Generative AI Engineer

Artificial Engineer

Location: Brazil, Mexico (Remote) – LATAM

Job Type: Full Time (No end date)

Salary: USD $35,000.00 Annually

Job Description

Key Responsibilities

Backend Development

• Architect and implement robust backend services and microservices for AI workflows.
• Design APIs with scalability, reliability, and security in mind.
• Optimize system performance for high throughput and low latency.

AI Engineering

• Integrate AI/ML models and LLM based applications into production systems.
• Experience in building end to end Gen AI based applications/solutions.
• Collaborate with data scientists to operationalize AI pipelines.
• Implement features for model evaluation, monitoring, and feedback loops.

DevOps & CI/CD

• Maintain automated pipelines for build, test, and deployment.
• Ensure compliance with code quality and security standards.
• Drive end-to-end design, building, and deployment of enhancements using Python, APIs, and Microservices.

Scalability & Performance

• Design systems for horizontal scaling and fault tolerance.
• Conduct performance tuning and load testing to ensure optimal resource utilization.

Foundational Services

• Build reusable frameworks and services that support multiple AI platform components.
• Implement secure handling of sensitive data (PHI/PII redaction).

Database & Data Management

• Work extensively with NoSQL databases (MongoDB, Cosmos DB).
• Ensure efficient data ingestion and retrieval for AI-driven applications.

Professional Qualifications

• Must have good communication and interpersonal skills.
• Ability to guide the team and deliver as an Individual Contributor without much supervision.

Required Skills

Strong SQL, Python, and Query Analysis skills are required for this role.

Programming

• Python
• JavaScript (React/Angular) with experience building basic UI using React or similar frameworks.
• Java or Go for backend.

Backend Expertise

• Microservices architecture.
• RESTful APIs.
• Distributed systems.
• Experience building data pipelines, APIs, and microservices.

AI/ML Tools

• TensorFlow
• PyTorch
• LangChain
• Vertex AI
• LLMs
• General Gen AI/Agentic AI experience.

Agentic AI & Google ADK

• Experience designing and implementing production-grade Agentic AI systems using Google ADK, including multi-agent workflows, tool-calling, and Model Control Plane (MCP) Server services (for exposing internal tools/APIs).
• Google ADK experience is highly preferred.

Cloud & Containerization

• GCP
• Kubernetes
• Docker
• GCP experience is highly preferred.

Databases

• NoSQL databases (MongoDB, Cosmos DB)
• SQL
• BigQuery experience is highly preferred.

Performance Optimization

• Profiling
• Caching strategies
• Query optimization
• Ability to identify performance bottlenecks and optimize performance using Gen AI.
• Observability experience.

Other

• Experience with design and support for multiple applications.