloads.

• Conduct load/performance testing and implement safeguards to meet system reliability targets.

• Data lake management

• Conduct and lead data Governance and data security best practices

Scalability, Security & Reliability

• Architect and implement systems for scalability, reliability, and security across backend and data layers.

• Add and maintain observability (logs, metrics, traces), alerting, and runbooks.

• Contribute to CI/CD, automation, and environment‑based deployments.

• Comply with privacy and security norms and rules such as PII, HIPAA, SOC 2 Type 2, or similar.

Cross‑Functional Collaboration

• Work with AI researchers to produce models and evaluate performance.

• Collaborate with the Solution Architect to align designs with long‑term architecture.

• Partner with Product to translate AI