לוח משרות דרושים מהנדסים במרכז

we are looking for a Senior Data Engineer to join our Data Platform team. We are seeking a hands-on individual with experience in building and scaling modern data infrastructure, passionate about exploring AI technologies and applying them to enhance and evolve our data systems. This role is ideal for someone focused on data systems, performance, automation, and reliability, who will design, build, and maintain core components of our data pipelines, storage, monitoring, and observability stack, with a strong focus on improving workflows and system capabilities, while embracing the Shift4 way.

Responsibilities:

Build and maintain scalable, reliable, and high-performance data infrastructure across cloud and on-prem environments
Partner with engineering, analytics, and observability teams to support data flow from ingestion to consumption
Develop infrastructure as code and automation tools to improve deployment, monitoring, and recovery
Help troubleshoot performance bottlenecks and reliability issues in large-scale data pipelines
Implement data quality processes aligned with security standards to ensure accuracy, consistency, and compliance with financial regulations and PCI requirements.
Continuously improve the performance and efficiency of the data platform with proactive tuning and benchmarking
Proactively explore and apply AI tools to enhance efficiency across the data engineering lifecycle, while improving accessibility and usability of data solutions for teams across the organization

Responsibilities
​​Design and implement scalable test strategies and automation that validate end-to-end scenarios across the Fabric Platform, with emphasis on cross-workload integration and real-world usage patterns.
Partner closely with engineering, PM, and SRE teams to embed quality early in the development lifecycle and ensure reliable, production-ready releases.
Build and evolve intelligent test infrastructure that leverages telemetry, synthetic data, and production signals to detect issues before they impact customers.
Identify systemic quality risks across services and drive improvements in reliability, performance, and resilience at cloud scale.
Contribute to a culture of continuous quality by improving test coverage, reducing gaps, and enabling faster, more confident delivery.
Investigate complex issues in distributed systems, using data-driven approaches to isolate root causes and validate fixes effectively.​

We have multiple positions open for Software Engineers and Senior Software Engineers to be hired across different Security teams in Israel.

As a Software Engineer you will:
contribute to business-critical initiatives in our Security
Requiring deep technical skills and the ability to quickly adapt to new areas.
Will improve the end-to-end lifecycle of services
Analyze complex system behavior, and apply modern engineering practices to streamline deployments and reduce costs.
Your role involves working on high-end technologies and collaborating across disciplines to deliver impactful features.
You will also collaborate with multiple teams across us to deliver key customer solutions and support technology.

We have multiple positions open for Full stack Software Engineers and Senior Full stack Software Engineers to be hired across different Security teams in Israel.

As a Software Engineer you will:
Contribute to business-critical initiatives in our Security.
Use deep technical skills and the ability to quickly adapt to new areas.
Improve the end-to-end lifecycle of services.
Analyze complex system behavior, and apply modern engineering practices to streamline deployments and reduce costs.
Work on high-end technologies and collaborating across disciplines to deliver impactful features.
Collaborate with multiple teams across us to deliver key customer solutions and support technology.

Responsibilities:

If you are passionate about advancing security and staying ahead of sophisticated threats, this is your opportunity. As a Software Engineer, you will:

Design, develop, and maintain security solutions for Edge and cloud environments, focusing on cryptography, keys and certificates.

Lead technical architecture and design discussions, driving innovation in secure Azure Edge technologies across Windows and Linux.

Collaborate with cross-functional teams to deliver scalable, reliable, and efficient security features for our Specialized Clouds.

Mentor junior engineers, fostering a culture of excellence, collaboration, and continuous learning.

Analyze emerging security threats and implement proactive measures to protect users, devices, and cloud workloads in the edge.

Do you enjoy helping customers architect systems, design complex software modules, and solve technical problems? Would you like to do this using the latest cloud computing technologies? Do you have a knack for helping software teams and companies understand application architectures and integration approaches, along with the consultative and leadership skills to launch a project on a trajectory to success? Do you have the passion to learn and experience technology hands-on? Do you enjoy working in a dynamic environment? Are you a team player?

In this role, you will practice your creativity, linking technology to tangible solutions and educating our customers about the art of the possible. You will have the opportunity to define or invent cloud-native reference architectures for a variety of use cases. You will have the support to grow your expertise in industry and technology areas of depth. Every day, you will learn something new from your customers, your peers, and your own experiments.

Key job responsibilities
As a Solutions Architect, you will work directly with customers to accelerate their projects and recommend best-practice architectures in line with their long-term business outcomes.
Educate customers of all sizes on the value proposition of us, and participate in deep architectural discussions to ensure solutions are designed for successful deployment in the cloud.
You will own the technical relationship with the customer and operate as their trusted advisor. The best interests of the customer will shape the guidance you provide.
Share the voice of the customer to influence the roadmap of new features and services for the platform.
Create and capture best practices, technical content, and new reference architectures (e.g., white papers, code samples, blog posts).
Evangelize and educate about our technology (e.g., workshops, user groups, meetups, public speaking, online videos, or conferences).
Contribute to the growth of the Solutions Architecture organization by hiring, coaching, and mentoring others.
Develop areas of depth in technical domains such as: Generative AI and Data Analytics, relevant to your interests and your customers' outcomes.

The Startup Solutions Architecture team is dedicated to working with startup companies as they build their businesses. Were here to help them deploy scalable, secure, reliable, performant, sustainable and efficient architectures - and do that spending as little time and money as possible.

In this role, youll work directly with a variety of interesting customers in various industries which could include AI/ML, HCLS, FinTech, ClimateTech, HCLS and others, and help them make the best (and sometimes the most pragmatic) technical decisions along the way. Youll have a chance to build enduring relationships with these companies, their founders, and establish yourself as a trusted advisor.

As well as spending time working directly with customers, youll also get time to sharpen the saw and keep your skills fresh. We have more than 200 services across a range of different categories and its important that we can help startups take advantages of the right ones. You will act as a customer advocate with our product teams to make sure we are building the right products and features for the startups you work with.

In addition, this role will provide plenty of opportunities to share your knowledge more broadly by working on technical content and presenting at events.

Key job responsibilities
Help a diverse range of startups to adopt the right architecture at each part of their lifecycle.
Support startups in architecting scalable, reliable and secure solutions.
Support adoption of a broad range of our services to deliver business value and accelerate growth.
Support the evolution and roadmap of the platform and services, connecting our engineering teams with our customers for feedback.
Establish and build technical relationships within the startup ecosystem, including accelerators, incubators and VCs.
Develop startup specific technical content, such as blog posts, sample code and solutions, to assist customers solve technical problems and reduce time-to-market.

In this role you'll design and build features that shape how customers discover products - tailored to their preferences, helping them find exactly what they need, even before they know they need it. We're defining how LLMs integrate into real-time personalization, how noisy behavioral signals become durable customer understanding, and how AI-powered experiences ship reliably at scale. You'll work across multiple technical teams, ship iteratively, and see your work in the hands of customers quickly. This organization values experimentation, moves fast, and gives engineers real ownership over what they build.

We are looking for a Software Development Engineer with sound technical judgment and a bias for action who takes ownership of problems end to end, communicates clearly, and cares about operational excellence - not just launching features, but making sure they hold up at scale. Someone who naturally raises the bar for the team: mentoring junior developers, advocating engineering best practices, and thinking beyond the immediate sprint.

Key job responsibilities
- Design, build, test, and operate production AI features used by multiple teams and operating in our scale.
- Deliver end-to-end solutions with focus on maintainability, scalability, performance, and reliability.
- Collaborate with Product and Science to define experiences, run experiments, and iterate based on data.
- Build AI-powered experiences including personalized recommendations, relevance explanations, and knowledge-driven features using LLMs and generative AI.
- Define and implement measurement strategies including analytics events and experiment configurations to track engagement and retention.
- Navigate ambiguity and make sound technical decisions in a problem space where established patterns don't always apply.

We are seeking an exceptional an exceptional leader to build and lead our next-generation internal Analog IP design team. This is a unique opportunity to create a world-class analog design center from the ground up, developing the critical IP blocks that power all of our custom silicon products, including Graviton (server CPUs) and Nitro (networking/security accelerators).

Key job responsibilities
Build the team: Recruit, hire, and develop a world-class analog/mixed-signal design team from the ground up. Define the org structure, roles, and growth path.

Define the IP strategy: Own the analog IP roadmap across all Annapurna Labs products. Evaluate build vs. buy decisions and drive internal capability development.

Drive execution: Lead the full design cycle from architecture through silicon validation - spec, schematic, layout, simulation, tapeout, and bring-up.

Collaborate cross-functionally: Partner with SoC architecture, digital design, physical design, DFT, packaging, and system teams to integrate analog IP seamlessly.

Set technical direction: Define design methodologies, flows, and best practices. Evaluate and select EDA tools, PDKs, and foundry processes.

Innovate at scale: Develop IP that is reusable, portable across process nodes, and designed to meet the performance, power, and area (PPA) needs of multiple products simultaneously.

Engage with leadership: Communicate strategy, progress, and risk to senior leadership. Influence the overall silicon roadmap with analog capabilities and constraints.

The MLIL DataPlane team is looking for a Senior Software Development Engineer to own the design and implementation of our inference data plane. We build the software that makes large models run efficiently on custom hardware - spanning model execution, memory management, data movement, and serving integration.
Our work covers the full inference path: integrating serving engines with custom hardware, developing high-performance compute kernels, enabling efficient data movement, and driving models from early validation through production. We operate at frontier scale with large distributed models.
This is a ground-up effort with rapidly evolving hardware and software. We need a senior IC who can write and optimize low-level code for custom hardware, validate model architectures end-to-end, build test and profiling infrastructure, and drive performance across the stack.

Key job responsibilities
- Develop and optimize compute kernels for a custom ML accelerator architecture, targeting production-level performance for large language model inference.
- Implement and validate LLM architectures (decoder-only, mixture-of-experts) end-to-end - from PyTorch model definition through distributed execution on custom hardware.
- Integrate custom accelerator backends into open-source ML serving frameworks (vLLM, PyTorch), including scheduler extensions, memory management, and model parallelism.
- Build and maintain test infrastructure for model correctness validation across CPU, GPU, simulator, and hardware targets.
- Profile and optimize inference workloads - identify bottlenecks, instrument critical paths, and drive latency and throughput improvements from simulation through hardware bringup.
- Own features end-to-end: from design through implementation, testing, and integration into the broader software stack.
- Contribute to CI/CD pipelines that gate model and kernel changes on correctness and performance regressions.
- Mentor engineers, drive design reviews, and raise the engineering bar across the team.

We are looking for an energetic, detail-oriented individual to join our Data Center Engineering Operations Team. This committed group works to maintain the critical physical infrastructure that supports our Web Services. Specifically, this team works to ensure that the data center's MEP operates at 100% availability while maintaining first-class customer service to the teams and groups within the data centers.
The Data Center Engineering Operations Facility Engineer is responsible for operating and maintaining all electrical, mechanical, and fire/life safety equipment within the data center.
DCEO Facility Engineers are our front line responders for hands-on electrical and mechanical equipment troubleshooting and operation. This equipment includes, but is not limited to, stand-by diesel generators, switchgear, UPSs, PDUs, AHUs, chillers, cooling towers, chemical treatment systems, pumps, motors, VFDs, and building automation systems.

Key job responsibilities
- Operate and maintain mechanical and electrical equipment.
- Perform root cause analysis of equipment failures.
- Troubleshooting of facility and rack-level events within internal SLA.
- Ensure all safety procedures are adhered to while performing work.
- Able to work shifts (rotating work days during the weeks).
- Take daily operational readings of all mechanical and electrical equipment.
- Utilize internal CMMS to manage building workflows.

Come join the Agentic AI science team in building the next generation models for intelligent automation.

We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making.

We're looking for a talented SoC Integration Lead to join our Nitro team and help shape what comes next. You will spearhead the SoC integration activities of sophisticated networking chips, collaborating closely with Architecture, RTL Design, Physical Design, Package Design, Verification, Software, DFT, and additional teams in a dynamic, open, and fast-paced environment. As a member of the Nitro project, you will have influence over the device through its entire lifecycle from product definition to mass production. You'll work alongside a world-class, fast-moving engineering team, take full ownership of critical IP blocks, and see your work deployed at a scale no other platform can match, powering hundreds of thousands of businesses across 190 countries.

Key job responsibilities
Take full ownership of SoC integration, including IPs development, partitioning, clock domain crossing (CDC), reset domain crossing (RDC), exploratory synthesis, and design quality verification.
Drive chip-level design implementation by partnering with multiple teams including Architecture, RTL Design, DFT, Verification, System Verification, STA, and Physical Design.
Oversee the creation of SoC-level IP blocks such as fabrics, interfaces, and security modules.
Lead RTL integration activities including micro-architecture definition, RTL coding and debug, synthesis and timing closure, and sign-off.
Address diverse functional and structural challenges, encompassing functional debugging, physical design preparation, emulation, and design quality issue resolution.
Contribute to the creation and implementation of design flows and automated solutions that facilitate efficient SoC development.
Support Verification and Emulation teams through test plan development and coverage review.
Ensure the chip meets quality and reliability standards while delivering to physical design teams, emulation platforms, firmware developers, and other stakeholders.

Required Al Infrastructure & Reliability Engineer
What this role is really about
Youll join a 3-person platform team within our Business Technology group -owning the internal infrastructure that our AI platform and its users depend on. This isnt a product engineering role, and it isnt ticket work or babysitting pipelines someone else built. Youre building and operating the internal foundation that the company runs on. The work covers the full stack of platform engineering: core cloud infrastructure (AWS, Kubernetes, IaC), CI/CD pipelines, AI-driven infrastructure components, and the SRE and observability practice that keeps it all honest -metrics, alerting, incident response, and reliability standards. As our AI capabilities grow, so does the complexity underneath them, and staying ahead of that is central to the role. If you treat infrastructure as a product -reusable, automated, observable, and built to last -this is your kind of role.
Job responsibilities
DevOps & AI-Driven Infrastructure - own CI/CD, deployment processes, and release reliability. Build and operate cloud infrastructure that is automated, intelligent, and continuously self-improving - not just managed.
Design and build our Terraform repository and IaC pipeline from scratch -AI-assisted generation, drift detection, and policy enforcement built in.
Build AI-driven GitHub Actions pipelines -automated code review, risk assessment, and intelligent deployment decisions.
Manage Kubernetes workloads across AWS accounts -zero downtime, fully automated, nothing left behind.
Embed AI into the operational layer -proactive drift detection, automated remediation, and intelligent scaling toward a self-healing runtime.
Reliability & SRE -improve uptime, resilience, and incident response.
Define and enforce SLOs/SLIs, error budgets, and on-call practices.
Lead incident response, postmortems, and systemic reliability improvements.
Own AI-specific reliability: model latency SLOs, token quota monitoring, rate limit handling, fallback and retry strategies, and cost-per-request alerting.
Observability & Telemetry - increase visibility, reduce noise, improve troubleshooting.
Establish and continuously evolve the observability stack: metrics, logs, distributed tracing, and alerting tuned for both application and AI workloads.
AI / LLM Operations- bringing AI systems to production and operating them at scale, with a focus on reliability, performance, and trust.
Own the AI infrastructure layer: rate limits, quota management, latency SLOs, and fallback strategies (retries, circuit breakers).
Operate LLM APIs in production with resilience and cost attribution per team/model.