Python Developer in United States

About Pinecone Pinecone is the knowledge infrastructure for AI at scale. Its leading vector database and knowledge engine, Pinecone Nexus, power accurate, performant AI applications for more than 9,000 customers and 800,000 developers worldwide. Pinecone's mission is to make AI knowledgeable. Pinecone is based in New York and raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital. About the Team and Role: We are hiring a senior/staff software engineer to help design and build core components of our next-generation knowledge retrieval system built for the AI era – search and retrieval infrastructure that powers high-quality, scalable, and enterprise-grade agentic systems. You’ll build the framework that allows our customers to connect knowledge–synthesized from structured and unstructured data–to modern LLM-powered applications, leveraging the world’s best-in-class vector DB supporting semantic search and hybrid retrieval. This role is ideal for someone who loves backend system architecture, distributed systems, and applied AI infrastructure. It is a high impact role with significant ownership across architecture, performance, and system reliability. Responsibilities: Design and build scalable platform components leveraging advanced retrieval via query planning, semantic and hybrid search, metadata-aware search, and LLM generation Design and build optimized indexing pipelines for structured and unstructured data Build backend services for semantic and hybrid retrieval, knowledge graph construction, and retrieval orchestration Improve retrieval quality through evaluation and observability frameworks Design APIs for internal and external user and agentic consumers Optimize latency, throughput and cost across large-scale inference and retrieval workloads Drive technical direction for reliability and security What You’ll Bring to the Table: To thrive in this role, you don't need to check every single box, but you should be deep

About Pinecone Pinecone is the knowledge infrastructure for AI at scale. Its leading vector database and knowledge engine, Pinecone Nexus, power accurate, performant AI applications for more than 9,000 customers and 800,000 developers worldwide. Pinecone's mission is to make AI knowledgeable. Pinecone is based in New York and raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital. About the Team and Role: We are hiring a senior/staff software engineer to help design and build core components of our next-generation knowledge retrieval system built for the AI era – search and retrieval infrastructure that powers high-quality, scalable, and enterprise-grade agentic systems. You’ll build the framework that allows our customers to connect knowledge–synthesized from structured and unstructured data–to modern LLM-powered applications, leveraging the world’s best-in-class vector DB supporting semantic search and hybrid retrieval. This role is ideal for someone who loves backend system architecture, distributed systems, and applied AI infrastructure. It is a high impact role with significant ownership across architecture, performance, and system reliability. Responsibilities: Design and build scalable platform components leveraging advanced retrieval via query planning, semantic and hybrid search, metadata-aware search, and LLM generation Design and build optimized indexing pipelines for structured and unstructured data Build backend services for semantic and hybrid retrieval, knowledge graph construction, and retrieval orchestration Improve retrieval quality through evaluation and observability frameworks Design APIs for internal and external user and agentic consumers Optimize latency, throughput and cost across large-scale inference and retrieval workloads Drive technical direction for reliability and security What You’ll Bring to the Table: To thrive in this role, you don't need to check every single box, but you should be deep

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Our Fraud team's mission is to help companies detect and prevent fraud using Plaid's financial network data. We believe that transaction patterns, device signals, identity linkages, and behavioral data are dramatically underleveraged tools in fraud prevention. Our products — including Protect and Signal — operate at network scale and depend on real-world investigation and research to stay ahead of adaptive adversaries. As a Senior Fraud Researcher, you will sit at the intersection of live fraud investigation, applied data science, and product innovation. You will lead complex investigations, translate findings into detection improvements, and collaborate tightly with Data Science, ML, and Product teams to shape the next generation of Plaid's fraud capabilities. This is not a purely operational role — your research directly drives features, model inputs, and product design. Responsibilities: Live Fraud Investigation & Reconstruction Lead investigations into complex fraud cases across identities, accounts, devices, and transaction surfaces Provide support to day-to-day fraud operations including SEVs and alert triage Reconstruct attacker sequences and hypothesize actor intent and tooling Distill p

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Our Fraud Intelligence team's mission is to turn fraud signals into insight that our EPD teams transform into improvements across Protect, IDV, Signal, and Guaranteed Payments. We believe transaction patterns, device signals, identity linkages, and behavioral data are dramatically underleveraged tools in fraud prevention, and we ground our products in what adversaries are actually doing right now. As the Fraud Intelligence Lead, you will build and run a small, high-leverage team of Fraud Intelligence Analysts (and eventually a Staff Researcher) responsible for live casework across Protect, IDV, and Payments/ACH. You'll operate as a player-coach, hiring and coaching your team while staying close enough to the work to personally pick up casework and SEV response when needed. Responsibilities Team Building & People Leadership Set the casework quality bar: define what rigorous investigation, triage, and reporting look like for the team Coach analysts on investigation technique, pattern synthesis, and translating findings into product/model input Operating Model & Cross-PA Partnership Own coverage allocation across the Protect/IDV and Payments/ACH pods, including flexing assignments as volume shi

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Making data driven decisions is key to Plaid's culture. To support that, we need to scale our data systems while maintaining correct and complete data. We provide tooling and guidance to teams across engineering, product, and business and help them explore our data quickly and safely to get the data insights they need, which ultimately helps Plaid serve our customers more effectively. Engineers on Data Infrastructure are domain experts in Data Warehouse, Data Lakehouse, Spark, Workflow Orchestration, and Streaming technologies. We scale our existing data pipelines in a performant and cost efficient way while creating the necessary abstractions to make developing on top of this platform extremely simple for other engineers at Plaid. Responsibilities Contribute towards the long-term technical roadmap for data-driven and machine learning iteration at Plaid Leading key data infrastructure projects such as improving ML development golden paths, implementing offline streaming solutions for data freshness, building net new ETL pipeline infrastructure, and evolving data warehouse or data lakehouse capabilities. Working with stakeholders in other teams and functions to define technical roadmaps for key backe

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. The Security Governance, Risk, and Compliance (GRC) team is part of Plaid’s security organization, focused on enabling the business by proactively managing information security risks and maintaining effective controls. Our mission is to reduce the likelihood and impact of security risks while operating a robust assurance program that builds trust with our customers, consumers, and data partners. We own Plaid’s security compliance frameworks, run our audits and risk programs, and partner across the company to keep Plaid’s platform secure, resilient, and aligned with industry and regulatory expectations. GRC Engineering is how we make all of that scale — turning compliance into code, evidence into telemetry, and audits into a continuous, automated capability. The Role: You will own GRC Engineering at Plaid — a foundational, high-ownership role defining an emerging discipline from the ground up. Today most of our compliance work is manual and point-in-time; you will turn it into an engineered system that is continuous, data-driven, and scalable, and set the technical direction for the field. You will: Define the discipline and the architecture — how GRC Engineering works at Plaid, not just execute with

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Making data-driven decisions is key to Plaid's culture. To support that, we need to scale our data systems while maintaining correct and complete data. We provide golden datasets and tooling to teams across engineering, product, and business and help them explore our data quickly and safely to get the data insights they need, which ultimately helps Plaid serve our customers more effectively. In addition, Plaid will not be successful if we can't move quickly. We build the data systems and tools that enable everyone at Plaid to be data-driven, making analytics easy, obvious, and proactive across the company. Data Engineers heavily leverage SQL and Python to build data workflows that integrate with our Golang applications. We use tools like DBT, Airflow, Redshift, Atlan, and Retool to orchestrate data pipelines and define workflows. We work with engineers, product managers, business intelligence, data analysts, and many other teams to build Plaid's data strategy and a data-first mindset. You will be in a high impact role that will directly enable business leaders to make faster and more informed business judgements based on the datasets you build. You will have the opportunity to carve out the ownershi

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Team Overview The TechOps team is the technical foundation that is a major stakeholder in keeping the company running. We own the systems, tools, and infrastructure that every Plaid employee depends on, from identity and endpoint management to help desk support, office infrastructure, and the internal tooling that powers day-to-day productivity. What sets us apart from a traditional IT team is how we approach our higher-level goals. We treat corporate infrastructure like an engineering problem: configuration lives in code when possible, endpoint provisioning is automated, access assignment is self-service, and we're always looking for ways to make our systems more reliable and our support burden smaller. We're a small team with broad ownership and high standards. We work closely with Security, Engineering, and People teams to make sure Plaid's internal environment is secure, scalable, and ready for where the company is going, whether that's a new office, a new compliance requirement, or a new way of working enabled by AI tooling. Role Overview In this role, you'll take part in our on-call rotation for a few hours each week, but this isn't just a break/fix IT position. It's a chance to build, improve

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Senior Data Scientist - Network Value (Plaid App) The Network Value Data Science team is helping Plaid build an industry-leading fintech consumer network with best-in-class products and user experiences. We are a product analytics team embedded in key product areas across Plaid. We support some of Plaid’s most important OKRs and help execute on product roadmaps. We translate ambiguous product questions into tractable analysis, serve as analytical thought partners throughout the org, identify opportunities to build better products, and champion a data-first decision-making approach everywhere we go. You’ll be a Senior Data Scientist supporting Plaid App, a critical user-facing product within Plaid’s Network Value portfolio. In this role, you’ll become a data and analytical thought partner to product managers and engineers, helping drive data-informed product development as the team launches and scales the product from 0 to 1. You’ll translate business questions into analytics projects, perform ad-hoc and strategic analysis, improve visibility into core systems through data modeling and dashboarding, create OKRs and metrics tied to business goals, and support feature ship decisions through experimenta

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. We are the Data Foundation & AI team within Plaid’s Data organization. Our mission is to build the shared ML and AI infrastructure that powers intelligent capabilities across Plaid’s product suite. We develop the foundational systems, models, and data assets that transform Plaid’s unique financial network data into scalable, general-purpose representations that teams across the company can leverage. Our work spans the full ML lifecycle — from large-scale data curation and model pretraining to production serving, evaluation, and monitoring. As part of the team, you’ll work at the intersection of machine learning infrastructure, applied AI, and distributed systems, helping establish the core AI platform that enables innovation across Plaid. As a Staff Machine Learning Engineer, you will lead the technical strategy and development of Plaid’s foundation models, driving key decisions across pretraining objectives, model architecture, and fine-tuning approaches that power a wide range of downstream product applications. You will serve as the technical lead for the full machine learning lifecycle, overseeing everything from data curation and experimentation to production deployment, feature management,

The Language Tools team enables ~1,500 Datadog developers to build, test, and package millions of lines of Go, Python, Java, Rust, and TypeScript in our backend monorepo. Our success is measured by their productivity and satisfaction. They use the tools that we develop and support several times a day, in both development and CI environments. We use the Bazel open source build system as a foundation. The team is growing rapidly, both with Datadog and as we absorb other repositories into the monorepo. As a senior software engineer on the team, you will own projects from start to finish, both greenfield and brownfield. You will gain first-hand understanding of what Datadog developers need, and inform our roadmap. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Invent build, test and packaging tools that are simpler and more reliable to use. Push performance and cost efficiency at scale, raising cache hit rates and cutting CI times and compute spend across millions of targets. Treat CI like SREs treat prod, making sure our pipelines are green and fast. Prepare, run, and finish complex migrations. Contribute back to the Bazel ecosystem, upstreaming fixes and shaping features we depend on. Who You Are: An expert in Bazel and/or one of the languages listed above. A well-rounded engineer. You must broadly understand the various types of software projects that are built, tested, and packaged with our tools. Both careful and fearless. The changes we make impact the velocity of hundreds of engineers. They are risky but necessary. User-focused. We help Datadog engineers to use the tools that we develop, and continuously improve their usability, so they don’t need our help the next time. Ideally, you have ex

About the Team API Multimodal builds the developer-facing products and infrastructure that bring OpenAI’s image, audio, and real-time model capabilities into the world. We are responsible for high-scale APIs for image generation, speech transcription, speech generation, and low-latency voice interactions. We partner closely with Research and Inference to bring frontier model capabilities to developers and use customer feedback to improve our models. About the Role As a software engineer on API Multimodal, you will build and operate the products and distributed systems behind OpenAI’s image, audio, and real-time APIs. You will work across model integration, API design, and production infrastructure to turn new research capabilities into reliable developer experiences. This hands-on role combines backend and systems depth with product judgment: you will own projects end to end, partner with Research, Inference, and Safety, and help make multimodal AI useful at scale. Model training experience is not required. In this role, you will: Design, build, and ship developer-facing APIs and backend services that serve frontier models. Architect low-latency streaming, request, session, and model integration systems that make complex multimodal interactions reliable and intuitive at scale. Work directly with Research to bring new model capabilities into production, shape the systems around them, and incorporate feedback from real-world developers and customers. Own the availability, latency, scalability, and cost efficiency of the services you build. Own projects from technical design and implementation through launch and ongoing iteration, while raising the team’s engineering standards. Your background might look something like: 7+ years of professional experience, excluding internships, in backend, infrastructure, platform, or product engineering roles. A track record of designing, building, and operating production backend services, developer-facing APIs, or distributed syste

About the Team OpenAI’s Applications Engineering organization builds and operates the products (such as ChatGPT & Codex) that bring our cutting-edge research to millions of users and developers worldwide. The Applied Foundations team owns the core product and platform layers that make those experiences possible — from identity & access, to safety to payments & commerce across all of our apps. Our teams span product engineering, infrastructure, and safety, working together to deliver technology that is reliable, secure, and trusted at global scale. About the Role We’re hiring Backend Software Engineers to design and implement safe services and infrastructure that power our core products. What You’ll Do Architect, build, and improve scalable backend systems and APIs. Drive performance, reliability, and safety across distributed services. Implement data storage, retrieval, compute, and integration solutions. Participate in long-term architectural planning and technical design reviews. Collaborate with cross-functional teams to design solutions that protect against and mitigate adversarial attacks without compromising user experience. You Might Thrive Here If You: Have strong experience with distributed systems, APIs, and backend languages (e.g., Go, Python, Rust, C++). Have experience setting up and maintaining production backend services and data pipelines. Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed. Enjoy building resilient services that handle large scale and complexity. Are self-directed and enjoy figuring out the best way to solve a particular problem Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done. 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

About the Team We’re hiring software engineers to make the Workload team more productive. The Workload team maintains the core components of OpenAI’s training and inference frameworks and helps execute frontier experiments. About the Role We’re looking for someone who cares about the developer experience of working in and around OpenAI’s core training and inference frameworks. In this role you will: Be responsible for optimizing the development workflows of the engineers around you Work within various Workload teams to address their specific needs, but collaborate with the centralized teams that own various aspects of development experience Optimize iteration speed, both broadly, and in particular by optimizing specific teams’ CI Improve reliability, for instance, by driving testing strategy for particular components Work through the long tail of things that it takes to build libraries and systems that will delight researchers You might thrive in this role if: You are motivated by helping people. You believe a thing that separates great teams from good teams are the players willing to do whatever work it takes, without ego. You believe in the power of developer experience. Something magical happens when people can quickly and confidently iterate on a simple codebase, but this magic is fragile and must be fought for. When you see someone trip over something, no matter how small, your first instinct is asking yourself what it would take for that to not happen again. Your second instinct is clicking merge on the PR you’ve already written to make it so. You are pragmatic. You have the ability to see the world through a perfectionist’s eyes, but are not yourself a perfectionist. You know which problems to pick and when to switch to making progress on a different problem. You like going end-to-end on things. You love co-design — that feeling when you were only able to find the right solution because you both deeply understand the users that interact with a system and the

About the Team We’re hiring software engineers to make OpenAI’s networking teams more productive. These teams build and operate the high-performance networking systems that support OpenAI’s training and inference infrastructure at frontier scale. About the Role We’re looking for someone who cares deeply about the developer experience of engineers working on complex infrastructure systems — especially around build systems, test architecture, release pipelines, and reliable development workflows. This role will be embedded with OpenAI’s networking team: making it faster, safer, and easier for engineers to build, test, validate, and ship changes across multi-server, networked, and hardware-adjacent environments. In this role you will: Improve development workflows for engineers building and operating OpenAI’s networking systems Design and improve continuous deployment, release, and validation pipelines Build and maintain test harnesses for multi-server, networked, and hardware-backed environments Improve iteration speed across C++, Python, and build-system-heavy codebases Partner with engineers to identify friction in CI, testing, debugging, and deployment workflows Drive testing and reliability strategy for infrastructure components that support large-scale training and inference workloads Work closely with centralized developer experience teams while staying deeply embedded with the networking engineers closest to the systems You might thrive in this role if: You are motivated by helping other engineers move faster and with more confidence You have experience with CI/CD, release pipelines, testing infrastructure, or build systems You are comfortable moving between C++, Python, and build systems such as CMake, Bazel, or Blaze You enjoy building test harnesses, automation, and workflow improvements for complex systems You do not need to be a networking expert, but you are excited to learn enough about the domain to make the team meaningfully more effective When you see