AI Engineer

Factspan; Brasil; Presencial; BRL 120 000 - 180 000; Tempo integral

Resumo da oferta

Factspan is seeking a Senior Backend AI Engineer to architect, build, and scale production-grade backend systems powering AI and ML workflows. You will design microservices, integrate LLMs and Gen AI applications, and lead the technical execution of end-to-end AI platforms.

The role emphasizes building robust APIs, ensuring performance, reliability, and security while collaborating with data scientists to operationalize AI pipelines and maintain DevOps practices for end-to-end deployment.

Qualificações

• Strong experience building production-grade backend systems for AI/ML workflows.
• Experience integrating LLMs and Gen AI applications into scalable platforms.

Responsabilidades

• Architect and implement backend services and microservices for AI workflows.
• Design scalable, secure, and reliable APIs for production use.
• Collaborate with data scientists to operationalize AI pipelines.
• Maintain automated CI/CD pipelines and ensure code quality.

Conhecimentos

SQL

Python

JavaScript

React/Angular

Go/Java

APIs

Ferramentas

MongoDB

Cosmos DB

BigQuery

Kubernetes

Docker

Google ADK

LangChain

Vertex AI

Descrição da oferta de emprego

About The Role

We are looking for a Senior Backend AI Engineer to architect, build, and scale production-grade backend systems that power AI and machine learning workflows. In this role, you will design microservices, integrate LLMs and Gen AI applications, and lead the technical execution of end-to-end AI platforms.

About The Role

We are looking for a Senior Backend AI Engineer to architect, build, and scale production-grade backend systems that power AI and machine learning workflows. In this role, you will design microservices, integrate LLMs and Gen AI applications, and lead the technical execution of end-to-end AI platforms.

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.
• Build end-to-end Gen AI applications and 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, including PHI/PII redaction.

Database & Data Management

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

Required Skills

Programming

Strong SQL, Python, and query analysis skills are required. Proficiency in Python, JavaScript (React/Angular) with experience building basic UI using React or similar frameworks, and Java or Go for backend development.

Backend Expertise

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

AI/ML Tools

TensorFlow, PyTorch, LangChain, Vertex AI, LLMs, and 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 such as MongoDB and Cosmos DB, SQL, and BigQuery experience are highly preferred.

Performance Optimization

Profiling, caching strategies, query optimization, and the ability to identify performance bottlenecks and optimize performance using Gen AI. Observability experience is expected.

Professional Qualifications

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