Sr AI Engineer (ML & Data)

Jobgether; Brasil; Remote; BRL 180,000 - 280,000; Full time

Benefits offered by this job

Monthly USD service fee

20 business days PTO

Six local holidays

Caregiver time off

Fully remote (Latin America)

Job summary

Jobgether, acting on behalf of a partner, seeks a Sr AI Engineer (ML & Data) based in Brazil for a fully remote contract. You will design, deploy, and operate AI agents on large-scale datasets, collaborating with product and engineering teams across the enterprise.

You will work with Databricks, Python, and cloud platforms (AWS/Azure) to build production-ready AI features, monitor performance, and optimize costs.

Qualifications

• Professional background in machine learning or AI engineering.
• Proven experience delivering AI agents or LLM-powered features to production.
• Hands-on with Databricks and data pipelines.
• Cloud experience with AWS and/or Azure.
• Experience using evaluations to determine readiness and measure production effectiveness.
• Strong Python proficiency with LLM APIs.
• Familiarity with agent frameworks or SDKs and when not to use them.
• Experience coding agents as the primary development approach.
• Ability to work independently and communicate clearly with non‑engineering stakeholders.
• Advanced written and spoken English with overlap to US Eastern hours.

Responsibilities

• Design, build, and deploy AI agents and features end to end, from initial specifications through production.
• Deliver early iterations and continuously improve solutions based on feedback from real users.
• Collaborate with product, support, and engineering stakeholders to translate business challenges into clear technical requirements.
• Develop AI agents and machine learning features using large datasets and Databricks.
• Build and manage batch and streaming data pipelines to support AI-powered applications.
• Monitor production solutions, evaluate agent performance, manage costs, and troubleshoot failures.
• Promote best practices in agentic engineering to improve development speed, reliability, and team productivity.
• Use coding agents as primary development tools, defining tasks, reviewing generated outputs, validating results, and coordinating parallel workflows.
• Strengthen engineering processes through testing, CI, agent reviews, and reusable skills that prevent recurring issues.

Skills

Machine learning

AI engineering

Python

LLM APIs

Databricks

Cloud (AWS/Azure)

MCP

CI/CD

Independent work

Tools

Databricks

AWS

Azure

MLflow

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr AI Engineer (ML & Data) based in Brazil.

We are seeking a senior AI engineer with a strong machine learning background and hands‑on experience building, deploying, and operating AI agents on large‑scale datasets. In this remote contract role, you will develop production‑ready AI solutions that combine advanced agentic workflows with enterprise data infrastructure. You will work with extensive datasets, including millions of compliance documents and more than a decade of tolling, inspection, safety, and vehicle information. Your work will support AI‑powered products serving the trucking and fleet compliance industry, with a direct impact on revenue, operational safety, and regulatory compliance. You will collaborate with cross‑functional stakeholders in a fast‑moving, entrepreneurial environment focused on practical outcomes and continuous improvement. The role offers significant ownership, technical autonomy, and the opportunity to shape how AI is built and deployed at scale.

Accountabilities

• Design, build, and deploy AI agents and features end to end, from initial specifications through production.
• Deliver early iterations and continuously improve solutions based on feedback from real users.
• Collaborate with product, support, and engineering stakeholders to translate business challenges into clear technical requirements.
• Develop AI agents and machine learning features using large datasets and Databricks.
• Build and manage batch and streaming data pipelines to support AI‑powered applications.
• Monitor production solutions, evaluate agent performance, manage costs, and troubleshoot failures.
• Promote best practices in agentic engineering to improve development speed, reliability, and team productivity.
• Use coding agents as primary development tools, defining tasks, reviewing generated outputs, validating results, and coordinating parallel workflows.
• Strengthen engineering processes through testing, CI, agent reviews, and reusable skills that prevent recurring issues.

Requirements

• Professional background in machine learning or AI engineering.
• Proven experience delivering AI agents or LLM‑powered features to production, with real users actively relying on them.
• Hands‑on experience with Databricks, including developing and managing batch and streaming data pipelines.
• Cloud experience with AWS and/or Azure.
• Experience using evaluations and data to determine when AI agents are ready for deployment and measure their effectiveness in production.
• Strong Python proficiency, with practical experience building solutions using LLM APIs and MCP.
• Familiarity with agent frameworks or SDKs, including the ability to identify when a framework is unnecessary.
• Established experience using coding agents as the primary approach to software development.
• Ability to work independently, gather requirements from non‑engineering stakeholders, communicate clearly, and provide specific, honest answers.
• Advanced written and spoken English, as the role operates entirely in English.
• Availability to overlap with US Eastern business hours, approximately 9 AM–5 PM.
• Willingness to participate in hands‑on technical interviews, including detailed discussions of solutions previously built and shipped.

Nice to have

• Experience owning deployment processes, including CI/CD, infrastructure as code (Terraform), and monitoring.
• Experience processing complex documents with LLMs, including OCR and data extraction.
• Familiarity with MLOps tools such as MLflow.
• Background in logistics, transportation, or compliance.

Benefits

• Monthly service fee paid in USD.
• 20 business days of paid agreed time off annually.
• Six local holidays.
• Caregiver time off.
• Fully remote work arrangement, with the flexibility to work from anywhere in Latin America.
• Dynamic and entrepreneurial work environment.

We appreciate your interest and wish you the best!

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