Build and improve the security platform that protects our products and customer data, including identity, access management, and data compliance.
Compensation
The base salary range for this role is $167,000 - $230,000 per year. Base salary is just one part of your total rewards package. You may also be eligible for equity awards and an annual performance-based bonus.
Responsibilities
Build and improve the security platform that protects our products and customer data
Work with product and infrastructure teams to make security controls easy to integrate and meet changing security and product needs
Improve service reliability and performance through testing, monitoring, and incident response
Lead the design, launch, and continuous improvement of platform solutions, driving product vision, strategy, and execution across cross‑functional teams.
Compensation
Rs 2000000 - Rs 7000000 (ie INR 20-70 LPA)
Responsibilities
Own the product vision and strategy for API ecosystems and platform modernization initiatives.
Translate complex architectural requirements into clear, actionable product backlogs and release plans.
Partner with engineering, data science, and UX teams to design scalable, secure, and high‑performance API services.
Drive the adoption of AI, machine learning, and automation workflows to optimize operational efficiency and user experience.
Shape product analytics frameworks to capture usage, performance, and economic impact, informing continuous improvement.
Lead the development, operation and continuous improvement of network systems and automation capabilities underpinning the Janet Network, building a high‑performing engineering team and driving automation across network operations.
Locations (4)
London, England, United Kingdom
Bristol, England, United Kingdom
Manchester, England, United Kingdom
Oxford, England, United Kingdom
Compensation
Salary: Circa £70,000 per annum (negotiable based on experience) + comprehensive benefits package
Responsibilities
Build and mature the Network Systems function
Define team structure, roles, responsibilities and operating model
Lead and develop a vulnerability management program leveraging AI tools to identify, prioritize, remediate, and report on security vulnerabilities across DXC’s global infrastructure and applications.
Compensation
A reasonable estimate of the current compensation range for this position is $167,000 - $346,800.
Responsibilities
Own and run the enterprise vulnerability management lifecycle
Lead adoption and operation of AI-enabled vulnerability discovery tools
Define validation and deduplication of AI-generated findings
Coordinate with partner programs and trusted access arrangements
Build prioritization workflows for rapid exploitation timelines
For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.
Responsibilities
Design and build agentic systems
Partner with operational teams to understand workflows
Develop and deploy production-grade agentic systems
Design, build, and operate intelligent agentic systems that transform complex operational workflows at scale.
Locations (3)
San Francisco, California, United States
Seattle, Washington, United States
Sunnyvale, California, United States
Compensation
For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
Responsibilities
Design and build agentic systems
Partner with operational teams to understand workflows
Develop and deploy production-grade agentic systems
Build the data foundation powering Coveo's next generation of product innovation.
Responsibilities
Work with product engineering to turn questions about how users interact with Coveo into well-defined data models.
Build and maintain pipelines that process hundreds of millions of events a day, with tests and monitoring to keep them reliable.
Design batch and streaming transformations, from incremental dbt models in Snowflake to PySpark Structured Streaming jobs in Databricks, and choose the right one for each use case based on latency, cost and data volume.
Take ownership of complex data engineering initiatives, proactively improving data reliability, performance and maintainability while sharing your expertise with teammates.
Build AI agents that query our data models directly, and improve their answers by refining the models and definitions they rely on.
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