Engineering Manager Application Security Salary India in United States

Software Engineer (Associate or Experienced) Company: The Boeing Company The Boeing Company has an exciting opportunity for a Software Engineer to join the SATCOM Mission Planning Software Engineering team in Colorado Springs, CO. Our teams are currently hiring for a broad range of experience levels including; Associate and Experienced Software Engineers. The Satellite Communication (SATCOM) Mission Planning team is a critical part of the U.S. military’s nuclear command, control, and communications (NC3) network, providing nuclear-survivable connectivity. Our team develops software tools and services for advanced satellite and ground systems. This role offers the opportunity to work in a fast-paced development environment using modern, scalable technology and tools. Our team works in an Agile and CI/CD environment with automated testing, vulnerability scanning, and quality scanning capabilities. Position Responsibilities: Develops and maintains requirements, architecture, algorithms, interfaces, and designs for high-performance APIs between front-end and back-end software services Supports software development activities in an Agile environment using DevSecOps methodologies, including integration of completed software components into a fully functional software system Supports the development of critical features and support the full development lifecycle from design through deployment Builds, architects, and consumes APIs and backend services as part of the platform ecosystem, with an emphasis on automation, testing, and security Conducts code reviews to maintain code quality, enforce best practices, and ensure compliance with establis

PWI R&D Writing Systems Engineer Description - A Writing Systems Engineer is an experience individual contributor responsible for owning system-level performance of industrial inkjet web presses , with a strong emphasis on hands-on engineering, on-press troubleshooting, and technical leadership . This role leads complex problem solving across ink, printhead, media, firmware, and mechanical systems, driving print quality, reliability, and robustness through a combination of deep systems thinking and direct experimentation . The specialist serves as a key decision-maker in resolving ambiguous, cross-functional issues and ensuring successful product delivery. Responsibilities Hands-on system ownership & advanced troubleshooting (Primary) Serve as the technical owner for system-level performance , including print quality, reliability, and production robustness Lead hands-on troubleshooting on industrial web presses , diagnosing complex print defects (banding, mottle, nozzle behavior, edge effects, etc.) Design and execute on-press experiments (DOEs) to isolate root causes and quantify system sensitivities Drive root cause analysis across subsystems (ink formulation, printhead, firmware, mechanics, media) and implement corrective actions Support press bring-up, ramp, customer escalations, and field issues , often in high-pressure situations requiring rapid, data-driven decisions Translate real-world press behavior into actionable engineering insights and design improvements System design & integration leadership Define and develop system-level solutions to optimize ink/media interactions, printhead performance, and image quality Lead integration of subsystems (ink, printheads, m

Own the end-to-end execution that takes NVIDIA DRIVE Autonomous Driving Software (NDAS) from product definition to production deployment across major OEM vehicle lines. We are seeking an accomplished engineering execution leader to lead adaptation, integration, validation, and production readiness of NVIDIA Autonomous driving solution (NDAS) for strategic automotive OEMs. You will work between NVIDIA product and engineering teams and the OEM's vehicle, software, systems, and validation groups. The role involves converting an agreed feature set into a deliverable vehicle program. This entails clarifying requirements, coordinating interfaces and responsibilities, setting the engineering plan, building consistent productization workflows, and managing issue resolution. You will influence teams such as systems engineering, autonomous-driving development, platform software, functional safety, cybersecurity, quality, validation, release, and customer engineering. What You'll Be Doing: Lead NDAS execution with major OEMs across the full program lifecycle — from feature definition and technical alignment through vehicle integration, validation, launch, and production ramp — owning the coordinated engineering plan per vehicle line, including requirements, architecture, adaptation scope, achievements, staffing, validation strategy, release criteria, and production-readiness gates. Translate OEM vehicle requirements and use cases into clear commitments for NVIDIA teams, while ensuring OEM partners understand product capabilities, constraints, assumptions, and the work required on their side; build scalable, repeatable workflows for adapting NDAS to specific OEM platforms, vehicle architectures, sensor configurations, compute platforms, networks, and development processes. Drive multi-functional implementation across autonomous-driving features, systems, platform software, vehicle integratio

NVIDIA is seeking a Senior System Architect: Heterogeneous EDA Systems to solve a complex challenge in accelerated computing: Failure Attribution at Scale. As EDA or equivalent experience workloads scale across thousands of heterogeneous nodes, a single failure can cause massive resource waste. We need an engineer to develop and build an automated framework. This framework will ingest telemetry from CPU and GPU clusters to identify the root cause of job failures in real-time. It will distinguish between hardware faults, infrastructure instability, and software defects. What you'll be doing: Architect Failure Attribution Frameworks: Build a scalable "flight recorder" for EDA jobs that captures high-fidelity state across the CPU, GPU, and Fabric at the moment of failure. Build automated diagnostics that correlate GPU XID errors, PCIe bus failures, and CUDA memory exceptions. Connect these errors with system-level events such as OOM kills or NUMA-related hangs. Distributed Logging & Tracing: Implement low-overhead tracing mechanisms (using tracing tools or custom agents) that provide access to job execution across multi-node Slurm or Kubernetes clusters. Root Cause Automation: Develop heuristics and models based on machine learning to classify failures as "Hardware Fault," "Software Bug," or "Environment Issue." This reduces the Mean Time to Identify (MTTI) for R&D teams. Resiliency Engineering: Work closely with hardware and infrastructure teams to define "signals of impending failure," enabling proactive job migration or check-pointing before a crash occurs. What we need to see: Distributed Systems Mastery: BS, MS, or PhD in Computer Science or Electrical Engineering (or equivalent experience) with 6+ years in systems programming. Experience building automated

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. We are looking for an outstanding Compiler Engineer to help build the next generation of intelligent compiler technologies for NVIDIA's accelerated computing stack. Our team works at the intersection of compilers, agentic systems, numerical correctness, and verification to create systems that can reason about, generate, optimize, and validate code transformations across software and hardware boundaries. This is an excellent opportunity for new graduates who are excited about coding agents, AI-assisted software engineering, developer tools, and GPU computing. In this role, you will work with experienced engineers and researchers to build agentic systems and compiler-aware tooling that improve developer productivity, code quality, and system performance across NVIDIA's software and hardware stack. What you'll be doing: Build and improve coding-agent systems for tasks such as code generation, transformation, debugging, optimization, validation, and developer assistance. Develop agent workflows involving tool use, planning, memory, execution, and feedback loops for software engineering and compiler-related tasks. Help create training, evaluation, and verification environments to improve agent quality, correctness, r

We anticipate the application window for this opening will close on - 5 Oct 2026 Careers that change lives start here. Medtronic is a global leader in healthcare technology with a Mission to alleviate pain, restore health, and extend life. Our 95,000 employees work across more than 150 countries to put patients first — developing innovative medical technologies that improve the lives of 72+ million patients each year. Your unique talents will help shape the future of healthcare while building a career grounded in purpose, growth, and impact. A Day in the Life We are seeking a highly motivated Finance Forward Deployed Engineer (FDE) to join our Finance Analytics and Transformation team. This role sits at the intersection of Finance, Data, Analytics, Automation, and Artificial Intelligence. Unlike a traditional data engineering or analytics role, the Forward Deployed Engineer will work alongside Finance teams to deeply understand business processes, identify high-value opportunities, and rapidly design, deploy, and scale solutions that improve how Finance operates and makes decisions. The ideal candidate combines strong Finance and business acumen with hands-on technical capabilities. This individual will be comfortable participating in forecasting, planning, performance reviews, management reporting, and other Finance processes while also working directly with data, building analytical solutions, automating workflows, and applying emerging AI capabilities. The role requires a strong builder mindset: someone who can move from an ambiguous business problem to a working solution, partner with users to iterate quickly, and ultimately transition successful solutions into scalable enterprise capabilities. At Medtronic, we bring bold ideas forward with speed and

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Data Scientist What is the opportunity? We are seeking a highly skilled and motivated Data Scientist to join our Cyber Analytics team within the Security Solutions Data Science organization. This role is critical to driving advanced analytics initiatives, improving fraud detection capabilities, and supporting strategic decision-making across cybersecurity and payment fraud domains. What will you do? • Gain subject matter knowledge on web application security, commonly exploited cyber vulnerabilities, and methods of online and payment card fraud including the common points of purchase for compromised cards. • Build, develop, and maintain innovative data-driven analytical solutions, including predictive models and machine learning algorithms, on large volumes of data to support analytics and reporting needs across products, markets, and services. • Competently handle large datasets, sifting for patterns and trends and translating those insights into technical rules and solutions. • Combine cybersecurity and transaction data into new and insightful views of fraud and vulnerability across the Mastercard network. • Collaborate with cross-functional teams including product, engineering, and operations to understand product, usage, and data pipelines as well as delivering scalable solutions. • T

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking an experienced Principal Hardware Diagnostics Engineer to design and develop diagnostics software used to monitor hardware health and diagnose system-level issues across Graphcore’s AI infrastructure platforms. This role focuses on building diagnostics agents, tools, and analytics frameworks that enable engineers and automation systems to identify, isolate, and resolve hardware issues across blade-level servers and rack-scale clusters. The Team Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. The Systems Engineering and Platform Validation team ensures Graphcore’s AI compute platforms are reliable, diagnosable, and operationally robust at scale. The team co

We are looking for a disciplined and dynamic, Lead System Engineer – compute blade and rack Validation to join our growing compute rack validation team. As a diligent leader in Systems Engineering, you will drive multiple aspects of validation throughout the life cycle of the program. In this high visibility position, you will be part of a leading team to innovate and improve system bring-up and enablement abilities, as well as silicon and system validation to deliver the highest quality, industry leading technologies to market. Your technical leadership skills, validation and debug expertise will be necessary towards product development, definition, root cause and resolution. Your agility and collaborative approach will be essential to work within System Validation & other engineering teams (System Architects, SoC and Rack FW etc). The technical leader will be driving keys areas of system validation including leading first silicon & system bring-up (nodes and rack level systems) - rack level systems and blades will be based of ARM server architecture. Candidate will be immersed in challenging system enablement work, system validation (end-to-end) methodology, tests development and execution as well as triage/debug of critical issues to meet critical program milestones at POR quality. The candidate will also be a key contributor to state-of-the-art HW and lab capabilities for Grapchore’s system engineering. The candidate should be able to work in a global environment while maintaining a synergetic culture. Primary Responsibilities: Lead the systemenablement (including first silicon and other FW components) to ensure system capabilities are brought up as per plan of record and system architecture spec. Drive organization wide methodology for Firmware integration and best known configuration (HW/FW/SW) usage model by leading the release of deployment ready solutions. Develop key methodologies, lab HW and system SW capabilit

Manufacturing Test Engineer – Server Hardware Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. We are opening a new AI Engineering Campus in Austin, which will play a central role in Graphcore's work building the future of AI computing. Role Overview We are seeking an experienced Manufacturing Test Engineer to support high-volume server manufacturing from board-level test through system-level production test. This role will work closely with an ODM manufacturing partner to define, implement, validate, and optimize the manufacturing test strategy for L6 board-level products , including ICT, MDA, and Board Functional Test , as well as support L10 system-level manufacturing test . The ideal candidate has strong experience in server hardware manufacturing, Linux-based test environments, diagnostic test coverage, fixture requirements, yield improvement, and root cause corrective action processes. This role requires both technical depth and hands-on manufacturing execution experience, with the ability to drive best practices across test development, factory readiness, quality planning, and ongoing production support. Key Responsibilities Manufacturing Test Strategy and Planning Work with ODM partners to define and execute the manufacturing test strategy for L6 board-level production . Develop and review test plans covering: In-Circuit Test, or ICT Manufacturing Defect Analyzer, or MDA Board Functional Test Diagnostic coverage requirements Manufacturing line test flow Fai

SUMMARY STATEMENT We are looking for a Solution Architect to design the technical solutions behind our client engagements and give delivery teams a clear, workable path from concept to production. You will work across enterprise data, software applications and GenAI - translating complex business problems into practical architectures that delivery teams can build and scale. This could include architecting an agentic workflow for clinical operations, a conversational analytics product grounded in enterprise data, or an AI-enabled decision platform for commercial teams. You will work directly with clients, define the architecture, test the most important technical decisions yourself and establish the foundations for successful delivery. This is an architecture-first role with meaningful hands-on engineering: you will stay close enough to implementation to prove the architecture works and support it through production delivery, without becoming the primary engineer for every component. You will also help shape the reusable patterns, technical standards and accelerators behind Lynx’s growing AI-native life sciences practice. KEY RESPONSIBILITIES Solution Architecture Own the end-to-end solution architecture for client engagements, including data models, system design, integration patterns and technology choices. Translate business requirements into clear technical designs and implementation paths that delivery teams can build from. Design solutions spanning enterprise data, APIs, applications, cloud platforms and GenAI capabilities. Lead technical discovery with clients: understand requirements, assess existing systems and identify dependencies, constraints and delivery risks. Present architectural options and trade-offs clearly to technical teams, business stakeholders and senior leaders. Make pragmatic decisions across build speed, cost, scalability, security and maintainability. Review key implementation decisions and remain

About the Role OpenAI’s Industrial Compute organization is responsible for ensuring our compute infrastructure scales efficiently to support millions of users and increasingly sophisticated AI models. We’re looking for a Data Scientist to partner closely with Capacity Systems Engineering, Infrastructure, Product, and Research to optimize inference capacity across our global GPU fleet. This role combines statistical modeling, large-scale data analysis, forecasting, and systems thinking to drive critical decisions around infrastructure investments, performance-efficiency trade-offs, and customer experience. You’ll transform complex operational data into actionable insights that directly influence how OpenAI allocates and scales one of the world’s largest AI compute environments. Key Responsibilities Build statistical and machine learning models to profile and improve GPU utilization, latency, throughput, and overall fleet efficiency. Develop forecasting models for inference demand across products, regions, and model families. Analyze production workloads to identify latency bottlenecks and capacity constraints, highlighting optimization opportunities. Partner with Capacity Systems Engineering to inform infrastructure planning and long-term GPU investment strategies. Design experiments and simulations to evaluate scheduling policies, serving strategies, and infrastructure tradeoffs. Build dashboards and operational metrics that enable leadership to make data-driven capacity decisions. Collaborate with Product, Research, Finance, and Infrastructure teams to align compute planning with business growth and model roadmaps. Communicate technical findings clearly to both engineering teams and executive leadership. Qualifications MS or PhD in Statistics, Computer Science, Operations Research, Applied Mathematics, Economics, or related quantitative discipline (or equivalent industry experience). 5+ years of experience working in the infrastructure data science space. Strong ex

About the Team The GTM Enablement team helps OpenAI’s customer-facing organizations turn rapidly evolving AI capabilities into consistent, high-quality customer outcomes. We build the onboarding, learning experiences, playbooks, and knowledge systems that help teams develop technical depth, stay current, and confidently guide customers through successful AI adoption. About the Role We’re hiring a Field Enablement Lead, Technical Success to design and scale enablement for our rapidly growing technical customer-facing teams. You will own programs spanning onboarding, continuous skill development, technical pitches and demos, and subject-matter-expert knowledge sharing. Working closely with Technical Success leaders, Product Enablement, and technical SMEs, you will turn complex product knowledge and field experience into practical systems that improve readiness, consistency, and the quality of customer interactions and deployments. In this role, you will: Design, implement, and scale comprehensive enablement programs aligned to Technical Success onboarding, role-based skill development, and ongoing readiness needs. Redefine and operate the Subject Matter Expert (SME) program, creating clear pathways for technical experts to share knowledge and raise technical depth and consistency across GTM. Own and proactively maintain a versioned repository of technical pitches, demos, playbooks, and launch-ready assets. Partner with Technical Success leadership, Product Enablement, and product SMEs to identify skill gaps and deliver targeted learning interventions. Capture, vet, organize, and make field- and SME-generated technical content easy to discover, trust, and reuse. You might thrive in this role if you have: 5+ years of experience in technical enablement, solutions engineering, solutions architecture, technical success, or a related role. A proven track record of designing and scaling technical enablement programs in high-growth SaaS or technology environments. Exceptional

About the Team The Finance Platform & Technology team builds and scales the systems and data architecture that power OpenAI’s core financial operations. We enable business agility, compliance, and operational excellence across procure-to-pay, quote-to-cash, supply chain, financial planning, and asset management. We partner with Procurement, Accounting, Tax, Legal, Security, Data, and Engineering to modernize workflows through thoughtful platform design, reliable integrations, scalable automation, and trusted data. About the Role As a Business Systems Lead for Procure-to-Pay, you will be a hands-on engineer who designs, builds, and operates the integrations and first-party applications that power OpenAI’s procurement workflows. You will translate business needs into secure, scalable software, APIs, data flows, and automation across Oracle Fusion, Zip, and connected platforms. You will build the future of buying at OpenAI using OpenAI’s own technology, from guided intake and approval experiences to supplier onboarding, purchasing, receiving, invoicing, and downstream financial data flows. You will own the technical roadmap and support model for these capabilities, improving today’s platforms while deciding where to integrate, configure, or build as OpenAI scales. Your core strength will be software and integration engineering. You will personally write code, troubleshoot cross-system failures, and take solutions through testing, deployment, and production support. You will also make targeted functional configurations in procurement platforms and partner with functional specialists on deeper process and module design. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, build, and operate integrations across Oracle Fusion, Zip, and connected systems using APIs, events, messaging, and batch interfaces where appropriate. Build first-party

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for a product manufacturing & quality engineer, who will be responsible for driving technical initiatives related to the manufacturing, quality and reliability of our AI supercomputer hardware systems to ensure product success from concept to launch and through mass production. You’ll have the opportunity to coordinate with functional SMEs and work with a wide range of stakeholders, from design engineering and operations teams, TPMs, external industry vendors and partners to ensure that all products are developed and delivered on time and to the highest quality standards. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees In this role, you will: Own the integrated manufacturing and quality readiness for a product across L6, L10, and L11, with clear gates, milestones, deliverables, owners, and closure criteria. Lead readiness of process flows, tooling, fixtures, assembly operations, test interfaces, and production controls. Review and contribute to work instructions. Translate product requirements into qualification plans, process controls, test requirements and acceptance criteria with design engineering and Area SMEs Coordinate and drive execution of product and process qualification, reliability testing, and validation with the relevant SMEs. Maintain traceable evidence that assigned products and processes meet agreed performance, reliability,