We are looking for a Senior AI Ops Engineer to join our AIOps team and help build the AI-powered platforms, agents, and workflows that enable engineering teams across our company.
This is a hands-on role for someone who can take AI solutions from idea to production, build the infrastructure around them, and create the observability needed to understand and improve how they behave in the real world.
Job responsibilities
Build and operate production-grade AI agents, AI-enabled tools, and workflows that empower developers and operational teams.
Design agentic systems using frameworks such as LangGraph, LangChain, and Supervisor, including RAG, MCP integrations, tool calling, and guardrails.
Build and evolve an AI SDLC harness that helps teams plan, implement, validate, govern, and safely deliver AI-assisted software changes.
Lead AI observability with Langfuse and OpenTelemetry, including tracing, evaluations, quality measurement, and cost analysis.
Build automated evaluation frameworks, including LLM-as-a-judge, to improve the reliability and quality of AI systems.
Design and maintain the infrastructure, CI/CD pipelines, GitOps workflows, and security controls that support AI services.
Develop internal developer tooling and automation that removes friction across the engineering organization.
Partner with engineering and product teams to turn real operational challenges into scalable AI-powered solutions.

We are seeking an experienced DevOps Engineer to join our Engineering team and play a key role in building and operating our cloud-native platform. The ideal candidate will have hands-on experience managing production environments at scale, driving cloud transformation initiatives, and supporting the of enterprise systems from on-premises deployments to modern SaaS and cloud-native architectures. You will be responsible for designing, automating, and maintaining scalable infrastructure, CI/CD pipelines, and deployment processes that support both our core products and emerging AI-driven capabilities. Working closely with Engineering, QA, Product, and AI teams, you will help ensure the reliability, security, and performance of our services while driving operational excellence and continuous improvement across our technology stack.
Responsibilities:
Design, implement, and maintain CI/CD pipelines.
Manage and optimize cloud infrastructure across AWS, Azure, and/or GCP.
Develop and maintain Infrastructure as Code using Terraform.
Manage Kubernetes-based environments and GitOps deployment workflows using Argo CD and
Kustomize.
Lead and support the migration of enterprise applications and infrastructure from on-premises
environments to scalable SaaS and cloud-native architectures.
Establish, maintain, and continuously improve production environments, ensuring high availability,
security, scalability, and operational excellence.
Demonstrate strong production ownership, including incident management, root cause analysis,
capacity planning, and performance optimization.
Collaborate with Engineering, QA, Product, and AI team
Support the deployment, operation, and monitoring of AI and Generative AI services.
Build and maintain monitoring, logging, and alerting systems.
Troubleshoot and resolve infrastructure, deployment, and production issues.

We are seeking a DevOps software engineer for our agentic AI team. If you are excited to work at the frontier of AI agents and want your work to multiply the output of hundreds of engineers, we want to hear from you.

What you'll be doing:

Build AI agents that solve real engineering problems across the networking stack, with a focus on the infrastructure and services that bring them into reliable daily use.

Design, build, and operate the platforms that make those agents reliable: MCP tools, service APIs, cloud and on-prem services, and the systems behind them.

Work broadly across networking architecture teams to identify high-impact AI use cases and turn them into working solutions.

Drive rapid and responsible AI adoption across the organization: establish best practices, guardrails, and evaluation methods so teams embrace agentic workflows with confidence.

Build evaluation and observability pipelines that measure AI-agent behavior and platform reliability on real production workloads.

As a Platform DevOps Engineer for us, you will lead DevOps for our SaaS product. You will serve as the products primary DevOps owner, with end-to-end responsibility for infrastructure, Production availability, reliability, and development and deployment workflows. The role is designed to establish a scalable DevOps capability as the product and organization grow.

Key Responsibilities
Own the end-to-end cloud-native infrastructure for us, including Development, Test, and Production environments.
Design and build scalable, secure, and reliable infrastructure for an active SaaS product.
Lead CI/CD, deployment, and release-management processes using GitHub Actions, GitOps, and Argo CD.
Manage and scale Kubernetes, Docker, Helm, and public-cloud infrastructure using Terraform.
Establish and lead observability, monitoring, alerting, and incident-response capabilities.
Participate in on-call rotations, resolve Production incidents, lead postmortems, and drive preventive improvements.
Partner with R&D teams to improve product performance, scalability, reliability, and security.
Develop automation and scripting tools, and promote AI-powered code assistance and development practices to improve operational speed and quality.
Build operational processes, infrastructure standards, and documentation that support the future growth of the DevOps capability.

We are looking for a proactive and skilled Software Infrastructure Developer with a strong Agentic AI focus to join our team. In this role, you will design and build the infrastructure, tooling, and AI-powered automation that keep our engineering systems reliable, scalable, and intelligent.

You will be responsible for embedding GenAI and agentic capabilities into our internal developer platforms and CI/CD workflows - creating frameworks, libraries, and multi-agent systems that accelerate automation, improve system stability, and unlock new levels of engineering productivity. This is a hands-on role for someone who thrives at the intersection of infrastructure engineering and applied AI.

The ideal candidate brings deep technical expertise in Python (FastAPI) and/or TypeScript, Kubernetes, CI/CD (Jenkins, GitHub Actions), containerization, and cloud infrastructure - combined with hands-on experience building LLM-powered applications, agents, MCP servers, and RAG pipelines.

What you'll be doing:
AI Platform Development: Design and build internal AI platforms, reusable SDKs, libraries, tools, and MCP servers for agentic applications.
Agentic Workflow Development: Develop single- and multi-agent workflows covering planning, tool selection, delegation, state and memory management, execution, retries, fallbacks, error recovery, and human-in-the-loop approval.
AI-Powered Infrastructure & CI/CD: Integrate AI capabilities into Kubernetes infrastructure and Jenkins/GitHub Actions pipelines to improve development, testing, deployment, and operational workflows.
AI Observability & Evaluation: Implement agent tracing, prompt and tool-call logging, latency and error monitoring, token and cost tracking, regression testing, and failure analysis.
AI Security & Governance: Apply guardrails, access controls, auditability, and governance practices to ensure agents operate safely and reliably.
End-to-End Platform Ownership: Own AI platform capabilities from architecture through production and build reusable solutions that accelerate adoption across engineering teams.
Cross-Functional Collaboration: Collaborate with engineering and business teams to identify high-impact AI opportunities and translate them into scalable technical solutions.
AI Research & Innovation: Evaluate emerging AI frameworks, models, and cloud technologies and promote their adoption where they provide measurable value.

We are looking for an independent Senior DevOps Engineer who thrives in a fast-paced environment. You will join our centralized DevOps team, serving as a pillar of reliability and innovation for the entire engineering organization.

This is a 50/50 "Build vs. Run" role. Splitting your time between building modern automation and improving our developer experience and operational excellence, ensuring our production environments are rock-solid, secure, and highly available while managing the live environment from server infrastructure all the way to the application.

Tasks you will take part in:
Design and implement next-generation CI/CD automation flows to streamline the path from "Code" to "Production."
Lead the evolution of our Infrastructure-as-Code (Terraform) to make our systems more modular and self-service for developers.
Collaborate with backend teams to architect scalable microservices and optimize datastore performance (RDS, MongoDB).
Embrace AI-powered development tools (Cursor, Claude Code) to automate toil and accelerate infrastructure delivery.
Full ownership of our AWS accounts and multi-cluster Kubernetes environments.
Manage and fine-tune live production environments, ensuring 99.9% uptime for our mission-critical fintech services.
Drive our Observability strategy (Datadog/Grafana) to proactively catch issues before they impact our customers.
Participate in a weekly on-call rotation, serving as the first line of defense for platform reliability.
is used for creating requisitions 'from scratch'

Key Responsibilities
We are looking for a passionate Software Developer to join our WAF SaaS Platform team, where we build, evolve, and operate our companys cloud-native WAF SaaS product.
In this role, you will develop new SaaS product capabilities while also building and operating the cloud infrastructure that powers the platform. You will work across backend services, Kubernetes environments, automation, CI/CD, monitoring, and, when needed, frontend components.
We are looking for a strong team player with a high sense of ownership, a get-things-done mindset, and the willingness to contribute across all areas of development - from UI and backend to DevOps and cloud infrastructure.
Major Responsibilities
Develop new features and capabilities for our companys WAF SaaS product, with a focus on backend services, cloud infrastructure, and DevOps-oriented development
Design, build, and maintain cloud-native infrastructure that supports customer environments, production workloads, and global SaaS deployments
Take part in creating and operating new POPs, improving customer environment provisioning, and evolving the platforms scalability and availability
Develop SaaS product capabilities such as certificate management, CDN-related flows, DDoS-related capabilities, onboarding flows, and other customer-facing platform features
Work with cloud services, CI/CD pipelines, monitoring, logging, and automation tools
Take end-to-end ownership of features and infrastructure components, from design and implementation through deployment, observability, support, and production operation
Build and maintain dashboards, alerts, and operational tools, using data and metrics to improve reliability, performance, and product decisions
Collaborate closely with developers, DevOps engineers, product managers, security researchers, support teams, and other stakeholders
Support production environments, investigate customer issues, and understand the real-world impact of features, bugs, and infrastructure changes.

we are looking for a Senior AI Engineer to design and build production-grade, LLM-powered systems. You'll work at the intersection of software engineering and applied AI - shipping agents, RAG pipelines, and tool-using systems that solve real problems at scale. This is a hands-on, high-ownership role for someone who thrives at the frontier of what's possible with modern LLMs and isn't afraid to write the glue, the infrastructure, and the prompts that make it all work.
This is a **cross-functional, company-wide role**. You won't be embedded in a single product team - instead, you'll partner with every department to identify high-leverage opportunities and build AI-powered tools and workflows that boost productivity and efficiency across the entire organization.
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
"our company's data management vision is the future of the market."- Forbes
we are the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, our company takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.
Our success has been built through intense innovation, a customer-first mentality and a team of fearless company ronauts who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our companys growth and at a pivotal point in computing history.
What You'll Do:
- Design, build, and operate LLM-powered applications, agents, and workflows end-to-end - from prototype to production.
- Architect retrieval, context engineering, and tool-use strategies that make models reliable, accurate, and cost-efficient.
- Integrate LLMs with internal services, third-party APIs, and data stores to automate complex business and engineering workflows.
- Build, evaluate, and continuously improve evaluation harnesses for non-deterministic systems.
- Collaborate closely with product, research, and platform teams to translate ambiguous problems into shipped capabilities.
- Stay ahead of the rapidly evolving LLM ecosystem (models, frameworks, agentic patterns) and bring the best ideas into our stack.