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Salary
≈ $29k – $76k per year (Estimated)
Location
In office (India)
Seniority
Staff · 8+ years exp

First seen by Alion on Oct 23, 2026.

Overview
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HiLabs is an AI platform that empowers healthcare organizations with data science tools to generate monetizable insights and identify hidden anomalies in their data, reducing financial losses caused by data errors. It hires AI engineers, engineering managers, frontend engineers, test engineers, technical program managers and data scientists, with its main engineering team in Bengaluru. The company is headquartered in Olney, Maryland, United States.

Job Description :

We are looking for an experienced Engineering Manager to lead engineering teams in designing, developing, and delivering scalable, reliable, and high-quality software solutions. The role involves driving technical execution, mentoring engineers, collaborating with product and data science teams, and ensuring timely delivery of business-critical product capabilities. The ideal candidate will combine strong software engineering fundamentals with people leadership, architectural judgment, and a hands-on approach to solving complex technical problems. Experience building data-intensive applications, AI-powered products, or enterprise platforms is highly desirable.

The core responsibilities for the job include the following :

Engineering Leadership and Team Management :

- Lead, mentor, and develop a team of software engineers, fostering a culture of ownership, collaboration, innovation, and continuous improvement.

- Establish clear goals, engineering priorities, and delivery expectations aligned with business objectives.

- Conduct performance reviews, provide regular feedback, and support career development and technical growth.

- Build a high-performing engineering team through effective hiring, onboarding, coaching, and retention practices.

- Promote engineering best practices, accountability, and a strong quality mindset.

Technical Strategy and Architecture :

- Drive the design and development of scalable, secure, maintainable, and high-performance software systems.

- Guide architectural decisions, technology selection, code quality, and engineering standards.

- Review technical designs and ensure solutions align with long-term product and platform objectives.

- Identify technical debt, performance bottlenecks, and system reliability issues, and drive appropriate remediation.

- Stay current with emerging technologies and evaluate opportunities to improve engineering efficiency and product capabilities.

Product Development and Delivery :

- Partner closely with Product Management, Data Science, Data Engineering, and other stakeholders to translate business requirements into technical solutions.

- Own engineering delivery across planning, development, testing, deployment, and production support.

- Break down complex initiatives into achievable milestones and manage dependencies, risks, and competing priorities.

- Ensure predictable delivery while maintaining high standards of code quality, testing, performance, and reliability.

- Track engineering metrics and continuously improve development processes, release cycles, and team productivity.

Software Engineering Excellence :

- Oversee the development of backend services, APIs, distributed systems, and data-intensive applications.

- Promote best practices in code reviews, automated testing, CI/CD, observability, and production monitoring.

- Drive system scalability, availability, security, and performance optimization.

- Establish effective incident management and root-cause analysis practices.

- Encourage automation and continuous improvement across the software development lifecycle.

Cross-Functional Collaboration :

- Work with product and business stakeholders to define technical roadmaps and prioritize engineering investments.

- Collaborate with AI/ML and Data Engineering teams to integrate intelligent capabilities into enterprise products.

- Communicate engineering progress, risks, and trade-offs clearly to senior leadership and relevant stakeholders.

- Align engineering execution with customer requirements, business priorities, and product strategy.

Key Success Metrics :

- Consistent and predictable delivery of engineering commitments.

- Improved product quality, system reliability, and application performance.

- Effective team development, retention, and engineering productivity.

- Reduction in technical debt and recurring production issues.

- Improved collaboration between engineering, product, AI/ML, and data teams.

- Successful delivery of scalable product capabilities aligned with customer and business needs.

Requirements :

- Bachelor's or master's degree in computer science, engineering, or a related technical field.

- 8+ years of experience in software engineering, with relevant experience managing or leading engineering teams.

- Strong programming experience in languages such as Python, Java, Go, or similar.

- Solid understanding of data structures, algorithms, object-oriented design, and software engineering principles.

- Experience designing and developing scalable backend systems, APIs, microservices, and distributed applications.

- Experience with relational and/or NoSQL databases and data-intensive systems.

- Strong understanding of cloud infrastructure, CI/CD, automated testing, and production deployment practices.

- Demonstrated ability to manage engineering delivery, resolve technical challenges, and develop engineering talent.

- Excellent communication, stakeholder management, and problem-solving skills.

- A strong engineering leader with sound technical judgment and a hands-on problem-solving mindset.

- Someone who can balance people management, architecture, and delivery execution.

- A leader who encourages ownership, accountability, and continuous learning.

- The ability to navigate ambiguity, manage competing priorities, and deliver results in a fast-paced product environment.

Preferred Qualifications :

- Experience building enterprise SaaS platforms or AI/ML-powered products.

- Exposure to healthcare technology, healthcare data, claims processing, or data quality solutions.

- Experience with AWS, Azure, or GCP, along with containerization and orchestration technologies such as Docker and Kubernetes.

- Familiarity with data engineering frameworks, large-scale data processing, or distributed computing.

- Experience with observability, reliability engineering, performance optimization, and production systems.

- Experience scaling engineering teams, improving development processes, and driving technical transformation.

Skills

Engineering Management, Distributed Systems, Python, Java, Golang, Data Structure, Algorithm, Microservices Architecture, NoSQL

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