Position Overview:
ShyftLabs is seeking an experienced Engineering Manager to lead the development of cutting-edge AI applications and drive the technical excellence of our engineering teams. You will manage a dynamic team of 7-12 engineers while maintaining hands-on technical involvement in architecting and building scalable AI-powered enterprise products. This role requires a unique blend of people leadership, technical expertise, and process optimization to deliver innovative agentic AI products that transform how enterprises interact with their data.
ShyftLabs is a leading data and AI product company founded in early 2020 and works primarily with Fortune 500 companies. We deliver digital products built to help accelerate the growth of businesses in various industries, by focusing on creating value through innovation
Job Responsibilities:
- Drive architectural decisions for AI applications, enterprise integrations, and cloud-agnostic deployments across AWS, Azure, and GCP environments
- Collaborate with Technical Leads on system design, database optimization, API architecture, and scalable backend/frontend development
- Lead, mentor, and grow a team of 7-12 software engineers by providing technical guidance and structured career development
- Stay current with AI/ML technologies, agentic AI frameworks, and enterprise integration patterns
- Partner with Product Managers to translate business requirements into technical roadmaps and deliverable timelines
- Implement agile development processes, engineering best practices, and continuous improvement initiatives
- Coordinate with cross-functional teams including data, DevOps, and customer success teams
- Establish code quality standards, testing frameworks, and deployment pipelines
Basic Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, or related technical field
- 10+ years of software engineering experience with strong system design and scalable architecture fundamentals
- Minimum 2-3 years of engineering management experience leading technical teams in product companies
- Broad technical expertise spanning databases (SQL/NoSQL), message queues, RESTful APIs, backend/frontend technologies, and microservices architecture
- Basic familiarity with AI/ML concepts and understanding of AI application integration with enterprise systems
- Experience with cloud platforms (AWS, Azure, GCP), containerization, and modern deployment practices
- Proven track record of scaling engineering teams, mentoring junior engineers, and establishing technical processes
- Strong communication skills with ability to coordinate effectively with Product Managers, Technical Leads, and cross-functional teams
- Problem-solving aptitude with experience debugging complex distributed systems and making data-d