Senior Engineering Manager, AI Workflows
Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Engineering Manager, AI Workflows based in the United States.
Join an innovative engineering team building the next generation of AI-powered application security solutions. As Senior Engineering Manager, AI Workflows, you will lead a team developing systems that combine traditional security scanning with large language models to detect, validate, and remediate software vulnerabilities. You will oversee the development of workflow orchestration infrastructure, SDKs, and ready-to-use automated security workflows. Balancing technical leadership with hands-on engineering, you will shape product strategy, guide execution, and help your team deliver meaningful improvements. This role offers the opportunity to influence how AI transforms cybersecurity while mentoring talented engineers and collaborating closely with product and engineering leadership.
Accountabilities:
In this role, you will lead the strategy, execution, and technical development of AI-driven security workflows while fostering an environment where engineers can grow and deliver high-quality solutions.
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Lead and mentor a team of 3–5 software engineers, supporting their professional development, technical growth, and ability to take on increasingly complex responsibilities.
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Define the team's strategic direction and develop a quarterly roadmap in partnership with product management and engineering leadership.
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Establish clear objectives and milestones, ensuring the team makes consistent progress toward short-term deliverables and long-term product goals.
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Oversee the development and evolution of an SDK for composing operations, an execution environment for running workflows, and a collection of predefined workflows.
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Guide the integration of traditional code security scanning tools and large language models to improve vulnerability detection, validation, and remediation.
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Make hands-on technical contributions to feature development while maintaining a deep understanding of the team's architecture, implementation, and challenges.
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Apply agile development principles and iterative planning practices to improve delivery, adaptability, and product quality.
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Coach senior engineers and emerging technical leaders, helping them develop the skills needed to mentor others and lead increasingly complex projects.
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Collaborate with platform, infrastructure, and security research teams to deliver reliable, scalable, and effective workflow capabilities.
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Continuously improve engineering practices, team execution, and technical decision-making to support the evolution of AI-native cybersecurity solutions.
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At least 3 years of experience leading software engineering teams.
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Strong software engineering fundamentals and the ability to make meaningful hands-on technical contributions.
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Experience defining technical direction, planning roadmaps, and delivering complex projects through iterative milestones.
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Familiarity with agile development principles and practices.
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A strong commitment to coaching, mentoring, and helping engineers and technical leaders grow.
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Ability to work effectively with product management, engineering leadership, and cross-functional technical teams.
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Strong problem-solving and decision-making skills, with the ability to balance strategic priorities and day-to-day execution.
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Expertise in at least two of the following three areas is strongly preferred:
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Public SDK or API design, development, and support.
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Data workflow orchestration technologies, such as Metaflow or Argo Workflows.
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Applying artificial intelligence to cybersecurity problems.
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Ability to communicate technical concepts clearly and align engineering work with broader product objectives.
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Willingness to work in a hybrid arrangement, attending the San Francisco office at least three days per week.
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Annual base salary: $197,000–$288,000 USD, depending on relevant experience, skills, qualifications, location, internal equity, and market conditions.
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Equity compensation: Equity opportunities designed to allow employees to share in the long-term value they help create.
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Potential additional compensation: Total compensation may include variable pay, depending on the applicable package.
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Competitive benefits: A market-aligned benefits program designed to meet or exceed local market standards.
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Location-specific support: Benefits tailored to local requirements and norms, with details provided through the benefits program.
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Fair and transparent compensation practices: Internal salary bands informed by market data and regularly reviewed to support consistent, competitive pay.
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Hybrid work environment: A combination of in-office collaboration and flexibility, with at least three days per week expected in the San Francisco office.
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Inclusive workplace culture: A respectful environment that values diverse backgrounds, experiences, and perspectives.
Benefits:
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Requirements:
The ideal candidate combines proven engineering management experience with strong technical judgment, a collaborative leadership style, and an interest in applying AI to complex security challenges.
Skills
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