דרושים » מחשבים ורשתות » Senior DevOps Engineer Platform Engineering

Were looking for a Senior Infrastructure Engineer who views "Infrastructure as Software." In 2026, we dont just manage servers; we build high-performance environments that allow multi-agent systems to operate at scale.
You will be a core member of the R&D team, blending deep DevOps expertise with the coding rigor of a Backend Engineer. You arent just "configuring" AWS; you are architecting the distributed systems and data pipelines that power our autonomous security brain. Your mission is to ensure that while our agents are evolving and taking actions, our underlying platform remains immutable, observable, and infinitely scalable.
What You'll Do
Design, build, and operate our company's cloud infrastructure using AWS, Kubernetes, and Infrastructure as Code.
Build internal tools and platform services using Python and Go to improve developer productivity and system reliability.
Own infrastructure automation with Terraform, Pulumi, and modern cloud-native tooling.
Partner closely with Backend, Data Science, and Security Engineering teams to build scalable, reliable platforms.
Improve observability, monitoring, and incident response across distributed production systems.
Design and optimize infrastructure for performance, scalability, security, and cost efficiency.
Help shape engineering best practices, platform architecture, and developer experience as our company continues to grow.

We are looking for a hands-on Senior DevOps Engineer with a strong cloud-native mindset to build, maintain, and evolve our highly scalable, highly-available cloud infrastructure. This role is pivotal in driving operational excellence, security, and automation across our entire engineering organization. You will promote communication, integration, and collaboration to significantly enhance our software development productivity and reliability. You'll work closely with engineering and product teams to streamline delivery, enforce platform standards, and enable a high-velocity development environment-all while keeping reliability and security top of mind.
Responsibilities:
Design, Automate, and Manage complex cloud infrastructure on AWS using best-in-class Infrastructure as Code (IaC) practices.
Lead the operation and enhancement of our production Kubernetes environments (EKS), focusing on automation, security, observability, and seamless CI/CD integration.
Drive continuous improvement across platform tooling, developer experience, and operational processes to meet our ambitious performance and uptime goals.
Implement and enforce security-first infrastructure patterns, including strong IAM, network segmentation, and secure secrets management.
Actively contribute to high-level technical design discussions and cross-functional architectural decision-making, ensuring solutions align with long-term platform strategy.

We are seeking an exceptional Platform Engineer who combines deep software engineering with a robust DevOps approach to help propel development infrastructure to the next level. , SPEED is integral to our DNA. AI transforms the way we develop at speed, and our development infrastructure is key to the scale and hypergrowth.



The DevX team is a multi-disciplinary group of DevOps and development experts focused on building and operating internal tools, infrastructure, and services to make engineering easy and intuitive SPEED.



Your mission is to build a top-tier Continuous Integration and Delivery (CI/CD) platform. You will own both the application services and the infrastructure that supports them, ensuring speed, stability, and reliability for our entire R&D organization.



Key Focus Areas & What You'll Do



Improve CI/CD pipelines and CI workflows (e.g., GitHub Actions) with a focus on speed and reliability.
Reduce CI flakiness and improve overall pipeline stability through systematic triage and root-cause analysis.
Shorten developer feedback loops by optimizing test strategy, pipeline consistency, and local development workflows.
Strengthen CD and release processes for secure, repeatable, and fast deployments.
Promote best practices such as GitOps and progressive delivery where they fit.
Track and improve delivery metrics, with emphasis on Lead Time for Changes and Deployment Frequency.
Partner with engineering teams to identify friction and deliver scalable automation and paved paths.

We are looking for an experienced Senior DevOps Engineer to join our DevOps team in the Posture R&D Group, who is passionate about software design, development and deployment. The role goes beyond traditional DevOps - it focuses on building the infrastructure and platforms that enable AI models and autonomous agents to run in production at scale, across both cloud and on-prem environments. The job involves writing production-grade modern DevOps solutions that will be shipped to the cloud and on-prem solutions, while working with cutting-edge technologies and architectures that push the boundaries of AI-driven cybersecurity systems.
Responsibilities
Build the best solutions for our production platform, enabling high-scale, AI-driven systems and agents to operate reliably in production-scale environments
Everything as a code approach (IaC): Run our infrastructure with a wide range of technologies including Terraform, and Kubernetes
Build and maintain tools for automation, deployment, monitoring, and operations, with a strong focus on scalability, resilience, and observability of distributed system.
Troubleshoot complex issues in our development, production, and test environments, including large-scale, distributed, and AI-integrated systems
Excellent communication and people skills.

Required Senior AI Platform Engineer - Sovereign AI Engineering
The Dream Job
It starts with you - an engineer driven to build the agentic AI platform that turns LLMs into reliable, production-grade capabilities. You care about clean APIs, well-defined service boundaries, and systems that teams can build on with confidence. We are AI-first across the board - every team builds and operates agents. You'll architect and ship the platform that makes this possible: agent orchestration frameworks, LLM gateways, evaluation pipelines, tool-calling infrastructure, and retrieval systems. Without this platform, agents don't ship - you own the layer that turns AI research into Sovereign AI products, deployed across cloud and on-prem environments.
If you want to make a meaningful impact, join our mission and build the agentic AI platform that drives Sovereign AI products - this role is for you.
Responsibilities
Design and build agentic systems - single and multi-agent workflows with planning, memory, context engineering, and tool use - for both internal automation and product-facing autonomous capabilities operating over long time horizons.
Build and operate the AI platform layer - LLM gateways, prompt management, structured output handling, tool-calling infrastructure, and cost/latency optimization - deployed on Kubernetes, consumed by every team for their agentic work.
Own the agent framework layer - orchestration primitives, execution environments, state management, and sandboxed tool execution - giving every team the building blocks to create and operate their own agents.
Build evaluation infrastructure that gives teams confidence in agent behavior - automated LLM and agent evals for quality, correctness, safety, latency, cost, and regressions, including human-in-the-loop oversight for mission-critical workflows.
Productionize and harden backend services (APIs, gRPC, async workers) that integrate LLMs - with proper error handling, retries, circuit breakers, and high-availability patterns.
Own RAG pipelines and retrieval systems - indexing, chunking, embedding, vector database management, filtering, and relevance tuning for production retrieval.
Optimize performance and cost across the AI stack - model routing, caching, batching, and inference cost management.
Ship shared tooling - libraries, SDKs, agent templates, and documentation - while working closely with ML Platform, Data Platform, DevOps, and other teams across the Applied AI Engineering group. Own architecture, documentation, and operations end-to-end.

Your Career:
Own and continuously improve AWS production infrastructure for scalability, reliability, security, performance, and cost.
Run and evolve Kubernetes environments that support fast, safe product delivery.
Drive developer velocity and production safety through better CI/CD pipelines, release workflows, deployment visibility, and GitOps practices.
Improve observability and incident response - reduce alert noise and raise signal quality.
Design and ship AI-assisted operational agents that change how engineers work - triaging monitoring alerts, summarizing incidents, proposing fixes, onboarding new services, answering questions and requests. This is a core part of the role, not a side project.
Build automation and self-service tooling that removes manual work from provisioning, monitoring, incident response, and developer workflows.
Analyze operational data across incidents, alerts, deployments, infra health, and cost to find reliability gaps, inefficiencies, and automation opportunities.
Partner with engineering, security, product, and leadership to remove bottlenecks and support safe production growth.
Evaluate and introduce new tools and AI-assisted approaches, balancing innovation with reliability, cost, and operational simplicity.
Your Impact:
You'll help scale production systems, improve deployment velocity and reliability, reduce operational overhead, and build automation and AI workflows that help engineering teams move faster and operate more efficiently.
This role is a strong fit for someone who enjoys ownership, collaboration, and operational innovation.

We are seeking an experienced Senior DevOps Engineer to build and maintain the critical infrastructure that powers our multi-platform development pipeline, from cloud-based development environments to embedded automotive systems.

This role combined traditional cloud infrastructure, embedded systems tooling, and safety-critical automotive software deployment.

You will work closely with our embedded systems, software, and quality teams to enable rapid, reliable, and traceable releases across multiple customer programs (VinFast, JoyNext, and internal platforms).

Responsibilities:
Expert in infrastructure cost optimization, cloud resource management, and identifying opportunities to reduce operational expenses without compromising performance or reliability.
Design, implement, and maintain CI/CD pipelines using GitHub Actions, supporting multi-repository development workflows and versioned manifest-based releases.
Build and optimize cloud infrastructure for development, testing, and OTA (Over-The-Air) deployment pipelines (x86-based build systems, container orchestration, monitoring, and observability).
Establish and enforce DevOps best practices for safety-critical automotive software (ISO 26262, AUTOSAR, traceability, audit logs, change management).
Collaborate with embedded systems teams to ensure deterministic, bit-identical builds across different platforms and environments.
Troubleshoot and resolve infrastructure issues affecting development velocity and production systems.

Required Senior ML Platform Engineer - Sovereign AI Engineering
The Dream Job
It starts with you - an engineer driven to build the ML platform that turns research into reliable, production-grade intelligence. You care about reproducibility, low-friction experimentation, and infrastructure that earns the trust of the scientists and researchers who depend on it daily. You'll architect and ship our ML platform - training pipelines, model serving, feature stores, experiment tracking, and compute orchestration - turning models into production capabilities across cloud and on-prem, including air-gapped deployments. A significant part of the platform supports large language models, with unique challenges across training, evaluation, and inference in mission-critical environments.
If you want to make a meaningful impact, join our mission and build the ML platform that drives Sovereign AI products - this role is for you.
Responsibilities
Build and operate ML training infrastructure - distributed training pipelines, compute scheduling, and reproducible experiment workflows that data scientists rely on daily.
Own model serving and inference systems - packaging, deployment, autoscaling, A/B testing, canary rollouts, and latency/cost optimization for production models.
Run feature stores, model registries, and dataset versioning - enabling self-serve feature engineering, model lineage, and reproducible experiments across teams.
Build experiment tracking and evaluation infrastructure - automated evals, comparison dashboards, drift detection, and monitoring that give teams visibility into model behavior and performance.
Build and maintain production pipelines for training, fine-tuning workflows, and serving domain models - owning reliability, reproducibility, and scale.
Build and maintain the monitoring and observability layer - model performance tracking, data and prediction drift detection, data quality validation, and alerting.
Improve performance and cost across the ML stack - training throughput, inference latency, batch vs. real-time tradeoffs, and compute cost management.
Ship shared tooling - libraries, templates, CI/CD for models, IaC, and runbooks - while collaborating across Data Platform, AI, Data Science, Engineering, and DevOps. Own architecture, documentation, and operations end-to-end.

We are looking for an experienced DevSecOps Engineer to join our DevOps core platform team and help strengthen the security of our cloud-native infrastructure and development pipelines.
You will work closely with our CISO, DevOps team, and developers to integrate security practices across the entire software development lifecycle (SDLC), helping ensure a secure, scalable, and resilient platform across cloud and on-prem environments.
Responsibilities
Integrate security practices into CI/CD pipelines and across the SDLC
Design and implement automated security solutions (vulnerability scanning, compliance checks, threat detection)
Build and maintain Infrastructure as Code (IaC) for secure, scalable cloud environments (Terraform, Ansible)
Automate security controls and operational processes across cloud and Kubernetes environments
Design, implement, and optimize CI/CD pipelines with a focus on security, reliability, and performance
Secure cloud and on-prem environments (IAM, network controls, encryption best practices)
Manage and harden Kubernetes workloads, including configuration, access control, and image security
Collaborate with DevOps, developers, and security teams to improve system reliability and overall security posture
Conduct security assessments, penetration testing, and compliance audits
Monitor threats, respond to incidents, and improve incident response processes
Promote DevSecOps culture by guiding teams on secure coding, infrastructure, and deployment practices
Enhance observability by integrating monitoring, logging, and SIEM solutions.

Who We Are: Incredibuild is the leading platform empowering developers and enterprises to radically accelerate their development cycles. We help world-leading brands like Microsoft, Citi Bank, GM, Amazon, and Adobe shorten build times, allowing for more iterations, faster product releases, and significant resource savings. Our technology streamlines and accelerates everything from compilation to release automation, dramatically expediting time to market for our clients. You aren’t just "fixing CI/CD pipelines" - you are building a robust Internal Developer Platform (IDP) and creating the tools that enable our engineers to ship high-performance code at scale. If you love writing clean code and get equally excited about a perfectly orchestrated Kubernetes cluster or an elegant Terra grunt module, you’ll fit right in.
What you'll do: Architect & Build: Take full ownership of our infrastructure, from backend services to cloud resources. Empower Developers: Develop and maintain our homegrown IDP , ensuring a seamless "golden path" for engineering teams. Scale the Stack: Design and manage scalable, reliable environments using AWS, Argo CD, and Helm. Automate Everything: Build sophisticated CI/CD workflows using GitHub Actions and manage stateful infrastructure with Terra grunt. Innovate: Evaluate and integrate new CNCF tools and internal utilities to keep our platform at the cutting edge.