Lead Software Engineer

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.
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
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.
Working Conditions:
Full-time remote/telework.
Computer-based work.
Occasional travel for leadership meetings and team planning.