Senior Python Engineer

Jobtailor; São Paulo; Presencial; BRL 120 000 - 240 000; Tempo integral

Resumo da oferta

Jobtailor is seeking a backend/full-stack engineer focused on ML/AI services in São Paulo. You will design, implement, and operate cloud-native systems using GCP, Docker, and Kubernetes to deliver scalable ML-powered APIs.

You will collaborate with data scientists and product teams, applying SOLID principles, CI/CD, and declarative IaC to ship reliable, well-tested code in a fast-paced international environment.

Qualificações

• 4-6 years of experience focused on backend or full-stack development with Python.
• Proven track record designing and deploying cloud-native applications; GCP preferred, with AWS/Azure also considered.
• Experience with resilient microservices, event-driven architectures, and RESTful/gRPC APIs.
• Hands-on experience with Docker and Kubernetes.
• Deep understanding of SOLID principles and architectural patterns.
• Comfortable using AI tools to accelerate development throughput.
• Experience serving ML models or LLMs in production.
• Familiarity with RAG, vector search, or fine-tuning workflows.
• Exposure to AI orchestration frameworks such as LangChain and Google ADK.
• Knowledge of Terraform or Pulumi and CI/CD pipelines.
• Advanced English proficiency for written and verbal communication with an international team.
• Ability to learn new technologies quickly.
• Well-tested, documented, and monitored code.
• Collaborative mindset and delivery-oriented approach.

Responsabilidades

• Design, develop, and deploy end-to-end ML/AI services, from model integration to customer-facing APIs.
• Build event-driven and real-time architectures using Cloud Run, Kubernetes (GKE), Cloud Functions, and Pub/Sub within the GCP ecosystem.
• Integrate transformer-based models and LLMs into scalable inference pipelines, handling prompt engineering, output formatting, and error recovery.
• Lead design and whiteboarding sessions, translating business requirements into robust, scalable, and fault-tolerant technical architectures.
• Champion SOLID principles, CI/CD, observability, rigorous testing, and infrastructure as code (IaC).
• Collaborate with data scientists, Product Owners, and other engineers to align priorities and deliver iteratively.
• Understand the integration between the front end, database, and infrastructure to ensure performance and a strong user experience.

Conhecimentos

Python Development

Cloud-Native Applications

GCP Ecosystem

Microservices Architecture

CI/CD Implementation

Advanced English Proficiency

AI Tools

Ferramentas

Docker

Kubernetes

LangChain

Google ADK

Terraform

Pulumi

Pub/Sub

Cloud Run

Cloud Functions

Descrição da oferta de emprego

• Design, develop, and deploy end-to-end ML/AI services, from model integration to customer-facing APIs
• Build event-driven and real-time architectures using Cloud Run, Kubernetes (GKE), Cloud Functions, and Pub/Sub within the GCP ecosystem
• Integrate transformer-based models and LLMs into scalable inference pipelines, handling prompt engineering, output formatting, and error recovery
• Lead design and whiteboarding sessions, translating business requirements into robust, scalable, and fault-tolerant technical architectures
• Champion SOLID principles, CI/CD, observability, rigorous testing, and infrastructure as code (IaC)
• Collaborate with data scientists, Product Owners, and other engineers to align priorities and deliver iteratively
• Understand the integration between the front end, database, and infrastructure to ensure performance and a strong user experience

Requirements

• 4-6 years of experience focused on backend or full-stack development with Python
• Proven track record designing and deploying cloud-native applications; GCP preferred, with AWS/Azure also considered
• Experience with resilient microservices, event-driven architectures, and RESTful/gRPC APIs
• Hands-on experience with Docker and Kubernetes
• Deep understanding of SOLID principles and architectural patterns
• Comfortable using AI tools to accelerate development throughput
• Experience serving ML models or LLMs in production
• Familiarity with RAG, vector search, or fine-tuning workflows
• Exposure to AI orchestration frameworks such as LangChain and Google ADK
• Knowledge of Terraform or Pulumi and CI/CD pipelines
• Advanced English proficiency for written and verbal communication with an international team
• Ability to learn new technologies quickly
• Well-tested, documented, and monitored code
• Collaborative mindset and delivery-oriented approach

Core Competencies

Demonstrates expertise in designing and deploying cloud-native applications, particularly within the GCP ecosystem, while integrating ML models and ensuring robust, scalable architectures. Proficient in backend development with Python and experienced in implementing CI/CD practices and infrastructure as code.

Highest-signal resume keywords

• Python Development
• Cloud-Native Applications
• GCP Ecosystem
• Microservices Architecture
• CI/CD Implementation

ATS Optimization Keywords

Hard Skills

• Machine Learning
• Event-Driven Architecture
• RESTful APIs
• GRPC APIs
• Docker
• Kubernetes
• SOLID Principles
• Terraform
• Pulumi
• AI Tools

Soft Skills

• Collaborative Mindset
• Delivery-Oriented Approach
• Advanced English Proficiency

Industry Keywords

• Microservices
• Infrastructure as Code
• Prompt Engineering
• Error Recovery
• Scalable Inference Pipelines

Tools & Technologies

• Cloud Run
• Cloud Functions
• Pub/Sub
• LangChain
• Google ADK