Software Engineer Core Interfaces Salary India Jobs

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About the Team The AI Platform team is a newly formed team at the center of Mixpanel's AI-first analytics vision. With a greenfield charter, we're building the infrastructure that accelerates and transforms AI product development at Mixpanel, both internally and for our customers. We provide the tools to improve AI products, enabling internal teams and customer agents to build things that were previously unimaginable. We build shared infrastructure that is essential for developing AI features with confidence and speed, and that gives every agent the tools, context, and quality guarantees to act autonomously on behalf of users. Some examples of what we are building: Agent Optimization Framework: A system that optimizes AI products for quality, speed, and cost, using metrics from production and evals, given the context of the invocation. AI Agent Integrations and Accessibility: Products and tools that bring the power of Mixpanel to wherever it is most effective for our customers, including a Mixpanel slackbot, MCP, and a public skills library. AI Engine: Services that centralize core AI and LLM functionality at Mixpanel in order to accelerate AI development, compound the value of AI efforts, and provide customers with a consistent experience. Role Overview We are looking for a driven Software Engineer to join our AI Platform team. You will be responsible for building the scalable, secure, and reliable infrastructure that accelerates AI agent development. You will be a leader and key contributor in a small, fast paced, newly formed team with a mandate to empower AI development across the c

About the Role: As a Staff Software Engineer on the ML Infrastructure team, you will collaborate closely with the Machine Learning and Product teams to build world-class machine learning inference platforms. These platforms power essential services like personalized recommendations, search, and content understanding across Tubi. A core responsibility of this team is developing and maintaining low-latency ML model serving systems that support Deep Learning, LLM, and Search models. This involves building self-service infrastructure and critical components such as the inference engine, feature store, vector store, and experimentation engine. You will improve the way we deploy and operate our services and even contribute to open-source projects. This role grants the architectural freedom to explore new frameworks, lead critical cross-functional projects, and transform the capabilities of our ML and Product teams. Responsibilities: Design and build scalable, high throughput, and low latency distributed systems using Scala Build reusable components and services that serve various ML applications like Personalization, Search, Ads and Exploration Partner closely with ML engineers to understand their challenges and limitations and develop scalable solutions to address them. Proactively recommend solutions to keep our ML Inference stack state of the art. Take a data driven approach to identifying & optimizing latency, cost, and efficiency of our infra. Lead large scale cross functional refactorings if necessary Mentor other engineers on the team on system design, effective incident management, interviewing, leveraging LLMs for work, etc. Collaborate with ML, Product, and cross functional engineering teams to define the long term vision and architecture for ML Infrastructure at Tubi. Your Background: Experience designing and building scalable, distributed systems in any modern backend language (e.g., Scala, Java, Python, Go, C++); experience with Scala or JVM b

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Software Engineer, you will own the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Design and implement scalable backend systems for Federal customers using cloud-native AI infrastructure. Build features for agentic systems including multi-layered guardrails and data retrieval optimization. Develop data pipelines and machine learning infrastructure to make data sources accessible by agents. Collaborate with cross-functional teams to execute backend solutions for secure environments. Participate in customer engagements to understand requirements and deliver technical solutions. Define requirements with stakeholders and implement features until they are accepted. Contribute to the platform roadmap and product strategy for the Federal business. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes

About the Team DoorDash’s GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is running frontier open-weight LLMs and VLMs (such as GLM, Qwen, Kimi, and DeepSeek) ourselves — real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs — delivering large cost and latency wins (for example, a billion embeddings produced roughly 20× cheaper and visual models served roughly 72% cheaper). We also own core platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, leading the design and architecture of our open-weights model platform spanning inference and fine-tuning: real-time GPU serving, high-throughput batch inference, and model fine-tuning. You’ll set technical direction across model serving and inference engines, fine-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability, and mentor engineers as you go. This role is ideal for a senior engineer who enjoys owning ambiguous, high-impact systems and pushing the cost/performance frontier of GPU inference and fine-tuning in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and cost/performance tradeoffs are evolving quickly. You’re excited about this opportunity because you will… Lead the design of infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Own and evolve our open-weights serving stack — real-time GPU endpoints, high-thr

About the Team The Fleet team builds core components to enable productive research from small to state of the art scale across OpenAI, with the goal of accelerating progress towards AGI. We frequently collaborate with other teams to speed up the development of new state-of-the-art capabilities. About the Role As we scale up with more researchers and engineers joining OpenAI, we seek a pragmatic and passionate engineer with a strong focus on the development experience for both engineers and scientists. In this role, you will be responsible for building and maintaining systems that allow our research + engineering organization to iteratively develop, test, and deploy new features reliably, with high velocity, and with a frictionless and fast development cycle. You will help oversee and drive to the vision of how we should build, test and deploy software. You will drive the design of our continuous integration pipelines, testing infrastructure, training and support around our build system. Our current environment relies heavily on Python, Rust, and C++, which you will take ownership of and strive to transform into a state of the art development experience for research. Ultimately, your role will be to provide the necessary tools and metrics to support our fast-paced culture and ensure a stable, scalable platform for growth, while also fostering a seamless and low friction experience for OpenAI’s research. This role is based in San Francisco, CA. For a San Francisco role, we use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. You might thrive in this role if you: Have supported large monorepo development and deployment before Are a proficient Python programmer working in large monorepos Are proficient with Docker and Kubernetes Experienced in CI/CD 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 boun

Technical Skills: Java Programming: Solid understanding of core Java concepts such as OOP (Object-Oriented Programming), data structures, exception handling, multithreading, and collections. Java Frameworks: Basic experience with popular Java frameworks like Spring and Hibernate. Familiarity with Spring Boot for developing microservices is a plus. Web Technologies: Basic knowledge of web development technologies including HTML, CSS, and JavaScript. Exposure to frontend frameworks like Angular or React is advantageous. Databases: Understanding of relational database concepts and basic SQL. Experience with databases such as MySQL or PostgreSQL. Version Control: Familiarity with Git and basic version control concepts, such as branching and merging. Build Tools: Experience with build tools like Maven or Gradle for project management and dependencies. Integrated Development Environment (IDE): Proficiency in using IDEs like IntelliJ IDEA, Eclipse, or NetBeans for Java development. RESTful Web Services: Basic understanding of RESTful services and APIs. Experience in creating simple RESTful APIs is beneficial. Testing: Exposure to unit testing frameworks like JUnit or TestNG. Understanding of basic test-driven development (TDD) practices. Agile Methodology: Basic understanding of Agile software development practices, including working within a team using Scrum or Kanban. Soft Skills: Problem-Solving: Ability to analyze problems and develop logical solutions, with a willingness to learn and adapt to new challenges. Communication: Good verbal and written communication skills, with the ability to articulate technical concepts to both technical and non-technical audiences. Team Collaboration: Experience working in a team environment, contributing to collaborative projects, and participating in code reviews. Time Management: Ability to manage time effectively, prioritize tasks, and meet deadlines. Attention to Detail: Strong attention to detail, ensuring code quality and

Technical Skills: Java Programming: Solid understanding of core Java concepts such as OOP (Object-Oriented Programming), data structures, exception handling, multithreading, and collections. Java Frameworks: Basic experience with popular Java frameworks like Spring and Hibernate. Familiarity with Spring Boot for developing microservices is a plus. Web Technologies: Basic knowledge of web development technologies including HTML, CSS, and JavaScript. Exposure to frontend frameworks like Angular or React is advantageous. Databases: Understanding of relational database concepts and basic SQL. Experience with databases such as MySQL or PostgreSQL. Version Control: Familiarity with Git and basic version control concepts, such as branching and merging. Build Tools: Experience with build tools like Maven or Gradle for project management and dependencies. Integrated Development Environment (IDE): Proficiency in using IDEs like IntelliJ IDEA, Eclipse, or NetBeans for Java development. RESTful Web Services: Basic understanding of RESTful services and APIs. Experience in creating simple RESTful APIs is beneficial. Testing: Exposure to unit testing frameworks like JUnit or TestNG. Understanding of basic test-driven development (TDD) practices. Agile Methodology: Basic understanding of Agile software development practices, including working within a team using Scrum or Kanban. Soft Skills: Problem-Solving: Ability to analyze problems and develop logical solutions, with a willingness to learn and adapt to new challenges. Communication: Good verbal and written communication skills, with the ability to articulate technical concepts to both technical and non-technical audiences. Team Collaboration: Experience working in a team environment, contributing to collaborative projects, and participating in code reviews. Time Management: Ability to manage time effectively, prioritize tasks, and meet deadlines. Attention to Detail: Strong attention to detail, ensuring code quality and

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Staff Software Engineer, you will orchestrate the implementation of vertical features and horizontal capabilities to include mentoring other engineers on defining requirements with stakeholders and communication tradeoffs of technical implementations on feature and capabilities until they are accepted by the stakeholders. You will: Orchestrate feature implementation across the Federal engineering team to ensure architectural consistency. Define technical strategy for agentic guardrails, explainability, and fleet orchestration. Ensure system reliability and performance across multiple security classifications and network types. Mentor engineers in the process of defining requirements with stakeholders and gathering acceptance. Communicate high-level technical trade-offs and implementation strategies to senior government stakeholders and Scale C-Suite members. Influence the long-term product strategy and technical roadmap for the Federal business unit. Consult on the architecture of AI-powered solutions for large-scale federal contracts. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Senior Software Engineer, you will lead the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers. Manage the full lifecycle of feature development from requirement definition to deployment on classified networks. Direct the orchestration of asynchronous agent fleets to meet mission requirements. Lead customer engagements to translate mission needs into technical requirements. Own the communication with stakeholders to ensure implementation meets defined acceptance criteria. Conduct technical reviews and identify risks within machine learning infrastructure and model serving. Drive the platform roadmap by providing technical specifications for Federal product offerings. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and contai

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Engineering at Brex Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders. What you'll do As a Senior Software Engineer on the Accounting Engineering team, you will build the platform and product surfaces that turn Brex activity into accurate, usable accounting data. Accounting is a core component of our product offering and often a strategic differentiator. Your focus will be the systems finance teams depend on to close their books: reusable accounting records, rules, and mappings, reliable ERP integrations with NetSuite, QuickBooks, Xero, and others, and AI-native automation that predicts accounting w

This position is based in Vancouver, BC , within Diligent’s Technical Center of Excellence. We are currently hiring candidates who are based in or able to work from Vancouver . Software Engineer — Platform AI Service Levels: Software Engineer II Senior Software Engineer Staff Software Engineer Location: Vancouver Position Overview As a Software Engineer on Diligent's Platform AI team, you'll help design, build, and operate the core services that power AI-driven capabilities across Diligent's global product suite. You'll build secure, scalable, serverless services on AWS that translate AI research and models into commercial-quality, production-ready solutions — enabling customers to derive insights from their governance data. You'll work closely with AI researchers, product managers, and other engineering teams, owning your services end-to-end: architecture, implementation, deployment, and monitoring. The team operates with a strong AI-augmented engineering culture — using AI tools to accelerate coding, testing, debugging, and delivery — while applying sound judgment about when and how to apply them. Key Responsibilities Design and implement secure, scalable, fault-tolerant, high-performing solutions using AWS serverless technology — event-driven, highly observable, and built with infrastructure as code. Collaborate with AI researchers/engineers to translate AI and LLM capabilities into robust, production-grade services, and help other teams integrate them. Build and maintain the pipelines needed to deploy, monitor, and manage AI services at scale — observable, resilient, and cost-effective. Use AI-powered development tools (code assistants, test generation, architecture exploration) responsibly to accelerate delivery and improve quality, always validating outputs. Participate in architecture discussions and design reviews, and contribute to product design by understanding customer problems — especially where AI can offer a breakthrough solution. Work in

Envoy Global is a proven innovator in the global immigration space. Our mission combines our industry-leading tech platform with holistic service to streamline, simplify and expedite the immigration process for employers and individuals. We are looking for a passionate Software Engineer to join our dynamic feature team in Hyderabad, India. This team works on complex technical challenges, employs creativity and constantly learns a variety of frameworks, tools and technologies. As our Software Engineer, you will be required to: Contribute to tech grooming backlog items providing design, architecture, and implementation details Quality is the key driver to successful delivery, ensure highly testable and quality deliverables Leverage troubleshooting and analytical skills to analyze issues Experience with debugging, performance profiling and optimization Develop code within C#, ASP. NET,.Net Core, Entity Framework, Web API, Typescript/ Angular To apply for this role, you should possess the following skills, experience and qualifications: Expertise in C#, Angular, ASP.NET Web API, .Net Core, Entity Framework Hands on experience with SQL Azure experience is a plus but not a deal breaker Knowledge and experience with Html, CSS, JavaScript 2 years to 4 years of strong programming experience with C# and ASP.NET Bachelor’s Degree or above Ready to code, collaborate, and create impact? Submit your updated resume and let’s start your journey with Envoy Global.!!

About the Team DoorDash is a data driven organization and relies on timely, accurate and reliable data to drive many business and product decisions. The Core Data Platform organization owns all the infrastructure necessary to run an operationally efficient analytical data stack. About the Roles The Data Platform team spans data mobility frameworks, ingestion, infrastructure, tools, and governance. Together, they design and operate scalable compute and ingestion frameworks using technologies such as Spark, Flink, Kafka, Airflow, and modern lakehouse solutions, while also building abstractions and tools that simplify data workflows for engineers, analysts, and ML practitioners. In parallel, these teams establish strong data quality, cataloging, privacy, and compliance standards to ensure trust in analytics and regulatory adherence. As relatively high-impact teams, they offer engineers the opportunity to shape the roadmap, influence core platform decisions, and directly enable DoorDash’s business-critical insights and real-time personalization capabilities. You must be located in San Francisco, CA, Sunnyvale, CA, Seattle, WA, or New York, NY. You're excited about this opportunity because you will… Drive vision & strategy for building the frameworks charter and position it to handle the challenges of a rapidly growing business. Scale the analytical platform for the increasing amounts of data and use cases. You will bring your expertise in building and operating high scale systems with a focus on reliability, scalability and cost efficiency. Collaborate with stakeholders building solutions on top of the platform Foster a positive and supportive work culture, upleveling others. We're excited about you because you have… B.S., M.S., or PhD. in Computer Science or equivalent. 2+ years of industry experience at our I4 level, 5+ years of industry experience at our I5 level Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in th

We are seeking a Software Engineer to join our growing Gurugram Products & Technology team to develop and expand core parts of a new platform we are building to make it easier for customers to build AI applications using MongoDB. As a Software Engineer on this new team, you will be responsible for developing cutting edge technologies related to enabling deployment at scale of AI applications. You will take on challenging, high-visibility projects that improve and enhance the performance, scalability, and reliability of the distributed systems infrastructure for this new product. MongoDB engineering teams pride themselves on building high-quality software and living MongoDB cultural values every day – we value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Position Expectations Work closely with research, product management, product engineering, product design, peers as well as other teams within the company to implement the first version and future evolution of the service Design, build and deliver well-tested core pieces of the platform in collaboration with other vested parties Contribute to shaping architecture, code reviews and development practices, developer experience as the teams and product grow Mentor fellow engineers and assume ownership and accountability of projects Qualifications Strong background in building core components for high scale compute and data distributed systems 3+ years experience of building distributed systems, and/or foundational cloud services at scale and an interest in working with Python, Go and Java Proven success in designing, writing, testing, debugging, performance tuning, possessing a strong grip on the foundational materials of computer science and maintaining distributed and/or highly concurrent software systems in large, long-

About the Team We’re hiring Software Engineers to join our broader Infrastructure organization, which supports multiple high-impact teams. Depending on your interests and experience, you could work on one of several focus areas—including Core Distributed Systems, Reliability Engineering, Observability, Developer Productivity or Cloud Infrastructure. About the Role All teams are deeply collaborative, work on mission-critical services, and are responsible for building distributed, scalable infrastructure to bring OpenAI’s technology to the world through products like ChatGPT and the OpenAI API. You’ll work closely with stakeholders to understand infrastructure, data and compute needs, setting the technical strategy that supports cutting-edge research and product development. This is a critical role for someone who is passionate about solving complex engineering problems at scale, ensuring their performance, scalability and reliability Team Focus Areas Distributed Systems: Owning and building important, highly scalable, available, performant, and reliable distributed systems (and their building blocks) to power the entire stack at OpenAI Systems Engineering: Work across layers of the stack—debugging system bottlenecks, evolving core infrastructure, and solving novel problems in performance and scalability. Reliability Engineering: Build scalable, fault-tolerant systems and lead efforts around service health, incident response, and resilience. Observability: Design and maintain observability tooling (metrics, logs, tracing) to give teams visibility into production systems at scale. Developer Productivity: Create tools, environments, and workflows that help engineers ship high-quality software faster and more safely. Cloud Infrastructure: Own the cloud-native infrastructure (compute, networking, storage) that underpins all services and research workloads. Databases: Building high performance, distributed database systems that power all of OpenAI's product stack. In this