Back
Tier-1 brand, generic software engineer title, mid-level experience, and metro location increase applicant density.
Production ML, data engineering and cloud skills transferable, healthcare/regulatory experience increases domain specificity.
Mandatory 3+ years, C++/Python, AWS, low-latency and cloud-native requirements tighten filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop, implement, and maintain AI solutions and robust data processing pipelines with a focus on scalability, performance, and compliance.
Manage complex data workflows including ingestion, transformation, storage ensuring data integrity and reliability for AI and analytics projects.
Coordinate deployments, monitor AI model performance, and collaborate with stakeholders to deliver projects aligned with business goals.
Bachelor's or Master's degree in Computer Science, Engineering, or Information Technology.
Minimum 3 years of software development experience covering full SDLC activities including analysis, development, testing, and problem resolution.
Strong proficiency in C++, Python, microservices, database design/tuning (MongoDB or similar), and AWS experience is mandatory.
Experience developing low latency, high throughput applications and working knowledge of deployment including CI/CD pipelines.
Experience working in agile and entrepreneurial environments with strong ownership and rapid iteration skills.
Capability to mentor and provide technical guidance to engineering teams and manage cross-disciplinary collaboration.
Familiarity with cloud-native data warehouses, automation testing frameworks, and regulated environments (e.g. medical devices) is a plus.