Development Manager Jobs

About PayPay India PayPay, a fintech company providing a service enjoyed by over 75 million users since its launch in 2018 in Japan. The company is now home to a very diverse team of members from more than 50 countries. We grew to a team of several thousand employees in Japan but are far from over. We are still in the Day 1. Every day, new members join us from all over the world to create new value and deliver it to society. Why India ? To build our Payment services, we got technical cooperation from Paytm (A large payment service company in India). And based on their customer-first technologies , we created and expanded the smartphone payment service in Japan. Therefore, we have decided to establish a development base in India, because it is a major IT country with many talented engineers, as evidenced by the fact that cutting-edge mobile payments can continue to be generated. OUR VISION IS UNLIMITED We dare to believe that we do not need a clear vision to create a future beyond our imagination. PayPay will always stay true to our roots and realise a vision (future) that no one else can imagine by constantly taking risks and challenging ourselves. With this mindset, you will be presented with new and exciting opportunities on a daily basis and have the opportunity to grow and reach new dimensions that you could never have imagined. Job Description PayPay India is seeking a Corporate Legal Counsel to provide legal support and guidance for business operations, with the objective of enabling compliant, secure and efficient operations. Department: Corporate Main Responsibilities Establish strong legal foundations as the company scales. Ensure contracts, policies, and business activities are legally compliant. Reduce legal and regulatory risks through proactive review and advisory. Support incident response documentation and regulatory communication. Build structured compliance processes rather than reactive handling. Protect the

Toradex is a global company strongly focused on engineering & technology. We’re powered by a diverse & uniquely gifted workforce. We pursue the best people to propel our innovative vision of embedded computing and IoT. If you’re interested in being a driving force at an agile technology company, engineering clever computing solutions & helping other companies bring their products to life, we should talk. Description We are looking for a DevOps Engineer to strengthen our cloud operations and engineering practices, with a focus on reliable website delivery, secure AWS foundations, and fast but controlled delivery of new services. The position combines AWS operations, infrastructure as code, CI/CD, automation, and pragmatic software engineering. The person should be confident working with services for edge delivery, compute, storage, databases, DNS, security, and observability without relying on manual console changes as the default operating model. The role also supports on-premises to cloud migration, global service optimization, and practical responses to increasing AI-driven traffic. We value candidates who can use modern AI-assisted development effectively to spin up proof-of-concept projects quickly, while still applying disciplined Git, review, security, and deployment practices. About you You enjoy building stable, secure, and maintainable infrastructure that supports business-critical services. You can work independently and take ownership of cloud environments, deployments, and operational improvements. You are comfortable balancing speed, reliability, cost, and security when making technical decisions. You communicate clearly with technical and non-technical stakeholders and explain trade-offs in a practical way. You document your work well and create clear runbooks and support material for future maintenance. You are methodical when troubleshooting incidents and stay calm when systems are under pressure. You are curious about modern traffic patt

About PayPay India PayPay, a fintech company providing a service enjoyed by over 75 million users since its launch in 2018 in Japan. The company is now home to a very diverse team of members from more than 50 countries. We grew to a team of several thousand employees in Japan but are far from over. We are still in the Day 1. Every day, new members join us from all over the world to create new value and deliver it to society. Why India ? To build our Payment services, we got technical cooperation from Paytm (A large payment service company in India). And based on their customer-first technologies , we created and expanded the smartphone payment service in Japan. Therefore, we have decided to establish a development base in India, because it is a major IT country with many talented engineers, as evidenced by the fact that cutting-edge mobile payments can continue to be generated. OUR VISION IS UNLIMITED We dare to believe that we do not need a clear vision to create a future beyond our imagination. PayPay will always stay true to our roots and realise a vision (future) that no one else can imagine by constantly taking risks and challenging ourselves. With this mindset, you will be presented with new and exciting opportunities on a daily basis and have the opportunity to grow and reach new dimensions that you could never have imagined. AI-First Culture at PayPay At PayPay, we believe the future of software development is AI-augmented engineering. Every engineer is expected to actively leverage AI tools for code reviews, testing, documentation, debugging, and productivity improvements. AI is not optional — it is a mandatory part of our daily engineering workflow. Candidates must demonstrate both hands-on experience and the right mindset to integrate AI effectively into their workflow, while maintaining the engineering rigor, ownership, and problem-solving skills that only humans can provide. Job Description PayPay India is lookin

Forward was founded in 2013 by four Stanford Ph.D.s, building the industry's first network digital twin: a mathematically accurate model of the production network. It's the foundation for autonomous networking, giving engineers and AI agents the ability to know the impact of every change before it touches production. That founding instinct still defines how we work. We're accurate and evidence-driven, relentless about clarity, and we'd rather be certain than comfortable, building a groundbreaking platform that transforms how teams run and secure networks across every major cloud and vendor environment. Global leaders like Goldman Sachs, PayPal, S&P Global, IBM, and Dell trust Forward, alongside fast-growing enterprises and government agencies, realizing an average of $14.2 million in annual benefits, according to IDC. Backed by top-tier investors, including A. Capital, Andreessen Horowitz, Goldman Sachs, MSD Partners, Omega Venture Partners, Section 32, and Threshold Ventures, and headquartered in Santa Clara, we're most proud of our team: curious people who'd rather build what doesn't exist than accept how things have always been done. Forward is currently seeking a Java Backend Software Engineer to work as part of our Apps - Server team. The work will involve developing our web server, REST APIs, and product core by writing clean and solid code that interacts with our other services and components. Responsibilities include: Developing new product features that leverage the network model to help users: visualize their network, understand how it behaves, see how it has evolved, answer specific questions, and plan changes Designing the data model for new product features Proposing and implementing REST APIs to support the Forward web application and to publish to customers Constructively reviewing product designs, technical design documents, and code changes Requirements: At least 5+ years of full lifecycle software development experience Expertise in Java (versi

Who are we: Graviton is a privately funded quantitative trading firm striving for excellence in financial markets research. We trade across a multitude of asset classes and trading venues using a gamut of concepts and techniques ranging from time series analysis, filtering, classification, stochastic models, pattern recognition, to statistical inference analyzing terabytes of data to come up with ideas to identify pricing anomalies in financial markets. As part of this team you will be tasked to apply machine learning and specifically deep learning techniques to trading problems while staying connected to broader research community. The researcher will put theory into practice and can immediately impact the global trading landscape with the expanding presence of Graviton in various markets. Description Lead research in applying machine learning to a wide variety of datasets and trading problems Follow latest developments in academic research and incorporating research techniques from different fields of applications to our problems Improve tick-by-tick order book based time series feature sets using latest preprocessing techniques Work on current and develop new deep learning models to exploit large pool of in-house features and computing infrastructure Develop scalable pipeline for building predictive models across global markets Discover and implement new sources of predictive alpha, verify that they improve existing models, and integrate them into the firm's strategy development pipeline Partner with quant researchers and software developers in implementation of conducted research to production using Python / C++ Advise infrastructure support team on latest developments on hardware and software to improve computing infrastructure for ML based research Qualifications Masters or PhD in Computer Science, Mathematics, Statistics, or a related field At least two years of demonstrated experience of ML/AI research in a professional setting or at a repu

We're looking for a Head of Enterprise & Field Marketing to lead and scale our global field marketing organization, own account-based marketing for our largest and most strategic accounts, drive alliances and partner marketing in service of enterprise growth and regional strength; and oversee our strategic events strategy and programs. This is a senior leadership role responsible for the strategy, team, and execution to drive high-quality pipeline and conversion for Diligent’s AI-powered GRC platform in all regions, and design programs that turns enterprise pipeline into revenue through a full-funnel approach, including integrated regional campaigns; 1:1/1:few ABM for named global accounts; bespoke strategic events that offer cut-through experiences for prospects and customers; and leveraging co-marketing of alliances and partnerships for net-new pipeline and brand expansion. You would be joining Diligent at an exciting moment in the company’s history, as they unleash their new AI-powered GRC platform to help General Counsels, Chief Compliance Officers, Audit and Risk Leaders. This is the result of nearly three years of intense development of agentic workflows inside the Diligent platform, as well as MCP/plug-in access to Diligent offerings - providing a robust, differentiated experience for clients who need solutions that accelerate and action critical business objectives, not just static reporting. Working closely with Sales and the broader GTM organization, you will lead an established, multi-region field marketing team and be responsible for evolving it from regional execution into a more specialized, account-centric growth engine — tightly aligned with enterprise sales leadership, customer success, global events, and partner teams. You'll own the budget, the roadmap, and the relationship with sales as the primary marketing partner for our highest-value opportunities. You w

Scale’s rapidly growing International Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for custom LLMs Upskilling and advisory services to spread the impact of AI As a Full Stack Software Engineer (Forward Deployed), you’ll collaborate directly with public sector counterparts to quickly build full-stack, AI applications, to solve their most pressing challenges and achieve meaningful impact for citizens. At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you. You will: Serve as the lead technical strategist for public sector engagements, converting ambiguous mission requirements into robust architectural roadmaps and guiding onsite implementation Architect the fundamental frameworks for production-grade AI applications, setting the gold standard for how interactive UIs, backend systems, and AI models are integrated at scale to deliver reliable outcomes. Guide the evolution of cloud infrastructure, ensuring security, global scalability, and long-term system integrity across all environments. Direct the development of core platforms and shared services, ensuring they solve cross-cutting needs for diverse global client use cases. Partner with cross-functional leadership to steer the technical roadmap, mentoring senior and junior staff and ensuring all products align with a cohesive, future-proof technical architecture. Bridge the gap between the field and the core platform by turning real-world client lessons into the reusable patterns that power the entire engineering team. Ideally you’d have: Masters or Phd in Computer Science or eq

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

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborate with cross-functional teams to define, design, and deliver new features. Proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades. Present technical information to teams and stakeholders, providing

Join the team shaping the future of AI at Scale. Scale builds RL environments: sandboxed replicas of the digital spheres where real knowledge work occurs and built from the operating data of the companies that actually hold it. As the Data Acquisition Lead , you will own the commercial motion that gets us that data end to end. You will figure out which companies sit on the data for the next domain worth owning and then go and get it. This is a zero-to-one function with no playbook. You should be prepared to wear many hats, from thesis-driven dealmaker to hands-on operator to technical translator between commercial and Research teams. You will: Map the supply side. Work backwards from where labs are pushing to the specific organizations holding the underlying data. Build a thesis on which domains are worth owning and in what order. Invent the deal structures. You'll work with Scale’s legal team to define the first version of how these transactions get priced. Close. Own it from cold outreach to signature. Close the loop with the technical side. You need to hold a real conversation about what makes a dataset trainable and become an expert in what makes this underlying data valuable. Build the machine. Do the work by hand first, then turn what you learn into a repeatable pipeline. Ideally, you’d have: 5+ years across some mix of business development, corp dev, commercial strategy, or early-stage GTM. The label matters less than a track record of building a commercial motion that didn't exist before you got there A strong track record of managing important external relationships Strong business judgment and the ability to evaluate partnership value quickly Clear communication skills and comfort working with senior stakeholders Ability to operate independently while staying closely connected to cross-functional teams A practical, hands-on approach to building new functions from the ground up Comfort working in fast-moving, ambiguous environments Experience in

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Senior Staff Frontier Agents Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineering & Optimization Create sophisticate

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Scale AI is seeking a highly skilled and motivated Software Engineer, Frontier AI Infrastructure to join our dynamic Public Sector Engineering team. As a part of this team, you will own the model inference layer - enabling state of the art models, debugging the latest AI tools, managing networking, debugging latency, and tracking pricing/usage metrics for AI models. You will lead technical discussions on the frontlines with cloud vendors and customers to deliver on critical contracts and to debug platform issues. You will also work upstream with Product to understand features before they break, moving us from "infra-only debugging" to proactive integration testing. You will: Design and implement secure scalable backend systems for Public Sector customers, leveraging Scale's modern and cloud-native AI infrastructure. Own services or systems and define their long-term health goals, while also improving the health of surrounding components Re-architect the stack to run in compliant or restrictive environments. This requires designing swappable components (auth, storage, logging) to meet government/security mandates without breaking the product. You will work with Product to build integration tests that catch issues early, shifting the focus from "infra-only debugging" to preventing failures upstream. Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions. Contribute to the platform roadmap and product strategy for Scale AI's Public Sector business, playing a key role in shaping the future direction of our offerings. Must have: At least an active secret clearance and the ability & willingness to up level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a secret clearance Ideally you'd have: Full Stack Development: Proficiency in both front-end and back-end development, including experience with modern web develo

Software Engineer Argentina; Uruguay Software Engineer - Robotics & Autonomous Systems Scale's Robotics business unit is dedicated to solving the data bottleneck in Physical AI across Robotics, Autonomous Vehicles, and Computer Vision. In this role, you'll be a key contributor building production systems for robotics data collection, model training pipelines, and evaluation infrastructure. You'll have the opportunity to own critical parts of our robotics platform, work directly with cutting-edge robotics and AV customers, and shape the future of embodied AI systems. You Will: Own and architect large-scale data processing pipelines for robotics and autonomous vehicle datasets Build ML training and fine-tuning pipelines using Scale's robotics data Work across backend (Python, Node.js , C++), and frontend (React, TypeScript) stacks to build end-to-end solutions Develop tools and real-time systems for robotics data collection, teleoperation, model evaluation, data curation, and data annotation Interact directly with robotics and AV stakeholders to understand their technical needs and drive product development Design comprehensive monitoring and evaluation frameworks for robotics models and data quality Solving complex, late-stage industry challenges in concurrent and real-time robotic systems, with strict attention to timing constraints and data integrity. This often involves deep investigation, reviewing academic papers, and direct collaboration with robotics vendors Collaborate with ML engineers and researchers to bring robotics research into production Deliver features at high velocity while maintaining system reliability and performance Ideally, You Have: At least 6 years of high-proficiency software engineering experience, with a strong background in complex systems and the ability to independently research, analyze, and unblock hard technical problems. Strong programming skills in Python and TypeScript/Node.js for production systems Experience with React and m

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. For 10 years, Scale has provided the high-quality data and full-stack technologies that power the world's leading models, and has helped enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. Scale's internship is not a side project. Interns own real, shipped work on the same roadmaps as full-time engineers, with mentorship from world-class talent and a culture that values ownership, speed, and truth-seeking. Many of our interns return as full-time Scaliens. Example Projects Build reinforcement learning and post-training data pipelines that power frontier model development Develop evaluation infrastructure that measures model reliability for enterprise and public sector customers Ship agentic AI applications and the tooling that makes them observable, testable, and safe to deploy Ship tools that accelerate the growth of new qualified contributors on Scale's platform Build fraud-detection systems that remove bad actors and keep Scale's contributor base safe and trusted Use models to estimate the quality of tasks and contributors, and guarantee quality on requests at large scale Devise advanced matching algorithms that pair contributors to customers for optimal turnaround and accuracy Create optimized and efficient UI/UX tooling, in combination with ML algorithms, for 100k+ contributors completing billions of complex tasks Develop new AI infrastructure products to visualize, query, and explore Scale data Requirements A graduation date in Fall 2027 or Spring 2028 with a Bachelor's degree (or equivalent) in a relevant field (Computer Science, EECS, Computer Engineering, Statistics) Available for a Summer 2027 internship (May/June start dates) in San Franci