Python Engineer 2c Agentic Ai Jobs

About Supabase Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. About the Role We are hiring a AI Platform Engineer to build the execution layer for Supabase's internal AI systems. Supabase is building an AI-native internal operating system: a common way of working across the company where AI carries a meaningful share of the operational load rather than sitting alongside it as an assistant. We are standing up a new central team to build those systems, enable the teams, and embed AI operations throughout the organization. You are the engineer on that team. The execution layer is yours. You will build the platform that actually runs agents: an event-triggered queue, a headless model-agnostic runtime, durable state so work survives a restart, a human review gate, atomic rollback, and full logging of every prompt, tool call and decision so any run can be reconstructed. You will build the evaluation layer that makes any of it trustworthy, because an agent that cannot be measured cannot be trusted with anything beyond reading. And you will build the agents themselves, across everything from executive reporting down to a layer of agents that watch the platform and improve it. This is a governance-heavy environment by design, and that is the interesting part of the problem. Agents are risk-tiered from read-only internal data through to external-facing output, with review depth, evaluation requirements and human approval scaling by tier. Some capabilities are permanently off limits: an agent may read and report, it may carry a human-authored update into a system of record once a human consents, and it may initiate contact within a strict budget, but it may never autonomously write a commitment (an owner, a due date, a status) into a shared work system. Your job is

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As an Offensive Security Engineer on the Application Security team within Security, you'll pioneer how Coinbase uses frontier AI models to scale vulnerability discovery, red team AI systems, and automate security workflows. This role bridges traditional penetration testing with next-generation AI-augmented offensive security, directly accelerating our ability to protect products and customers. You'll own the development of AI-driven security tooling and collaborate across Vulnerability Management, Offensive Security, and Incident Response to fundamentally shift how we operate. What you'll do: Build, deploy, and maintain custom security scanners that leverage frontier models to detect vulnerabilities at scale across Coinbase's product surface. Lead red teaming efforts against internal AI systems, including jailbreak testing, prompt injection analysis, and tool abuse simulation. Develop AI-driven automation for vulnerability triage, validation, and remediation workflows to accelerate the bug bounty and vulnerability response pipelines. Partner with engineering teams to prioritize, remediate, and verify fixes for critical vulnerabilities discovered through AI-augmented and manual testing. Mentor junior security engineers on integrating AI into offensive security workflows to scale team capabilities. Required Skills and Experience: 3+ years of experience in application s

About Flexport: At Flexport, we believe global trade can move the human race forward. That’s why it’s our mission to make global commerce so easy there will be more of it. We’re shaping the future of a $10T industry with solutions powered by innovative technology and exceptional people. Today, companies of all sizes—from emerging brands to Fortune 500s—use Flexport technology to move more than $19B of merchandise across 112 countries a year. The recent global supply chain crisis has put Flexport center stage as we continue to play a pivotal role in how goods move around the world. We are proud to have the support of the best investors in the game who believe in our mission, solutions and people. Ready to tackle global challenges that impact business, society, and the environment? Come join us. What you'll do There is no MSSP and no tier-1 queue here. Detection & Response engineers own their detections end to end: you write them, you tune them, and your team is paged when they fire. The security team is spread across the globe with a follow-the-sun pager rotation so nobody is paged at 3am local. The adversaries are real. The business is growing fast and the threat surface is growing with it. Defining the necessary telemetry is part of the job. Detection engineering Build and tune detections across endpoint, identity, SaaS, and cloud , treating them as software: version-controlled, peer-reviewed, and shipped through the same CI/CD practices the rest of engineering uses. Track detection quality as measured quantities : coverage against MITRE ATT&CK, precision, time-to-detect. We don’t build-and-forget here. Response & automation Own incident response: triage, contain, remediate, and write the retrospective that turns the incident into a systemic fix. Build automation that removes toil from investigations, and partner closely with the US-based team so context carries across time zones instead of getting lost at handoff. Telemetry & partnershi

Location Details: Gurgaon, India At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​ This is a hybrid position. You’ll divide your time between working remotely from your home and an office, so you should live within commuting distance. Hybrid teams may work in-office as much as a few times a week or as little as once a month or quarter, as decided by leadership. The hiring manager can share more about what hybrid work might look like for this team. Join Our Team GoDaddy is empowering everyday entrepreneurs around the world by providing all of the help and tools to succeed online. GoDaddy is the place people come to name their idea, build a professional website, attract customers, sell their products and services, and manage their work. Our mission is to give our customers the tools, insights and the people to transform their ideas and personal initiative into success. Our Identity team is looking for a Software Engineer to join us in building and maintaining GoDaddy's customer identity platform. As a software engineer on our team, you will work in an Agile scrum environment, contributing to the development and maintenance of mission-critical services that serve as the authoritative source of truth for all GoDaddy customer profiles, identity verification, and consent management. You'll be working with modern cloud-native architectures, handling billions of requests, and ensuring the highest standards of security and compliance for customer data. What you'll get to do... Design, develop, and maintain backend services and RESTful APIs using Java and Spring Boot for GoDaddy's customer profile and identity platform Build scalable, event-driven microservices on AWS (DynamoDB, Kinesis, Lambda, ECS/Fargate, S3, OpenSearch), including real-time integrations with internal systems and third-party vendor

About Flexport: At Flexport, we believe global trade can move the human race forward. That’s why it’s our mission to make global commerce so easy there will be more of it. We’re shaping the future of a $10T industry with solutions powered by innovative technology and exceptional people. Today, companies of all sizes—from emerging brands to Fortune 500s—use Flexport technology to move more than $19B of merchandise across 112 countries a year. The recent global supply chain crisis has put Flexport center stage as we continue to play a pivotal role in how goods move around the world. We are proud to have the support of the best investors in the game who believe in our mission, solutions and people. Ready to tackle global challenges that impact business, society, and the environment? Come join us. What you'll do There is no MSSP and no tier-1 queue here. Detection & Response engineers own their detections end to end: you write them, you tune them, and your team is paged when they fire. The security team is spread across the globe with a follow-the-sun pager rotation so nobody is paged at 3am local. The adversaries are real. The business is growing fast and the threat surface is growing with it. Defining the necessary telemetry is part of the job. Detection engineering Build and tune detections across endpoint, identity, SaaS, and cloud , treating them as software: version-controlled, peer-reviewed, and shipped through the same CI/CD practices the rest of engineering uses. Track detection quality as measured quantities : coverage against MITRE ATT&CK, precision, time-to-detect. We don’t build-and-forget here. Response & automation Own incident response: triage, contain, remediate, and write the retrospective that turns the incident into a systemic fix. Build automation that removes toil from investigations, and partner closely with the US-based team so context carries across time zones instead of getting lost at handoff. Telemetry & partnershi

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . We're looking for a Staff Software Engineer to lead the technical direction of the backend systems powering Pinterest's AI-driven product experiences — Pinterest Assistant, visual editing and content creation tools and future LLM-based products. You'll design and ship backend systems while architecting the broader platform strategy that enables these experiences to scale across surfaces and teams. This is a hands-on leadership role where you'll move between deep technical execution, system-level architecture and cross-team technical leadership. What you'll do: Define the backend and platform architecture for AI-driven product experiences — visual-chat, AI image generation and editing, and agentic or LLM-based products — partnering with Engineering, Product, ML and UX leaders to shape the technical vision and roadmap. Architect end-to-end systems

Datadog Notebooks provide customers with a collaborative surface for ad-hoc data analysis, technical documentation, incident postmortems and runbooks. The power and flexibility of Notebooks also makes it the perfect place to integrate AI tools that can augment user workflows. Our vision is that in Notebooks users can collaborate with each other and with AI agents seamlessly. We are looking for a product-oriented Senior Software Engineer to help build the AI-assisted workflows that are becoming central to how customers use Notebooks. In this role you will work closely with product and design, and own platforms for analysis workflows and context discovery. There is a real opportunity for impact here: turning Notebooks into the tool that helps customers go from uncertainty to answer, and making that knowledge retrievable and reusable across Datadog products. 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 Lead the design and delivery of AI-powered product experiences for Notebooks and adjacent surfaces Develop systems that combine deterministic product capabilities with LLM-powered experiences to deliver trustworthy and explainable customer outcomes Partner closely with Product: Work hand-in-hand with the Product Manager to translate customer problems, adoption signals, and roadmap goals into concrete technical decisions and iterations Build experiences that enable Datadog capabilities to operate within third-party AI platforms, agents, and conversational environments Provide technical leadership and mentorship while helping establish AI engineering best practices Own production systems: Build and operate reliable backend services that run in the critical path of customer deployments, and be on-call for those services Who You Are You have experience with Go,

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Senior Solution Engineer dedicated to one of Snowflake's most strategically important healthcare customers. This is a named-account role: your entire focus will be a single global healthcare organisation, whether a payer, provider, life sciences company, or health technology platform. You will own the full technical relationship, drive use case expansion across the organisation's clinical, operational, and research functions, and act as the go-to trusted advisor to CTO, CDO, and engineering leadership within the account. This is a senior-level, high visibility role with global scope and direct exposure to Snowflake's leadership. AS A SENIOR SOLUTION ENGINEER AT SNOWFLAKE, YOU WILL : Own the end-to-end technical relationship for a single strategic Global Account in healthcare, from discovery and technical qualification through proof of concept, technical close, and ongoing expansion Build and deliver compelling demonstrations, solution architectures, and executive presentations that connect Snowflake's platform capabilities to the account's clinical, operational, and research data priorities Design and lead proof of concept engagements covering healthcare use cases including clinical data interoperability, population health analytics, claims and payer data pr

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role: Anyscale is looking for a Site Reliability Engineer to join the Infrastructure team. Anyscale aims to provide the next generation of tools and infrastructure to make developing and running distributed AI applications in the cloud as easy as on your laptop. As part of the Infra team, we build the scalable, secure, and robust backbone that enables this vision. Our team is responsible for both the control plane, which orchestrates cluster management, scheduling, and user access, and the data plane, which ensures high-performance execution of distributed workloads. We are seeking a talented engineers with a strong background in control plane and data plane development, along with expertise in Kubernetes, container orchestration, and cloud-native infrastructure. You will play a crucial role in designing, implementing, and optimizing the critical infrastructure that powers Anyscale’s cloud platform. You will have the opportunity to work on open-source Ray, contribute to our infinite laptop proprietary product, and develop seamless integration between the two, while also delivering high-impact features for our customers. A snapshot of projects you may work on Design, build, and scale services that orches

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. Join NVIDIA's GPU Performance Infrastructure team and be part of a brand-new journey in validating and shipping next-generation GPU architectures. At NVIDIA, we empower our engineers to innovate and drive powerful performance through innovative infrastructure and workflows. This role is uniquely positioned to influence the entire lifecycle of GPU performance verification, from early-stage modelling to post-silicon validation. With our bold standards and extraordinary team, you'll have the chance to define a significant impact on the future of computing! What you'll be doing: Build and develop end-to-end performance verification infrastructure. Build scalable data pipelines to surface performance metrics from simulation, emulation, and silicon environments. Coordinate with GPU architects to craft infrastructure for performance verification of upcoming architectures. Work closely with HW teams to automate and accelerate verification workflows, enabling faster GPU build iteration. Empower GPU architects by providing insights to understand current performance and model industry-leading performance for future builds. Improve the daily workflows of the wo

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Senior Backend Engineer on the Plan: Spec-Driven Development team, you'll help build GitLab's intent-to-code loop: agentic workflows that turn a stated intent into a refined work item, an implementation plan, and verified, mergeable code. You'll own early-stage backend work across the flows, application programming interfaces, data models, and evaluation systems behind this experience, using Ruby on Rails, Python, PostgreSQL, GitLab Duo Agent Platform, large language model application programming interfaces, and an artificial intelligence gateway. You'll join a small, distributed team working on one

About Us: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. Job Summary: We are seeking a highly motivated and skilled Akamai CDN & WAF Engineer with 2-5 years of hands-on experience in configuring, deploying, and managing Akamai's Content Delivery Network (CDN) and Web Application Firewall (WAF) solutions. The ideal candidate will possess a strong understanding of web performance optimization, security best practices, and have a proven track record of implementing and troubleshooting Akamai services in a production environment. This role requires a proactive individual with excellent problem-solving skills and the ability to collaborate effectively with cross-functional teams. Responsibilities: Configuration and Deployment: Configure and deploy Akamai CDN services (e.g., Domain onboarding, delivery rules, caching policies, origin configurations) and WAF rulesets (e.g., security policies, custom rules, DOS and client reputation) based on application requirements and security guidelines. Production Support: Provide day-to-day operational support for Akamai CDN and WAF infrastructure, including monitoring performance, identifying and resolving issues, and implementing necessary changes. Performance Optimization: Analyze website performance metrics and implement Akamai CDN features and configurations to optimize website speed, reduce latency, and improve user experience. Security Implementation: Implement and manage Akamai WAF policies to protect web applications from various security threats, including OWASP Top 10 vulnerabilities, bot attacks, and DDoS attacks. Rule Management: Create, review, and maintain custom WAF rules and exceptions based on application-specific ne