Weekday AI
Posted 6 days ago
Engineering Manager
AI Summary
Lead an onsite engineering team within Managed Risk to build and scale internal platforms, tools, and data-driven insights that improve developer productivity, security content, and customer outcomes in an AI-first engineering organization.
About this role
Min Experience: 10 years
Location: Bangalore
JobType: full-time
Requirements
This position will function as a Manager within **Managed Risk **, tasked with developing and expanding internal platforms, tools, and data-driven insights to enhance developer productivity, operational maturity, and customer outcomes. The Senior Manager will lead an onsite engineering team located in ** Bangalore, India **, collaborating closely with global engineering, product, and customer-facing teams to design systems and metrics that support a high-performing, AI-first engineering organization.
Key Responsibilities
The Managed Risk team manager should possess strong content and rules development skills (OVAL, SCAP), practical cloud experience (AWS, Kubernetes, Terraform), and a thorough understanding of the SDLC. Experience with AI tools is a valuable advantage. They will have a proven track record of managing high-performing teams to enhance product quality and strengthen the security content landscape, while also leveraging emerging AI/LLM technologies (AWS Bedrock Flows, Databricks MLFlow) for automating content generation from vendors as well as in-house development. A solid background in cybersecurity, specifically in **Vulnerability Management / Exposure Management **, is essential and non-negotiable. Additionally, the role requires the ability to guide architectural decisions, product roadmaps, and foster cross-functional collaboration across engineering and other departments.
Required Experience
At least 10 years of experience in software engineering roles, including a minimum of 2 years in engineering leadership or management positions, overseeing technical leads and developers.
Demonstrated expertise in building and scaling internal engineering tools or platforms utilized by multiple teams.
A strong hands-on background in **AWS cloud architecture **, encompassing distributed systems and data platforms.
A proven ability to define, implement, and operationalize engineering performance metrics and dashboards.
Preferred / Nice to Have
Familiarity with developer productivity, engineering excellence, or platform engineering domains.
Experience collaborating directly with customers or customer-facing teams to translate requirements into technical solutions.
Skills
vulnerability and threat modeling experience, rule development, content development, vulnerability and threat modeling experience, OVAL.