Highly Skilled AI Engineering Leader

Há 7 horas

Brasil beBeeSoftware Tempo inteiro R$150.000 - R$200.000
Job Overview

Lead Software Engineer - AI Applications

About the Role

This is a unique opportunity to lead a global engineering team responsible for building and deploying AI-first applications.

The ideal candidate will have expertise in architecture oversight, coding, and agile team management to deliver scalable, cost-effective digital solutions.

The successful candidate will ensure reduced vendor dependency, retain intellectual property, and accelerate delivery speed.

Key Responsibilities
  • Build and lead an offshore engineering team to deliver enterprise-scale AI-native applications.
  • Collaborate with Product Management and Data Science teams to develop and deploy AI-powered solutions for clinicians and patients.
  • Establish engineering best practices including continuous integration, test automation, code quality, and cloud-native deployments.
  • Drive architectural decisions (microservices, APIs, security, scalability).
  • Ensure efficient delivery while maintaining high quality and reliability.
  • Act as a hands-on leader, including coding, reviewing, and mentoring team members.
  • Align mobile platforms with organizational priorities to enhance patient engagement, provider efficiency, and enterprise growth.
Supervisory Responsibilities
  • Lead strategy, design, and execution of all mobile applications and digital tools across iOS, Android, and cross-platform environments.
  • Oversee end-to-end development lifecycle, including architecture, security, integration with clinical systems, and user experience.
  • Ensure performance, scalability, compliance, and alignment with organizational goals.
Qualifications
  • Master's Degree in Healthcare, User Experience, Human-Centered Design, or relevant field preferred.
  • 10+ years in software engineering with at least 3 years leading offshore teams.
  • Proven track record of delivering high-velocity, cost-effective software solutions.
Skills & Competencies
  • Expertise in AI/ML-enabled applications and API-first architectures.
  • Proficient in modern cloud tech stacks (AWS, Azure, GCP), Kubernetes, and microservices.
  • Strong collaboration with data scientists, engineers, and product stakeholders.
  • Ability to translate complex ML concepts into business outcomes.
  • Data-driven decision-making using KPIs and telemetry.
  • Advocates for ethical AI, bias mitigation, explainable models, and data privacy.
  • Ensures compliance with regulatory standards and internal governance frameworks.
Working Conditions
  • Full-time remote/telework.
  • Computer-based work.
  • Occasional travel for leadership meetings and team planning.

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