Required Senior Backend Engineer - AI Framework (Python)
As a Senior Backend Engineer on our AI Framework team, you will build the foundational platform that enables the entire organization to design, evaluate, deploy, and operate AI agents at scale. This is a new, high-impact team responsible for creating the frameworks, tools, and guardrails that power our agentic ecosystem.
Youll work deeply in the agentic space, designing systems for orchestration, evaluation, observability, and safety. The platforms you build will be used by multiple teams across, making your impact immediate and company-wide.
Youll Own:
Agentic Framework Architecture: Designing and building our 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.
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 broader backend ecosystem.
Agent Runtime and Execution Engine: Building the runtime responsible for orchestrating agent execution, managing tool calls, maintaining state and memory, and ensuring reliable execution across distributed systems.
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 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 will rely on.
AI Safety and Quality Bar: Raising the bar for how AI systems are evaluated, monitored, and governed across the company.

our company's product is built around an AI agent that security analysts and detection engineers work with directly. It investigates coverage questions against live enterprise security data, authors and tests detection logic, and tunes noisy alerting.
That agent is already in production with enterprise design partners. Now we need to make it dependable and scalable enough for GA.
You will own that evolution: the agent architecture, its evaluation and quality system, and the production engineering around it. This is a hands-on senior IC role with real architectural authority - you set the technical direction and you write the code.
The agent operates inside customer security environments, where a wrong action can become a customer incident. Correctness, isolation, observability, and evaluation are not polish. They are the product.
What you'll be doing
Agent architecture: Design the evolution from today's production single-agent system to a multi-agent one: orchestration, task decomposition, runtime and framework choices, and a migration path that does not break what design partners already rely on.
Agent capability: Own the prompts, context, skills, and tool design that make the agent genuinely good at detection engineering across multiple security platforms, not just plausible-sounding.
Evaluation platform: Build the harnesses, judges, and golden datasets that turn "the agent feels better" into a number, plus the CI gates that keep regressions from shipping.
Reliability and safety: Keep long-running agentic sessions healthy in production, and build the isolation and guardrails required of an agent working inside enterprise security environments.
Production debugging: Work real failures from production traces, and turn each one into an eval case that can never regress silently.
Technical direction: Make the calls on architecture, sequencing, and quality bar and be accountable for the outcome, including raising how AI-natively the whole team builds.
Cross-team partnership: Partner with product and customer-facing teams on what the agent should do, and with platform teams on the data and integrations it depends on.

Were hiring a ML Engineer to accelerate AI-driven innovation across B2B SaaS platform.
Youll be at the forefront of building intelligent systems that power core product experiences and automate internal operations, driving efficiency, speed, and scale across the organization. This is a high-impact, hands-on role in a fast-growing, AI-first company where machine learning is a foundational pillar, not a bolt-on feature. You'll partner with product, engineering, and operations teams to design and implement powerful ML and LLM-based solutions that make a measurable difference.
What You Will Do:
Build Intelligent Systems: Design and develop ML/LLM-powered solutions that solve real-world challenges across product and internal workflows.
Own Full Lifecycles: Take projects from concept all the way to production, including model training, evaluation, integration, and monitoring.
Leverage State-of-the-Art Tools: Work with leading frameworks like LangChain, Hugging Face, TensorFlow, and PyTorch to deliver cutting-edge functionality.
Collaborate Cross-Functionally: Partner with product managers, engineers, and stakeholders to embed AI capabilities into user-facing features and backend services.
Ship at Scale: Build and maintain scalable APIs and services, integrating best practices in CI/CD, observability, and cloud infrastructure.
Report with Impact: Share progress, challenges, and results clearly with technical and executive stakeholders.

We're looking for a Senior Backend Engineer to own core infrastructure that powers our platform - from the pipelines that move and process data at scale, to the systems that keep our engineering org shipping fast and reliably. This is a technical leadership role: you'll set architecture direction, raise the bar on engineering practices, and mentor other engineers, while staying deeply hands-on.

You'll operate in an organization that expects AI-native ways of working. Using tools like Claude, Cursor, Hermes or LangGraphor isn't a bonus here - it's the baseline for how we build, and we expect you to help the rest of the team level up on it too.

What Youll be Doing:
Own core backend infrastructure - design and build scalable, reliable Node.js/TypeScript/Python/Go services that other teams and systems depend on.
Build and scale data pipelines - architect the infrastructure that processes and moves large volumes of data reliably, efficiently, and at scale.
Elevate test & validation infrastructure - build the automation, tooling, and CI/CD systems that let engineering ship fast without breaking things, and that make quality and reliability measurable.
Set technical direction - make architecture decisions with company-wide impact, drive design reviews, and establish engineering standards and best practices.
Mentor and multiply - level up other engineers technically, and help shape a fast, high-ownership engineering culture as the team grows.
Lead with AI-native workflows - use AI-assisted development tools daily to move faster without sacrificing architectural quality, and champion their adoption across the team.

We are looking for an exceptional Senior / Principal Backend Engineer to join our AppSec Platform group, reporting directly to the Group Leader.
This is a highly autonomous, hands-on role for an engineer who wants broad technical ownership rather than a narrowly defined domain. You will work on some of AppSec's most important and challenging engineering problems - spanning high-scale distributed systems, data infrastructure, onboarding and integrations, developer experience, reliability, performance, and AI-driven engineering.
You will frequently operate across team boundaries, take ambiguous problems from idea to production, and lead technical initiatives that have an impact well beyond a single service or team.
We are looking for someone who combines deep backend expertise with strong execution: an engineer who can design the architecture, dive into the code, debug production systems, challenge existing assumptions, rapidly prototype new approaches, and bring others along with them.
Key Responsibilities:
Lead Critical Initiatives End-to-End - Own complex, business-critical engineering efforts from problem definition and architecture through implementation and production, often spanning multiple teams and domains.
Build and Scale the Backbone of AppSec - Design and evolve distributed systems and data infrastructure supporting large enterprise environments and hundreds of millions of entities, while balancing scalability, reliability, performance, and cost.
Stay Hands-On and Raise the Engineering Bar - Write and review production code, solve complex technical problems, and champion excellent architecture, maintainable code, testing, observability, and production ownership.
Drive Performance & Reliability - Identify architectural and operational bottlenecks and lead meaningful improvements in scalability, resiliency, efficiency, observability, and production readiness.
Shape DevEx and AI-Driven Engineering - Improve how engineers build, test, debug, and operate software while leveraging AI, automation, and agentic approaches to accelerate development and unlock new capabilities.

We are looking for an exceptional Senior / Principal Backend Engineer to join our AppSec Platform group, reporting directly to the Group Leader.
This is a highly autonomous, hands-on role for an engineer who wants broad technical ownership rather than a narrowly defined domain. You will work on some of AppSec's most important and challenging engineering problems - spanning high-scale distributed systems, data infrastructure, onboarding and integrations, developer experience, reliability, performance, and AI-driven engineering.
You will frequently operate across team boundaries, take ambiguous problems from idea to production, and lead technical initiatives that have an impact well beyond a single service or team.
We are looking for someone who combines deep backend expertise with strong execution: an engineer who can design the architecture, dive into the code, debug production systems, challenge existing assumptions, rapidly prototype new approaches, and bring others along with them.
Key Responsibilities:
Lead Critical Initiatives End-to-End - Own complex, business-critical engineering efforts from problem definition and architecture through implementation and production, often spanning multiple teams and domains.
Build and Scale the Backbone of AppSec - Design and evolve distributed systems and data infrastructure supporting large enterprise environments and hundreds of millions of entities, while balancing scalability, reliability, performance, and cost.
Stay Hands-On and Raise the Engineering Bar - Write and review production code, solve complex technical problems, and champion excellent architecture, maintainable code, testing, observability, and production ownership.
Drive Performance & Reliability - Identify architectural and operational bottlenecks and lead meaningful improvements in scalability, resiliency, efficiency, observability, and production readiness.
Shape DevEx and AI-Driven Engineering - Improve how engineers build, test, debug, and operate software while leveraging AI, automation, and agentic approaches to accelerate development and unlock new capabilities.

Required Senior Software Engineer, Cloud Datastream and Database Migration Service
About the job
Our software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to our needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
The Control & Connect (C&C) team builds the core infrastructure powering our DMS and Datastream. We own the mission-critical Control Plane and Data Movement Infrastructure that allows enterprise customers to seamlessly migrate and replicate their databases at massive scale.
As a Senior Software Engineer, you will design and build the core infrastructure that enables enterprise customers to replicate and migrate their databases. You will address distributed systems issues involving stateful microservices, intricate multi-region architectures, and high-throughput data pipelines. Operating in a collaborative environment, you will guide the technical design of new features, improve system reliability, and mentor fellow engineers. Our team is also pioneering AI-assisted engineering operations, giving you the opportunity to shape how we use generative AI to accelerate development, improve testing, and reduce operational toil.
Responsibilities
Design and implement resilient, multi-step long-running operations and manage orchestration workflows on our cluster management systems.
Drive architectural improvements to decouple systems, manage service overload, and integrate seamlessly with various Cloud services like AlloyDB, Cloud SQL, and BigQuery.
Take end-to-end ownership of ambiguous technical challenges, translating complex requirements into concrete architectures and maintaining high engineering standards through design and code reviews.
Identify and eliminate operational toil, including contributing to the team's custom AI agents to automate release pipelines and streamline on-call workflows.

Cortex Cloud Application Security (AppSec) is building the security platform for the modern software development lifecycle. We help organizations identify, prioritize, and prevent security risks across source code, open-source dependencies, infrastructure as code, secrets, container images, CI/CD pipelines, and the broader developer ecosystem.
At the heart of AppSec is a large-scale platform responsible for connecting to customers' development environments, collecting and processing massive amounts of data, and making it reliably available to security products and experiences across Cortex Cloud.
We are looking for an exceptional Senior / Principal Backend Engineer to join our AppSec Platform group, reporting directly to the Group Leader.
This is a highly autonomous, hands-on role for an engineer who wants broad technical ownership rather than a narrowly defined domain. You will work on some of AppSec's most important and challenging engineering problems - spanning high-scale distributed systems, data infrastructure, onboarding and integrations, developer experience, reliability, performance, and AI-driven engineering.
You will frequently operate across team boundaries, take ambiguous problems from idea to production, and lead technical initiatives that have an impact well beyond a single service or team.
We are looking for someone who combines deep backend expertise with strong execution: an engineer who can design the architecture, dive into the code, debug production systems, challenge existing assumptions, rapidly prototype new approaches, and bring others along with them.
Key Responsibilities
Lead Critical Initiatives End-to-End - Own complex, business-critical engineering efforts from problem definition and architecture through implementation and production, often spanning multiple teams and domains.
Build and Scale the Backbone of AppSec - Design and evolve distributed systems and data infrastructure supporting large enterprise environments and hundreds of millions of entities, while balancing scalability, reliability, performance, and cost.
Stay Hands-On and Raise the Engineering Bar - Write and review production code, solve complex technical problems, and champion excellent architecture, maintainable code, testing, observability, and production ownership.
Drive Performance & Reliability - Identify architectural and operational bottlenecks and lead meaningful improvements in scalability, resiliency, efficiency, observability, and production readiness.
Shape DevEx and AI-Driven Engineering - Improve how engineers build, test, debug, and operate software while leveraging AI, automation, and agentic approaches to accelerate development and unlock new capabilities.

As a Senior Applied AI Engineer, you will lead the bridge between cutting-edge AI capabilities and production-grade software. You will design, build, and optimize the intelligent systems, agentic workflows, and LLM-driven architectures that power our companys conversational products.
Also, you will combine software engineering rigour with state-of-the-art Generative AI techniques - optimizing for conversational quality metrics, latency, and system reliability in high-scale production environments, serving millions of users. We are looking for an engineer who is hungry for AI innovation, eager to pioneer new generative capabilities, and passionate about shipping impactful AI solutions.
In this role, you will:
Design & Scale AI Systems: Architect and deploy high-performance LLM orchestration systems, agentic workflows, retrieval-augmented generation (RAG) pipelines, and AI microservices.
Bridge AI Research & Production: Transform frontier LLM research, foundation models, and generative techniques into robust, production-ready features with high availability and low latency.
LLM Evaluation & Guardrails: Design and implement automated LLM evaluation (evals) frameworks, benchmark suites, and guardrail policies to continuously measure accuracy, reduce hallucinations, and ensure safety across product flows.
Optimize Performance & Cost: Lead latency, throughput, and token-cost optimization strategies across commercial APIs and open-source models.
Set AI Engineering Standards: Elevate software craftsmanship across the team through architectural reviews, code quality, and LLMOps best practices, utilizing the latest AI tools.
Drive Product Innovation: Collaborate closely with product and engineering teams to translate complex human resource and conversational challenges into intelligent software solutions.

We are looking for a Senior Software Engineer to join our growing Data Infrastructure team!
The team's main responsibility is developing our data platform - from building the microservices and pipelines that onboard customer data into our platform, to the infrastructure and tooling that enables our internal data teams to analyze, transform, process, and collect data independently. Our goal is to build leverage: every feature we ship reduces friction for the teams that depend on our platform. We're looking for a builder who takes full ownership from inception to production, cares deeply about quality and performance, and leverages AI tools to move faster and deliver better outcomes.
Responsibilities
Design and implement scalable, production-grade data pipelines and microservices that ingest, transform, and move data from a wide variety of customer sources at high volume.
Build and maintain high-performance backend services and APIs that interface with our data ecosystem, ensuring reliability, low latency, and security.
Develop and evolve the platform infrastructure - data warehouse, orchestration, compute - that internal data teams rely on daily.
Identify opportunities to automate recurring workflows and turn ad-hoc needs into robust, self-serve platform capabilities.
Collaborate with data scientists, analysts, and engineers across R&D to translate requirements into platform features.
Drive code quality through design reviews, code reviews, and adherence to engineering best practices.
Leverage AI tools throughout the full engineering cycle - from scoping and design to implementation and debugging - to deliver faster, higher-quality outcomes.