Associate Director/Director , AI & Engineering
Syneos Health (company site, opens in a new tab)12+ yrsHyderabadHybridDirect career pageEst. 40–70 LPA
Posted 15h ago
Reach people at Syneos Health
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Syneos Health you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Own end-to-end engineering execution and delivery for complex enterprise products, platforms, or multiple teams including discovery, design, build, test, release, and operations.
- Translate product and business strategies into multi-quarter engineering roadmaps, investment priorities, staffing, and measurable outcome frameworks.
- Lead cross-team coordination, governance of engineering standards, AI adoption, and continuous improvement to drive customer and business value.
Minimum Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.
- Typically 12+ years of progressive software engineering and technology leadership experience with substantial people management responsibility.
- Proven leadership of multi-team delivery environments through full product development lifecycle and cross-functional dependencies.
- Strong technical breadth in architecture, cloud, APIs, distributed systems, DevSecOps, security, reliability, and operational governance.
Ideal Candidate Profile
- Experienced leader in managing multiple teams and technical managers with strategic ownership of engineering execution and delivery.
- Deep knowledge of AI/ML including Generative AI, Responsible AI, and AI-assisted engineering practices and governance.
- Skillful in applying business and technical metrics to improve engineering predictability, quality, operational excellence, and business outcomes.