Were looking for an Engineering Team Lead, who will be responsible for the foundational infrastructure framework used by all our company engineering teams to build, deploy, and operate AI agents safely in production. We are building the "operating system" for AI at our company, covering agent sessions, memory management, tool orchestration, durable execution, and multi-tenant isolation. You will lead a high-impact team of 5 engineers to create the runtime and platform that defines the future of autonomous enterprise intelligence.
Youll Own:
Agentic Framework Architecture: Designing and building our companys internal agentic framework, leveraging and integrating industry-standard tools such as LangChain, LangSmith, ADK, and similar ecosystems.
Evaluation and Quality Systems: Building evaluation frameworks and workflows for AI agents, including offline and online evaluations, quality metrics, regression detection, and experimentation infrastructure.
Team Leadership & Mentorship: Leading a squad of 3-4 senior engineers, fostering a culture of technical excellence, and managing end-to-end delivery in a fast-paced environment. You will spend approximately 50% of your time hands-on, architecting core systems and reviewing code, and 50% leading the team, mentoring engineers, and aligning with cross-functional stakeholders.
Observability, Monitoring, and Guardrails: Providing the organization with robust observability capabilities for AI agents, including tracing, logging, monitoring, cost tracking, and safety guardrails to ensure reliable and responsible usage.
Developer Enablement Platforms: Creating APIs, SDKs, and abstractions that enable product teams to easily build, test, and operate agents while adhering to platform standards.
Cross-Language Integrations: Designing integrations and tooling across Python and Java to enable seamless adoption of the AI framework within our companys broader backend ecosystem.
Youll Solve:
Agent Lifecycle and Orchestration Complexity: Managing agent execution, tool usage, memory, workflows, and failure modes in production-grade systems.
AI System Reliability at Scale: Ensuring agents remain observable, debuggable, and safe as usage scales across teams and products.
Evaluation and Drift Challenges: Detecting quality regressions, model behavior changes, and unintended agent behaviors through robust evaluation and monitoring systems.
Platform Adoption Friction: Balancing flexibility with guardrails so teams can innovate quickly without compromising reliability, security, or cost controls.
Youll Impact:
Company-Wide AI Enablement: Empowering every engineering team at our company to build agent-based solutions faster, with higher quality and confidence.
Foundational AI Infrastructure: Establishing the core frameworks, evaluations, and observability standards that all AI agents at our company will rely on.
AI Safety and Quality Bar: Raising the bar for how AI systems are evaluated, monitored, and governed across the company.

Were looking for a Hands-on AI & Data Engineering Manager to lead a team building intelligent, large-scale consumer experiences powered by AI. In this role, you will lead engineers developing AI-driven products, work closely with data scientists, product managers, and designers, and ensure that AI capabilities-from LLMs and agents to product data insights-are translated into reliable, scalable production systems. You will be responsible not only for delivering AI features, but also for analyzing product data and user behavior to continuously improve AI performance and product outcomes. This is a technical leadership role combining engineering management, architecture ownership, AI product development, and data-driven decision making.
Key responsibilities:
Lead a team of data scientists, data engineers and product analysts
Own the delivery of AI-powered product capabilities, from research and experimentation to production and operation
Drive excellence, code quality, and best development practices
Provide technical direction and hands-on guidance for complex AI systems
Drive the integration of LLMs, AI agents, and intelligent workflows into core consumer experiences
Ensure AI solutions are safe, scalable, observable, and continuously improving
Lead initiatives around product data analysis and experimentation
Analyze user interactions with product features to improve accuracy, UX, and business impact
Partner with product teams to define metrics, dashboards, and experiments that guide product improvements
Design system architectures for AI-enabled applications at scale
Evaluate and select technologies for AI platforms and data pipelines
Guide the development of prompt engineering frameworks and centralized prompt management
Ensure robust monitoring, evaluation, and feedback loops for AI outputs
Translate product and business goals into technical roadmaps and execution plans
Drive alignment between AI capabilities and measurable product outcomes.

We're looking for a VP R&D to build both the technical foundation and the engineering organization behind that platform. This is not pure people management, and it's not a chief-architect role in disguise. It's a rare combination: a deeply technical leader who can challenge the strongest engineer in the room on architecture, and who also builds an organization where talented people grow, decide independently, and own outcomes end to end.



What You'll Own

Technical direction: Define architecture and technical strategy with the CTO, Product and AI leadership. Make real tradeoffs between speed, simplicity, reliability and long-term scale. Stay deep enough to lead architecture reviews, surface hidden risks, and tell the difference between an impressive demo and a dependable production system.
An enterprise-grade agentic platform: Agent orchestration, planning and tool use governed knowledge and policy representation retrieval, context and memory evaluations human review and escalation permissions, identity, security and auditability reliability and observability cost, latency and model performance enterprise integrations.
The R&D organization: Design the structure for the company's next stage. Recruit exceptional engineers and engineering leaders at a consistently high bar. Grow managers and senior ICs who own major domains independently. Set clear expectations, feedback and performance standards - and build a leadership bench so the org doesn't depend on a handful of people.
Autonomy with accountability: Define outcomes, decision boundaries and interfaces, then push decisions as close to the problem as possible. Autonomy that produces better and faster decisions - not ambiguity, duplicated work, or diffused responsibility.
Velocity and quality together: An operating model that moves fast without normalizing instability. Better planning, testing, deployment, observability and incident learning. AI-native development as real leverage for every engineer, with clear standards for security, correctness and human judgment.
Business impact: Shape the roadmap with Product rather than receiving requirements. Join strategic customer conversations where technical leadership builds trust and unblocks adoption. Operate as a company leader, not only a function leader.

we are building an agentic development lifecycle, an infrastructure of autonomous agents that work alongside our engineers to accelerate and improve how we build software. Our goal is to ship faster, with higher quality, and to continuously tighten the feedback loop between what the agents produce and what engineering actually needs. Over time, this system should compound: every improvement makes the next one easier to reach.
we are an enterprise secure browser used by some of the largest organizations in the world. It's a complex, multidisciplinary product spanning browser core, frontend, extensions, and backend services, and it runs at scale for customers who need it to always work. The bar for what we ship is high. That means whatever agentic infrastructure we build has to meet the same standard. We're not here to vibe code our way to production.
We're looking for an AI Engineer with a product builder's mindset. You have real experience with AI and agentic workflows, and you know how to take a complex project from idea to adoption, technically and organizationally. That means working across teams, aligning with security, infrastructure, and other engineering groups, and understanding that building the system is only half the job. Getting people to trust it is the other half.
We aren't looking for a conventional senior developer; we need someone whose mindset is adapted to technical challenges that didn't even exist 18 months ago.

Were looking for an experienced Full Stack Team Leader to lead the engineering team behind our Customer Portal-the central platform used by every customer across all of our products. This role reports directly to the VP R&D and combines technical leadership with product ownership, cross-functional collaboration, and execution.

As the engineering leader of the Customer Portal, youll shape one of the companys most strategic products, ensuring customers enjoy a seamless experience throughout their entire journey with us. Youll lead a talented team, drive technical excellence, champion AI adoption, and collaborate closely with stakeholders across Product, Marketing, Customer Success, Support, Sales, and Design to deliver customer-facing capabilities with direct business impact.

Were looking for someone who doesnt wait for direction. You naturally identify opportunities, challenge the status quo, and drive initiatives from idea to execution. You inspire your team through technical leadership, raise the engineering bar, and continuously look for better ways to build products and develop people.

What Youll Do
Lead, mentor, and grow a team of Full Stack Engineers, fostering a culture of ownership, accountability, innovation, and continuous improvement.
Own the technical execution and delivery of the Customer Portal roadmap, serving customers across all our products.
Partner closely with Product Management and business stakeholders to translate strategic objectives into scalable technical solutions.
Collaborate daily with Product, Marketing, Customer Success, Support, Sales, and Design to deliver an outstanding customer experience.
Lead architectural decisions, ensuring the platform remains scalable, secure, maintainable, and ready for future growth.
Drive engineering excellence by establishing high standards for code quality, testing, observability, performance, reliability, and operational excellence.
Champion AI-first engineering practices by driving adoption of AI tools and workflows that improve developer productivity, code quality, and delivery velocity.
Proactively identify opportunities to improve the product, engineering processes, and team effectiveness. Bring ideas, challenge existing approaches, and lead meaningful technical and organizational improvements.
Lead planning, prioritization, estimation, and execution while balancing business priorities with technical investments.
Remove blockers, manage technical risks, and create an environment where the team can consistently deliver high-quality outcomes.
Stay hands-on when needed, contributing to architecture, design, code reviews, and implementation of complex features.

Req ID: 20153

As a Machine Learning Engineering Manager, you will lead a team focused on the foundational ML & Data layers to power the ranking & recommendation systems in scope. You will drive the development of robust data & ML pipelines at scale, lead the implementation of the tools for ML scientists to test and productionize advanced ML RecSys solutions.

As a technical manager of Machine Learning Engineers and Data engineers, you should be passionate about technology, keep up to date with recent breakthroughs in the field, define and shape the teams ML and platforms roadmap, and not be afraid to get your hands dirty with code when needed.

You are expected to be the focal point for all technical aspects, make sure your team members deliver on their tasks, and work together with other stakeholders to define and shape the roadmap of our products. You will work independently and will also be responsible for making technical decisions within your team.

Key Job Responsibilities and Duties:

Lead and develop a high-performing team, fostering individual growth and collaboration.

Manage and mentor ML engineers and Data engineers, ensuring their professional development and effectiveness.

Develop scalable ML infrastructure and pipelines for efficient data processing and evaluations deployment.

Evaluate architecture solutions based on cost, business needs, and emerging technologies.

Collaborate closely with software engineers to ensure seamless deployment and model inference.

Monitor application health, set and track relevant metrics, and implement effective maintenance strategies.

Collaborate with stakeholders to translate business requirements into viable ML solutions.

Evaluate and integrate new ML technologies to enhance productivity and performance.

Drive continuous improvement through model retraining, performance monitoring, and optimization.

Develop robust ML and AI solutions that meet business objectives while considering production constraints.

We are looking for a strong technical leader to lead our Runtime team - one of the most critical backend teams. The Runtime team owns the execution layer of all our automations, the core of our product. The team operates at a significant scale, processing hundreds of millions of steps and millions of security events every day in systems that simply cannot break.

You will lead a strong team of five senior engineers and take ownership of both the people and the technology. This role combines team management with deep technical leadership: developing engineers, setting the technical vision, leading design and architecture decisions, and staying close enough to the code to step in when needed.

What Will You Do?
Lead, mentor, and develop a team of five experienced backend engineers.
Own the teams technical vision, priorities, execution, and long-term direction.
Lead the design and implementation of architectural changes that keep our platform reliable at massive scale.
Drive complex, cross-team projects and influence technical decisions beyond your immediate team.
Lead production incidents and post-mortems, and continuously raise the bar for reliability and operational excellence.
Identify risks and problems before they impact production, and build the processes and infrastructure needed to prevent them.
Stay close to the technology through design discussions, code reviews, debugging, and hands-on contribution when needed.
Use data to understand how customers interact with the platform and turn emerging use cases into new product capabilities.
Help lead significant technical initiatives, including the evolution from GCP toward a Multi-Cloud architecture.
Work with modern AI tools such as Cursor and Claude Code as a core part of the development workflow, while maintaining deep technical understanding and high-quality standards.

As an Engineering Manager at Cortex Cloud, you will lead a team of ~6 engineers operating in one of our most complex and cross-functional domains. This role requires a strong blend of people leadership and deep technical expertise, including systems design and large-scale distributed cloud architectures. You will be responsible for driving the design and delivery of complex, high-impact systems, while ensuring the team executes against the roadmap with both speed and engineering rigor.
Key Responsibilities
Build, mentor, and lead a high-performing software engineering team, fostering a culture of empowerment and driving both individual growth and collective impact.
Partner closely with Product Management and cross-functional teams (Infrastructure, Research, UX) to define priorities and shape multi-quarter product roadmaps, ensuring alignment across all stakeholders.
Own the end-to-end software development lifecycle, translating product strategy into executable plans and ensuring consistent, high-quality, on-time delivery.
Provide architectural leadership for scalable, distributed systems operating at petabyte scale, guiding the design and implementation of high-throughput, cloud-native backend microservices.
Drive production readiness by enforcing best practices around deployment, observability, reliability, and runtime stability, focusing on the details to ensure operational excellence.
Align stakeholders across business units through clear communication of technical strategy, trade-offs, priorities, risks, and execution plans.
Engage directly with strategic customers to lead technical deep dives and architecture reviews, and to influence future product direction.
Foster a culture of high engineering standards, accountability, and continuous improvement, with a strong emphasis on quality and security.