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We seek an analytically driven and strategic Revenue Operations Manager to join our team. This role will be a critical partner to our C-level executives and revenue-focused leaders, leveraging data to identify growth opportunities, optimize processes, and drive actionable insights that enhance the customer journey and revenue performance.

Key Responsibilities:

Data-Driven Insights & Analytics

Serve as a trusted advisor to C-level executives, delivering regular, actionable insights based on in-depth analysis of key revenue, customer, and operational data.
Develop and maintain revenue forecasting models and predictive analytics to proactively identify opportunities, risks, and trends.
Analyze customer behavior, pipeline performance, and market data to recommend growth and operational improvement strategies.
Create and maintain dashboards and reports that provide visibility into KPIs covering the revenue funnel as well as customer-focused metrics such as churn, retention, and upsell opportunities.

We're seeking a Senior Application Security Engineer who comes from a genuine software engineering background - someone who has designed, written, shipped, and maintained production code and then moved into security (or wants to formalize that move). You'll join the CISO organization as the security backbone of our R&D engine: owning the Secure SDLC end-to-end, embedding security into every stage of development, and partnering with R&D, DevOps, Architecture, and Product so that every line of code and every feature we ship - including our AI capabilities - meets the highest security standards.

This is a high-impact, hands-on role reporting directly to the CISO, with a clear growth path to AppSec Lead and exposure to GRC, cloud, and AI security.

What Youll Do

Secure SDLC & Application Security

Own and continuously evolve Secure SDLC (SSDLC), integrating security gates from design to deployment.
Lead threat modeling (STRIDE / PASTA / attack trees) for new features, architectural changes, and AI components.
Perform and oversee secure code reviews, design reviews, and security architecture reviews - and pair directly with developers on remediation, reference fixes, and reusable secure patterns / "paved-road" libraries.
Manage and operate the SAST, DAST, IAST, SCA, and secret-scanning stack; tune rules, triage findings, drive remediation, and reduce noise.
Define and enforce AppSec policies, secure-coding guidelines, and standards aligned with OWASP Top 10, ASVS, and SAMM.
Software supply-chain security: SBOM generation/analysis, open-source component risk, and dependency hygiene across R&D.

our company MDR delivers 24x7x365 managed detection and response services, protecting customer data through advanced detection, investigation, and response at scale.
We are seeking an MDR Security Engineer to own and scale the automation layer that powers our global MDR operations. This role is responsible for building and operating production-grade automation systems that reduce manual workload, improve detection quality, and enable consistent, high-quality incident response.
The ideal candidate is a hands-on engineer with strong experience in SOAR platforms, security operations, and automation design, capable of driving measurable improvements in efficiency, reliability, and response outcomes across a high-volume SOC environment.
Responsibilities
Upkeep the design, development, and lifecycle of SOAR playbooks, workflows, and integrations across the MDR platform
Build and operate production-grade automation systems supporting alert triage, enrichment, investigation, and response
Define and drive automation strategy by identifying high-impact, high-volume SOC processes and scaling them through automation
Develop integrations across SIEM, EDR/XDR, identity, cloud, and ticketing systems using APIs and scripting
Partner with MDR analysts, IR, threat hunters, and engineering teams to translate operational workflows into scalable automation
Improve detection and response quality through automation of enrichment, investigation, and containment workflows
Contribute to incident response and RCAs by delivering tooling that improves investigation speed, accuracy, and consistency
Evaluate and implement new automation capabilities, including AI-assisted workflows and data-driven decisioning
Monitoring, Metrics & Reliability Ownership
Define and own automation KPIs, including:
Automation coverage (% of alerts handled or augmented)
MTTD / MTTR improvement
False positive reduction and signal-to-noise improvement
Analyst time saved and throughput increase
Build and maintain dashboards and reporting to measure automation impact on SOC performance and SLAs
Ensure production reliability and stability of automation systems, including:
Monitoring workflow success/failure rates and execution latency
Tracking integration and API health, errors, and retry behavior
Implementing logging, alerting, and observability across automation pipelines
Continuously optimize workflows based on data, feedback, and operational performance to ensure consistent 24/7 MDR operation.

we are establishing a strategic R&D center in Israel to drive the development of complex semiconductor chips that solve the critical 'data bottlenecks' enabling the future of AI at scale. As we expand our presence in Israel, we're seeking a visionary Expert IC Package Design Lead to help build our local engineering powerhouse from the ground up. This is a unique opportunity to take on meaningful product ownership in a new site, leading the physical implementation strategy for chips that power the world's largest AI clusters.
As an Expert IC Package Design Lead, you will be a core technical contributor in the development of advanced IC packaging solutions for high-performance connectivity silicon.
You will own package flow, architecture, design, and qualification from concept through production, working closely with silicon, signal integrity, power integrity, mechanical, manufacturing, and external OSAT partners.You will be responsible for defining package technologies that meet aggressive electrical, thermal, mechanical, and cost targets, enabling our companys products to operate reliably in the worlds most demanding AI and cloud environments.
Key Responsibilities
Own end-to-end IC package design, from early architecture and feasibility through detailed design, qualification, and high-volume manufacturing
Define package architecture and technology selection (organic substrates, advanced laminate, interposers, multi-die/chiplet packaging, CoWoS - 2.5D/3D integration)
Lead signal integrity (SI), power integrity (PI), and thermal considerations at the package level for high-speed, high-power devices
Drive package layout, substrate routing, bump/ball maps, stack-ups, materials selection, and mechanical constraints
Collaborate closely with silicon design, SerDes, system, SI/PI, and reliability teams to optimize overall product performance
Interface with OSATs, substrate vendors, and manufacturing partners to ensure design-for-manufacturability (DFM), yield, and cost targets
Lead package-related risk assessment, failure analysis, and corrective actions during bring-up and production ramp
Support NPI, qualification, and product sustainment activities, including vendor audits and technical reviews.

Partner with sales teams to understand client requirements and propose tailored HCM solutions.
Lead discovery sessions, workshops, and process discussions with prospects and customers.
Design process flows, solution architectures, and product demonstrations based on customer needs.
Collaborate with cross-functional teams to ensure successful solution design and delivery.
Advocate Oracles AI and Agentic AI capabilities.
Create and deliver presentations and proof-of-concepts that showcase Oracles solutions.
Support the sales cycle with RFI/RFP responses and commercial guidance.
Build trusted relationships with customers and partners and ensure strong customer satisfaction.

As a Deputy Program Manager (DPM), you will serve as a Director-level member of the Program Management Team (PMT) and work across highly matrixed organizations to achieve program objectives. The DPM will partner closely with the Program Manager (PM), customer stakeholders, and cross-functional Oracle teams to drive execution of mission-critical initiatives in complex and dynamic environments.

The ideal candidate will bring strong leadership capabilities, experience managing complex cloud or infrastructure programs, and a proven ability to collaborate across technical, operational, and business organizations. The candidate should possess a strong understanding of cloud environments, SaaS operations, technology transformations, migrations, and the technology delivery lifecycle.

Key Responsibilities
Lead and collaborate across diverse, matrixed teams to achieve PMT objectives
Support execution of large-scale cloud and infrastructure programs for Public Sector customers
Identify, assess, and manage program risks, issues, dependencies, and opportunities across multiple lines of business
Provide recommendations to improve integration and alignment across interfacing programs and projects
Support development of program-level briefings, documentation, and decision-support materials
Drive operational consistency through development of repeatable PMT processes and best practices
Partner with customer stakeholders and internal Oracle organizations to support successful program delivery
Ensure timely delivery of contractual deliverables and overall program commitments
Lead internal and external collaboration, communication, and stakeholder engagement activities
Support program governance, operational reporting, financial tracking, and strategic planning activities

Define and execute cloud-native sales strategies to drive adoption and revenue growth within key accounts.
Build, lead, and inspire a high-caliber sales team focused on delivering value-based solutions that address client digital transformation goals.
Lead a sales team dedicated to Cloud Native
Train the team to reach goals and much more.
Cultivate deep, consultative relationships with C-level executives, architects, and line-of-business stakeholders to position Oracle as a cloud-native innovation partner.
Partner with OCI engineering, product, and marketing teams to develop targeted go-to-market campaigns and customer engagement strategies.
Lead complex sales cycles-from opportunity identification and scoping to proposal development, negotiation, and closing.
Stay up to date on OCIs evolving cloud-native suite and broader market trends to effectively evangelize Oracle's unique value proposition.
Represent Oracle and OCI at key industry events, customer forums, and strategic engagements.
Ensure sales activities comply with internal policies and relevant external regulations.

This role requires a strong operational leader with experience managing large-scale cloud environments, developing technical talent, and driving continuous improvement through automation, standardization, and data-driven decision making.

Responsibilities
Leadership

Build, lead, and develop high-performing cloud operations and site reliability engineering teams.
Establish organizational goals, priorities, and operating rhythms aligned with OCI business objectives.
Foster a culture of operational excellence, accountability, collaboration, and customer focus.
Recruit, mentor, and develop technical leaders and individual contributors.

The MLIL DataPlane team is looking for a 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 are looking for an 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.

We are looking for talented students/engineers to help us develop the semiconductor platform which is based on revolutionary architecture. Take part in the development of cutting edge products within disruptive system architecture. Youll have the opportunity to work on the technologies that power the worlds largest Cloud provider, within a dynamic, open, and fast-paced environment. Our Web Services provides a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world. Become part of the group which is responsible for development of essential components for networking and storage functionality in the biggest cloud in the world (AWS).

Learn and influence how the cloud works "behind the curtain" today and be part of the innovation that defines how it will look tomorrow - make if more secure, faster and robust. This challenging and interesting job will allow you to contribute into different domains which include embedded development, host stacks and internal services. Get involved in using of cutting edge technologies in both kernel and user space. Being part of Annapurna's SW group will help to establish connections with many other AWS groups and contribute on a company wide scale.

We are seeking an experienced engineer to join our team that owns the network stack for EC2 distributed AI/ML systems. The team develops support for a variety of frameworks and communication libraries including NCCL, NVSHMEM, NIXL, NCCL GIN, and Perplexity kernels. Solid knowledge of Linux, networking, and performant coding is important. Experience with embedded systems is valued, and experience with high-speed networking or HPC/RDMA interconnects is highly valued.

If you like solving hard problems, want to work with HPC and ML customers, iterate fast and deliver meaningful solutions at scale, then come join us! This truly is a role at the forefront of AI/ML-you'll be working on features for the largest clusters, with the largest customers, for the largest AI models.

Key job responsibilities
Be a senior engineer on a team that builds and maintains the infrastructure that monitors and reports on functionality and performance of massive testing workloads run at scale. Use our internal CI/CD tools, Linux, and public AWS products to automate the delivery of our software to customers, saving developer time. Write Python code that effortlessly spools up large clusters and runs benchmarks and applications for ML and HPC workloads. Use AWS Managed Grafana and Athena to digest the massive amount of performance data generated by these workloads and create dashboards for developers and stakeholders. Invent automatic mechanisms to alert developers to functional and performance regressions so they never reach reach customers. Manage the complexity of infrastructure that covers many instance types, software stacks, Linux operating systems, cutting-edge releases and make it easy to evolve.

As a Software Engineer in our NoSQL and in-memory computing platform team, you will lead the software development of large-scale, distributed in-memory storage platform with sub-millisecond latency. You will leverage open source technologies like Valkey, Memcached, and our proprietary technologies. This includes data plane extremely fast and high throughput development, low level optimizations, asynchronous messaging, event-based technologies, real-time failure detection system, horizontal and vertical scaling, auto-remediation, high availability, fault tolerance, storage technologies, snapshoting, and disaster recovery.

In this role, you will have oversight of all things technical, own significant portions of the product, and serve as a mentor for other engineers in their areas of work. As software Enginee, you will helping define the product features, drive system architecture, and spearhead best practices. You will work to enable a quality product and set the groundwork for success in the next phase of the product and beyond. A commitment to teamwork, hustle, and strong communication skills (to both business and technical partners) are absolute requirements. Creating a reliable, scalable, and high-performance service requires exceptional technical expertise, a sound understanding of the fundamentals of Computer Science, and practical experience building large-scale distributed systems. You should be someone who enjoys working on complex system software, is customer-centric, and feels strongly about building good software as well as making that software achieve its operational goals.

Our team focuses on developing products to allow for personalizing the customers experience and providing them with real-time insights and revolutionary experiences using Computer Vision (CV) and Machine Learning (ML). You will get a chance to work on greenfield and large-scale engineering and science projects.

Key job responsibilities
- Own architecture and feature development for our Personalization and CV/ML teams.
- Partner with other engineers to ideate, design, and build scalable solutions.
- Utilize data science and ML to develop products that deliver great experiences for customers.
- Tackle complex technical challenges across the stack - from data pipelines to large scale services.