Software Engineering Intern Winter Salary India in United States

About the team Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats to global security that could scale to an extreme level of severity. Our work involves: Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework , and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. About the role As AI agents become more capable at software engineering, and automate more of our internal work, they could become a dangerous cyber threat. People in this role will help OpenAI prepare for security threats from advanced AI agent insiders. In this role, you will: Identify paths by which capable future internal AI agents could compromise OpenAI. Design security controls - focusing on measures with long lead times that benefit from advanced preparation. Stress-test defenses with AI agent evaluations and penetration tests You might thrive in this role if you: Are deeply technical across security and modern infrastructure, and are comfortable digging into the details of operating systems, cloud, containers, CI/CD, or distributed systems. Have strong software engineering skills and enjoy building prototypes yourself. Are interested in engaging with stakeholders and can do so effectively. Bonus: have experience securing cloud infrastructure, and are deeply familiar with core components of the AI stack. Compensation Range: $293K - $405K USD About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy

About the Team Our Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. Within Safety Systems, the Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. About the Role Frontier AI systems are rapidly expanding what is possible in cybersecurity and software engineering. These capabilities create major defensive opportunities, but they also raise serious dual-use and misuse risks across areas such as malware development, exploit discovery, vulnerability chaining, credential abuse, cyber intrusion, and autonomous offensive operations. In this role, you will help define how OpenAI’s models should behave in high-risk cybersecurity contexts. You will develop policy frameworks, threat models, taxonomies, evaluations, and behavioral specifications that guide model behavior across training, deployment, and monitoring systems. This role sits at the intersection of cybersecurity, AI safety, threat modeling, evaluation science, and policy implementation. You will work closely with research, engineering, safety training, preparedness, and product teams to build policies that are technically grounded, measurable, enforceable, and responsive to real-world cyber risk. Your Responsibilities: Design and maintain model policies for cybersecurity and frontier-risk domains, especially dual-use and high-risk cyber capabilities. Translate cybersecurity threat models into clear behavioral specifications, evaluation criteria, grading guidance, and system-level mitigations. Define practical boundaries between legitimate security research, defensive workflows, and assistance that could materially enable harmful activity. Build policy artifacts that support i

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 You will develop and evolve the tooling ecosystem that hardware engineers rely on every day — from hardware compilers and IR transformations to simulation, debugging, and automation infrastructure. The work spans software engineering, compiler concepts, and practical hardware workflows, with direct impact on how quickly and effectively we design next-generation AI systems. You’ll collaborate closely with architects, RTL designers, and verification engineers to translate real engineering friction into durable, scalable tooling solutions. In this role you will: Build and improve the software tooling that makes hardware teams faster: compilation, IR transforms, RTL generation, simulation, debug, and automation. Extend and integrate hardware compiler stacks (frontends, IR passes, lowering, scheduling, codegen to Verilog/SystemVerilog) and connect them to real design workflows. Improve developer experience and reliability: reproducible builds, better error messages, faster iteration loops, and dependable CI and regression infrastructure. Work closely with designers and verification engineers to turn real pain points into durable tools. Dive into RTL when needed: read and reason about Verilog/SystemVerilog to debug issues, validate tool output, and improve debuggability. Be willing to go all the way down the stack when necessary, including gate-level views, synthesis results, and implementation artifacts. Help enable PPA optimization loops by building analysis and au

About the Team The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time. About the Role We’re looking for applied AI engineers to help bring Codex agents from impressive demos to dependable tools. This role is about improving agent performance on real software engineering tasks and closing the gap between research capability and real-world usefulness. You’ll work closely with research, infrastructure, and product to ensure agents are not just powerful, but useful, steerable, and reliable in practice. The job is not only to improve model behavior in isolation, but to turn those improvements into measurable gains in solve rate, usefulness, and economic value for users. What You’ll Do Design and iterate on agent behaviors across real-world coding tasks and long-horizon workflows. Work closely with research to develop and run evals to measure agent performance, regressions, failure modes, and edge cases. Improve performance through prompting, tool-use strategies, context construction, and model-facing experimentation. Analyze failures in production and systematically improve robustness and reliability. Build feedback loops and data systems that get better real-task data into evaluation and research. Work with product teams to shape user-facing agent experiences and the interfaces the agent depends on. Help define what “good” looks like for agents completing complex tasks end-to-end. You Might Be a Good Fit If You Ha

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Job Description Central Engineering at Micron Technology, Inc. is a dynamic and integral part of the company, focused on providing essential services and driving innovation across various technical domains. Established nearly five years ago, Central Engineering initially concentrated on creating economies of scale and enhancing efficiency for the Technology Products Group (TPG). Over the past three years, the team has evolved to deliver industry-first products, develop core design process automation, and produce powerful AI and Data Science tools. As a CAD in CE Memory CAD Engineer at Micron, we work in a fast-paced and collaborative environment. We provide production support role by evaluating, developing, enhancing and debugging both in-house and commercial EDA tools and flows for the design, physical layout, and verification of CMOS integrated circuits! The right person will have be developing and applying CAD software engineering methods, theories and research techniques in support of the organization's product development! Assignments include crafting and developing CAD software, assessing architecture and hardware limitations, and defining and implementing CAD software engineering applications. Responsibilities: Innovating to develop tools, flows, and methodologies to increase the design efficiency and quality of our memory designs on NAND/DRAM/HBM Providing training, documentation, and support to end-users o

About the Team pAGI Infra team builds and operates the systems that make large-scale model training and evaluation reliable, efficient, and easy to run. Our work spans distributed training infrastructure, inference and grading platforms, compute scheduling, and research tooling. We partner closely with researchers and engineering teams to turn new research needs into dependable infrastructure, improve GPU efficiency, and shorten the path from an experiment to a validated model. About the Role We’re looking for an AI Systems Engineer to help scale the infrastructure behind our training and evaluation workflows. You’ll own projects from identifying bottlenecks and designing solutions through deployment and operation. The work combines distributed systems engineering, performance optimization, and close collaboration with researchers. You might build a shared grading service, improve resource allocation across workloads, or bring a new training stack into production — directly improving how quickly and reliably research moves forward. In this role, you will: Build and operate infrastructure for large-scale training and evaluation, improving reliability, throughput, and resource efficiency. Develop shared inference and grading platforms with automated capacity management, health monitoring, and visibility into performance. Improve compute scheduling and resource allocation to reduce idle GPU time and help workloads recover quickly from failures. Diagnose bottlenecks across training, inference, and orchestration, and work across teams to improve end-to-end performance. Build self-service tools, automated validation, and observability that help researchers launch experiments, diagnose issues, and compare results with less manual intervention. You might thrive in this role if you: Are excited about the potential of personal AGI and want to build the infrastructure that enables it. Have strong software engineering fundamentals and experience building or operating large-scal

About the Team OpenAI’s User Operations team shepherds our customer’s adoption of AI and ensures that our customers' product experience is nothing short of exceptional. We are building the very first post-AGI support team. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We are looking for a Support Program Manager to join our Support Delivery team. This role is an exciting opportunity to help define and implement foundational support practices that will scale with OpenAI’s growth. You will lead efforts to establish new operational frameworks, driving process alignment with various internal teams, and leading tooling and automation projects. This position offers the chance to make a significant impact in shaping customer experience while collaborating across multiple teams. We’re looking for people who thrive at the intersection of project management, systems building, data science/data engineering/software engineering, team enablement, and customer advocacy – and enjoy working cross-functionally in a fast-paced, evolving environment. This role is based in San Francisco, CA, and follows a hybrid work model of 3 days in-office per week. Relocation assistance is available. In this role, you will: Lead support delivery programs for Tier 3 frontline delivery for our most strategic customers, including productivity and workflow improvements, team operations, and knowledge management for the Support Delivery team Partner with Support Delivery and cross-functional leadership to define the experience, stand up the program, manage pilots and rollout, and ensure premium operations and playbooks st

As a Forward Deployed Engineer on the Feature Flags team, you'll partner directly with customers to accelerate their feature flag implementations — from initial architecture consulting through prototype builds to full-scale migrations. This role is for someone who wants to write code with customers, not just advise them. You'll work hands-on inside customer codebases to unblock complex, high-stakes deployments, directly influencing deal velocity and customer success. Working closely with Sales, Solutions, and Engineering, you'll be the technical force that turns a signed contract into a live, adopted implementation. What You'll Do: Serve as the hands-on technical partner for strategic customers implementing Datadog Feature Flags, from pre-sales technical validation through post-sales delivery Consult on flag architecture and implementation approach for complex environments — multi-service, multi-platform, high-scale deployments Build prototype flag implementations directly in customer codebases to prove value and de-risk technical decisions early in the sales cycle Implement flags across diverse and advanced deployment modes (server-side, client-side, edge, mobile, streaming/real-time) tailored to each customer's stack Drive full flag migrations to completion — including legacy system cutover — efficiently and with minimal customer engineering burden Identify patterns across customer implementations and feed them back to Product and Engineering to improve the core product and reduce future implementation time Collaborate closely with Engineering on technical edge cases, product gaps, and implementation tooling Partner with Sales and Solutions to accelerate deal cycles by removing technical risk and uncertainty Who You Are: 5 years of professional software engineering experience, with hands-on coding ability across the stack you're deployed into Experience with feature flagging, experimentation, or config management systems (internal or vendor) Comfortable dropping i

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As a Data Engineer, you’ll be responsible for laying the foundation for a best-in-class analytics function. You’ll partner closely with our engineering team and business stakeholders to ensure that our analytics stack and processes meet the business needs today with an eye towards the future. Visit our Vanta Engineering Blog to learn more about what our team is working on! What you’ll do as a Senior Data Engineer at Vanta: Design and deploy data infrastructure needed to drive data-driven decision-making solutions Design and implement complex data orchestration models, modeling metadata, scaling reporting tools for data science and ML products users Be the company’s expert on data administration, data management and scalable data systems Write highly tuned, scalable SQL queries running over large-scale, heterogeneous data warehouses Work with the Product and Enterprise Engineering system teams to structure source systems for reporting consumption across the enterprise Help maintain CDC pipelines to power customer reporting Help develop front end applications to expose analytical data sets enterprise wide How to be successful in this role: Have at least four years of experience working with data and two years of experience in Software Engineering or a related field. Have experience with common analytics tooling (e.g. Stitch/Fivetran, Snowflake/BigQuery/Redshift, dbt, Airflow, Dagster). Have good working knowledge of AWS data infra systems and Terraform. Bring a system-oriented and software engineering mindset to the Data Engineering practice. We’re looking to build frameworks that manage data, and minimize bespoke queries Deep kn

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Job Summary We are looking for a GTM DevOps Engineer to join our Business Systems team and own the reliability, automation, and delivery infrastructure behind our Go-To-Market (GTM) technology stack. This role sits at the intersection of platform reliability and CI/CD engineering, ensuring that our critical business systems — including Salesforce, NetSuite, MuleSoft, Workato, and an expanding portfolio of AI-powered workloads — are deployed consistently, operate resiliently, and scale with the business. You will partner closely with Business Systems developers, architects, and business stakeholders to build and maintain the pipelines, monitoring frameworks, and operational standards that keep our GTM systems healthy and our release cycles fast and predictable. As our team builds and deploys AI agents across GCP Cloud Run and AWS Bedrock AgentCore, you will serve as the infrastructure and deployment owner for these workloads — bringing engineering discipline to an environment where AI-generated code is increasingly entering production. This is a hands-on engineering role for someone who thrives in complexity, takes ownership of platform uptime, and brings a software engineering mindset to business application operations — directly supporting GTMSOE's broader mission of operational excellence across the GTM org. Key Responsibilities CI/CD & Release Engineering Design, build, and maintain CI/CD pipelines for Salesforce (SFDX/Salesforce CLI), NetSuite (SuiteScript/SuiteBundler), MuleSoft (Anypoint Platform), and Workato; establish branching strategies, environment promotion standards, and release gatin

Here at Datadog, we think about offensive security a little bit differently. We embrace automation and AI to run adversary simulations continuously across a massive cloud-native environment, and we expect our offensive engineers to build the tooling that makes that possible. We're looking for a Senior Security Engineer who can execute sophisticated red team operations, write the code that scales them, and take an AI-first approach to offensive security engineering. At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Plan and execute red team engagements end-to-end, simulating real-world threat actors across cloud infrastructure (AWS, GCP), Kubernetes, CI/CD pipelines, and corporate environments Build and maintain custom offensive tooling, automation frameworks, and engagement infrastructure, treating offensive operations as a software engineering problem Develop custom payloads and evasion capabilities tailored to Datadog's environment and modern defensive controls (EDR, SIEM, network monitoring) Improve the efficiency of offensive operations through thoughtful use of automation and AI, accelerating reconnaissance, vulnerability analysis, and reporting workflows Partner with the Detection & Response team on purple team exercises to validate detection logic, improve alert fidelity, and influence threat models Translate offensive findings into concrete improvements by working directly with defensive security and engineering teams to close gaps Who You Are: You have 5+ years of hands-on experience in offensive security (red teaming, penetration testing, or adversary simulation) with a track record of operating against mature, well-defended environments You write production-quality code (Python, Go, or similar), can build your own tools, and automate your w

About the Role As Enterprise Sales Manager, Banking, you will build and lead a team of Account Directors focused on driving strategic growth across the world’s largest banking institutions. You’ll be a hands-on front-line leader responsible for helping your team navigate complex enterprise sales cycles, deepen executive relationships, and drive adoption of OpenAI’s platform across highly regulated banking environments. This role will shape how OpenAI partners with global banks as they rethink productivity, operations, customer engagement, risk management, and software development through AI. You will help define the GTM strategy, operating model, and industry playbook for one of OpenAI’s most strategic verticals. Key Responsibilities Recruit, develop, and lead a high-performing team of Account Directors focused on large enterprise banking institutions across North America. Create a strong coaching culture with frequent deal reviews, account strategy sessions, ride-alongs, and structured 1:1s that elevate team performance. Define and refine the GTM strategy for banking, including account prioritization, executive engagement strategy, and territory planning. Drive disciplined pipeline generation, forecasting accuracy, and operational rigor across a complex enterprise sales motion. Guide teams through highly consultative, multi-stakeholder opportunities involving technology, security, compliance, legal, and procurement stakeholders. Help customers translate AI and API capabilities into measurable business outcomes across banking use cases such as employee productivity, customer operations, risk and compliance, software engineering, knowledge management, and workflow automation. Lead teams selling into highly regulated environments with a deep understanding of banking-specific risk, governance, and data security considerations. Partner closely with Product, Solutions Architecture, Technical Success, Legal, Security, and Finance to help customers successfully deploy AI a

About the Team OpenAI’s User Operations team shepherds our customer’s adoption of AI and ensures that our customers' product experience is nothing short of exceptional. We are building the very first post-AGI support team. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We are looking for a Technical Program Manager to join our Senior Support Engineering team. This role is an exciting opportunity to help define and implement foundational support practices that will scale with OpenAI’s growth. You will lead efforts to establish new operational frameworks, driving process alignment with various internal teams, and leading tooling and automation projects. This position offers the chance to make a significant impact in shaping customer experience while collaborating across multiple teams. We’re looking for people who thrive at the intersection of project management, systems building, data science/data engineering/software engineering, team enablement, and customer advocacy – and enjoy working cross-functionally in a fast-paced, evolving environment. This role is based in San Francisco, CA, and follows a hybrid work model of 3 days in-office per week. Relocation assistance is available. In this role, you will: Lead support delivery programs for Tier 3 frontline delivery for our most strategic customers, including productivity and workflow improvements, team operations, and knowledge management for the Support Delivery team Partner with Support Delivery and cross-functional leadership to define the experience, stand up the program, manage pilots and rollout, and ensure premium operations and

About OpenAI OpenAI is dedicated to ensuring that artificial general intelligence (AGI) benefits all of humanity. Our mission requires building not only world-class AI models, but also the infrastructure that enables those models to be deployed reliably, efficiently, and at global scale. As demand for AI continues to grow, we are expanding the ways OpenAI can bring high-performance inference capacity online across a diverse hardware ecosystem. About the Team The GPT Infrastructure team builds software that turns advanced inference and optimization research into production products. One focus is enabling strategic infrastructure partners and accelerator vendors to qualify and onboard new compute without a bespoke porting and optimization effort for every hardware platform. We build the control planes, APIs, secure partner-side execution environments, evaluation systems, artifact pipelines, and operational tooling that make these workflows repeatable and trustworthy. The work sits at the intersection of distributed systems, AI inference, compilers and runtimes, performance engineering, security, and external partnerships. About the Role We are seeking an experienced systems generalist who can work comfortably across the stack to help build an automated inference optimization platform. Given a workload, target hardware profile, compiler and runtime context, and a trusted verifier, the system runs durable optimization campaigns that generate, compile, execute, grade, and improve candidate kernels, runtime configurations, and serving-stack changes. You will design both the OpenAI-hosted control plane and the partner-side software that evaluates candidates on real accelerator hardware. The product must keep long-running workflows reliable, make performance results reproducible, and maintain clear trust boundaries around sensitive model and hardware information. This is a deeply cross-stack role, combining strong software engineering fundamentals with systems thinking and

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About The Role Millions of people rely on Notion to do their most important work, and protecting that trust is foundational to everything we build. We’re looking for a hands-on Detection Engineer to build and operate the systems and workflows we use to detect and respond to attacks across Notion’s cloud-native environment. You’ll ship high-signal detections, improve the platform that powers them, participate in incident response, and help shape how detection and response engineering scales at Notion. You’ll work closely with Engineering, Corporate Security, and Infrastructure, with broad latitude to identify gaps, prioritize investments, and build what’s needed next. We view detection and response as a software engineering discipline: detections are code, platforms are products, and measurement matters What You'll Achieve Design and maintain high-signal detections across cloud, identity, endpoints, and SaaS environments. Build and improve the detection platform, including rule lifecycle management, tuning, measurement, and rollout safety. Develop tooling and automation that accelerate triage, enrichment, investigation, and detection