
Lead Software Engineer
4 semanas atrás
Overview
Lead Software Engineer – Offshore
Location: 100% Remote / Telework
Employment Type: Full-Time
About the Role
We are looking for a Lead Software Engineer (Offshore) to lead our global engineering team responsible for building AI-first applications for our client. This is a hands-on leadership role combining architecture oversight, coding, and agile team management to deliver scalable, cost-effective digital solutions. The Lead will ensure reduced vendor dependency, retain IP, and accelerate delivery speed.
Key Responsibilities- Build and lead an offshore engineering team (mix of FTEs and partners) to deliver enterprise-scale applications.
- Collaborate with Product Management and Data Science teams to develop AI-native applications for clinicians and patients.
- Establish engineering best practices including CI / CD, test automation, code quality, and cloud-native deployments.
- Drive architectural decisions (microservices, APIs, security, scalability).
- Ensure cost-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.
- 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.
Education :
- Master’s Degree in Healthcare, User Experience, Human-Centered Design, or relevant field preferred.
Experience :
- 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.
- Full-time remote / telework.
- Computer-based work.
- Occasional travel for leadership meetings and team planning.
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