Development Engineer 3 Jobs

MongoDB’s mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. We enable organizations of all sizes to easily build, scale, and run modern applications by helping them modernize legacy workloads, embrace innovation, and unleash AI. Our industry-leading developer data platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available in more than 115 regions across AWS, Google Cloud, and Microsoft Azure. Atlas allows customers to build and run applications anywhere—on premises, or across cloud providers. With offices worldwide and over 175,000 new developers signing up to use MongoDB every month, it’s no wonder that leading organizations, like Samsung and Toyota, trust MongoDB to build next-generation, AI-powered applications. Atlas Search is a multi-cloud service that allows users to execute complex full text and vector search queries using the MongoDB Query Language . Our users are free to focus on relevance and data retrieval instead of the machinery needed to search data at scale. Our team builds and maintains the instances and supporting infrastructure powering Atlas Search. This platform deploys and monitors search deployments, providing a highly scalable yet observable system for customers and engineers. The Atlas Search product is quickly gaining traction with customers and we are shipping core infrastructure components that enable this growth. This role is based in San Francisco, CA with an in-office or hybrid work model. Successful candidates will have the following qualities: 2+ years of hands-on experience designing, building, testing, and maintaining industrial-strength backend software and automation in complex codebases Experience developing distributed systems and multithreaded applications Familiarity with public cloud platforms, distributed infrastructure, and metric-based development Experience with at least one modern statically typed program

MongoDB is seeking a Software Engineer 3 to join the Documentation Platform Engineering Team. The Documentation Platform delivers 60M page views a year and is critical to our users’ understanding of MongoDB products.It is also increasingly the context engine that helps AI tools understand, surface, and recommend MongoDB correctly. You will contribute to the evolution of our documentation platform by building and improving internal infrastructure, integrations, and applications that support our documentation and learning experience. This role can be based out of one of our offices in Canada or the USA, or remotely in Canada or the USA. Our ideal candidate Hands-on experience and understanding of Git, TypeScript, React, Next.js, CI/CD, MDX and other markup languages Experience with MongoDB (or a strong track record of working with other databases) Has worked on complex, in-production web applications Deep understanding of TypeScript or JavaScript, preferably TypeScript Can write, discuss, and review code in a collaborative way Understands how to make resilient, scalable, and maintainable software Has 2+ years of professional experience building and maintaining production software systems At MongoDB, you will Contribute to the development and enhancement of the MongoDB Documentation Platform Explore ways to improve documentation accessibility, discoverability, and user engagement Develop features that enhance the user experience for documentation consumers and contributors Contribute to and occasionally lead small-to-medium scoped features and platform improvements, collaborating with partner teams as needed Analyze user

MongoDB is growing its team in Sydney, focusing on building intelligent tools that help customers understand and modernise their application codebases. The Application Modernisation Platform (AMP) guides customers through the entire journey of modernising their applications — from legacy relational platforms to modern, scalable systems built on MongoDB. The App Analysis & Modelling team owns the critical first stage of this journey: building the context that powers everything downstream. The team builds code analysis tools that construct code dependency graphs and generate deep insights for codebases, giving customers a clear understanding of their existing applications before transformation begins. The team also designs schema recommendation engines that analyse signals such as existing relational schemas and query patterns to inform data modelling decisions. Our work sits at the intersection of analysis, data modelling, and AI — helping developers make confident, data-driven decisions as they transition to MongoDB. We are looking for a Software Engineer who is passionate about building scalable backend systems and applications. As we expand our use of AI to power smarter analysis and recommendations, the ideal candidate will bring strong backend engineering fundamentals with the ability to contribute across the full stack. You will collaborate closely with product management and other engineering teams to design and deliver cutting-edge features that guide customers through complex modernisation journeys. We are looking to speak to candidates who are based in Sydney for our hybrid working model. The Ideal Candidate Will Have 3+ years of commercial software development experience with strong proficiency in Python and/or Java Experience designing and building scalable, high-performance APIs and backend services Solid understanding of relational data modelling and SQL (Oracle, PostgreSQL, MySQL, or similar), including schema design and query optimisation Good und

The Agent Research and Tooling team, part of MongoDB's AI Builder Experience organization, owns the platform layer around agents: how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior. We are hiring a software engineer to build and maintain the tooling, evaluation systems, and quality gates behind MongoDB's agent skills. This is a software engineering role at the intersection of developer tooling, applied AI, and software quality. You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows. This role is open to remote work in the US or can be based out of any of our US offices. What you'll do Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI Integrate tooling into GitHub Actions and other CI workflows, including secrets, annotations, exit codes, and artifacts Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code Investigate real failures such as nondeterministic results, false positives, and unsafe generated guidance, and turn them into reusable improvements Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams Examples of the problems you'll solve How can tests verify an agent tool's

The Agent Research and Tooling team, part of MongoDB's AI Builder Experience organization, owns the platform layer around agents: how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior. We are hiring a software engineer to build and maintain the tooling, evaluation systems, and quality gates behind MongoDB's agent skills. This is a software engineering role at the intersection of developer tooling, applied AI, and software quality. You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows. This role is open to remote work in Canada or can be based out of any of our Canada offices. What you'll do Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI Integrate tooling into GitHub Actions and other CI workflows, including secrets, annotations, exit codes, and artifacts Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code Investigate real failures such as nondeterministic results, false positives, and unsafe generated guidance, and turn them into reusable improvements Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams Examples of the problems you'll solve How can tests verify an agent to

Job Details: Job Description: Join Intel as a Module Development Engineer, where you will play a critical role in driving technology development and enabling advanced manufacturing solutions. In this position, you will lead the design and optimization of complex manufacturing processes, including material selection and equipment development, to enable innovative product designs and high-volume production. Your work will directly impact Intel's ability to maintain its leadership in cutting-edge semiconductor technologies. Business group As part of Intel Foundry, you will join a dynamic team focused on advancing semiconductor manufacturing technologies and capabilities. The group's mission includes enabling high-volume production through innovative process integration, equipment solutions, and technology advancements. Collaborating across Intel's global network, you will contribute to driving Intel's success in delivering transformative technologies to its customers. Key Responsibilities Lead the development of manufacturing processes that include MHS equipment development, parameter optimization, and equipment metrology. Perform pathfinding activities to enable emerging device architectures and support process and hardware development. Develop roadmaps for future technologies that align with Intel's leadership in semiconductor innovation. Collaborate with equipment and materials suppliers to implement solutions that meet manufacturing and technology needs. Recommend and execute modifications to equipment and processes to improve efficiency and optimize production output. Stay informed about industry trends in materials and manufacturing processes, identifying opportunities for innovation. Behavioral Traits Strong p

This position will be part of a growing team working towards building world class large scale Big Data architectures. This individual should have a sound understanding of programming principles, experience in programming in Java, Python or similar languages and can expect to spend a majority of their time coding. Location - Bengaluru Work Experience : 3 - 5 Years Responsibilities: Good development practices Hands on coder with good experience in programming languages like Java, Python, C++ or Scala. Good understanding of programming principles and development practices like checkin policy, unit testing, code deployment Self starter to be able to grasp new concepts and technology and translate them into large scale engineering developments Excellent experience in Application development and support, integration development and data management. Align Sigmoid with key Client initiatives Interface daily with customers across leading Fortune 500 companies to understand strategic requirements Stay up-to-date on the latest technology to ensure the greatest ROI for customer & Sigmoid Hands on coder with good understanding on enterprise level code Design and implement APIs, abstractions and integration patterns to solve challenging distributed computing problems Experience in defining technical requirements, data extraction, data transformation, automating jobs, productionizing jobs, and exploring new big data technologies within a Parallel Processing environment Culture Must be a strategic thinker with the ability to think unconventional / out:of:box. Analytical and data driven orientation. Raw intellect, talent and energy are critical. Entrepreneurial and Agile : understands the demands of a private, high growth company. Ability to be both a leader and hands on "doer". Qualifications: - Years of track record of relevant work experience and a computer Science or related technical discipline is required Experience with functional and object-oriented pro

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

The Opportunity Typography is central to how ideas are communicated. If you're passionate about beautifully created design, have deep curiosity about what AI can do, and take personal responsibility for creating products that people love; then this may be the role for you. Adobe Fonts supports millions of creatives in choosing and using typefaces across fonts.adobe.com, Express, Photoshop, Illustrator, Acrobat, and more Creative Cloud platforms. Our Internal Services team provides the platform engineering and deployment backbone for all of these. We manage CI/CD, deployment approaches, the services and data layers our engineers depend on, our observability and security stance, and increasingly the agentic tools that transform how our entire organization delivers software. We're seeking a Senior Software Development Engineer to lead this exciting journey in our San Francisco location. What you'll do Own and evolve our deployment platform. Lead strategy for CI/CD, PR environments, and release safety across a mixed fleet that includes containerized services, serverless services, and static front ends. Build the foundation for AI-accelerated development. Help build our agent factory and grow our internal agentic toolkit and skill library. Ship inference applications at scale. Take greenfield services from spec to production and standardize our ML/inference footprint. Modernize our services for the AI era. Identify where an existing service is held back by its current build and lead the fix. Rethink our security posture for agentic threats. Lead how we secure autonomous agents and their tool use. Expose Adobe Fonts to the agentic ecosystem. Extend our Model Context Protocol (MCP) surface and conversational, intent-based font discovery. Work higher up the stack, too. Contribute directly to search, browse, discovery, and the customer-facing experie

We are seeking a qualified Software Tools Development Engineer to join our GPU SWQA team. The successful candidate will have strong experience applying AI technologies to automate test cases and a deep understanding of Windows operating systems. Extensive knowledge of GPU, CPU, SoC, x86, and ARM architectures is required, along with expertise in PC I/O architecture and common bus interfaces such as PCIe, USB, and SATA. Familiarity with specifications for general PC architecture components is a plus. What you’ll be doing: Design and implement automated tests incorporating AI technologies for NVIDIA's device driver software and SDKs on windows platforms. Build tools/utility/framework in Python, C# or equivalent which would help automate and optimize the testing workflows in GPU domain. Develop and implement automated and manual tests, analyze results, identify and report defects. Rigorously drive test automation initiative. Build innovative ways to automate and expand our software testing. Expose defects and constraints; Isolate and debug the issue(s) and find the root cause; Contribute to the solution and drive to closure. Measure code coverage for the software under test, analyze and drive code coverage enhancements. Develop applications and tools that accelerate development and test workflows and write fast, effective, maintainable, reliable and well documented code. Generate and test compatibility across a range of products and interfaces and validate different key software applications across a test matrix designed to test both breadth and depth. Provide peer code reviews including feedback on performance, scalability and correctness. Report test coverage and Go/No-Go status for deliverables, escalate critical issues, and drive them to closure. Participate in root cause analysis and corrective actions to continuously im

We are Datadog's in-house product experts. The Datadog Federal Support Engineering team is dedicated to serving as highly trusted technical advisors for our Public Sector customers, who operate within some of the most highly regulated and security-constrained environments. These customers include various government agencies and organizations with critical, sensitive missions. As a Federal Support Engineer 3, this role places you at the forefront of supporting these customers' mission-critical workloads. These complex workloads are often deployed across sophisticated hybrid and multi-cloud architectures, requiring deep expertise in cloud technologies, monitoring, and security best practices. Your primary responsibility is to ensure the complete success of these customers across their entire lifecycle with Datadog. Whether you’re looking to learn from the best or be the best, the Federal Support team is dedicated to furthering personal development and team success. 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: Engage with public sector customers via multiple channels (ticketing system, live chat, calls, and screensharing tools) to identify and resolve technical support requests. Troubleshoot, investigate, and resolve complex technical issues in highly constrained environments across Datadog's 1000+ integrations, often with limited logs or sanitized data. Handle urgent escalation cases that may result in customer-facing troubleshooting calls, and internal or external incident management Become a subject matter expert in many Datadog product areas Partner with Product, Engineering, and Account teams to to validate bugs and advocate for customer-impacting improvements Provide mentorship to junior members of the team and serve

Engineer 3, Business Systems (CPQ) We are looking to speak to candidates who are based in Gurugram for our hybrid working model. About Team The CRM Technologies Team plays a critical role in optimizing our sales processes, streamlining customer interactions, and maximizing the efficiency of our sales efforts. By leveraging Salesforce and Quote-to-Cash technologies, the team ensures that business users have the tools, automation, and operational support needed to effectively manage quoting, pricing, approvals, and downstream business processes. With deep expertise in Salesforce development, CPQ, integrations, and platform operations, the team continuously enhances the CRM ecosystem to meet evolving business needs. The team partners closely with stakeholders across Sales Operations, Revenue Operations, Finance, Deal Desk, and Engineering to deliver scalable, secure, and reliable Quote-to-Cash solutions. Role Overview We are looking for a CPQ Engineer III to design, build, and support core capabilities in our Configure–Price–Quote (CPQ) stack that power how our GTM teams sell and price MongoDB offerings. As a senior individual contributor, you will own end-to-end delivery of features across configuration, pricing, discounting, approvals, and quote generation, working closely with Product, Deal Strategy, RevOps, and Sales. You will translate business requirements into high-quality technical solutions on Salesforce CPQ and related platforms, spanning configuration, custom development (Apex/LWC/Flows), and integrations with downstream systems. This role is hands-on and delivery-focused: you will be responsible for implementing well-structured, testable solutions, improving performance and reliability of existing CPQ flows, and contributing to shared patterns, frameworks, and best practices within the CPQ & RevOps engineering team. What you’ll do Design, build, and support Salesforce solutions across product modeling, pricing, quoting, approvals, amendments, and renewa

The CRM Technologies team is responsible for building, scaling, and operating Salesforce-based solutions that power MongoDB’s customer lifecycle from lead management and sales execution to renewals, reporting, and downstream operational workflows. The team partners closely with Sales Operations, Marketing, Revenue Operations, Finance, Customer Success, and Engineering to deliver secure, scalable, and reliable Salesforce solutions. With strong expertise in Salesforce development, automation, integrations, and platform operations, the team continuously evolves the CRM ecosystem to meet changing business needs. Role Overview We are looking for a Salesforce Engineer III to design, build, and support core Salesforce capabilities that enable MongoDB’s global go-to-market and operational teams. This is a senior individual contributor role with clear ownership from requirements through production delivery. You will translate business requirements into high-quality technical solutions using a combination of declarative configuration and custom development. This role is hands-on and delivery-focused, requiring strong technical judgment, attention to platform best practices, and the ability to work effectively across multiple business domains. As an Engineer III, you will also influence engineering standards, improve system performance and reliability, and contribute to shared frameworks and best practices within the Business Systems engineering organization. What You’ll Do Design, build, and support Salesforce solutions across sales, marketing, revenue, customer, and operational workflows Implement and enhance Salesforce functionality using standard configuration, Flows, Apex, Lightning Web Components, and platform automation Partner with business stakeholders to understand requirements, identify gaps, and deliver scalable, maintainable solutions Develop and maintain integrations between Salesforce and external systems such as Marketo, ERP, billing, marketing, support, or ana

Job Details: Job Description: As a Packaging Module Development Engineer, you will play a pivotal role in the development and optimization of Intel's assembly media and collaterals. Your daily work will involve designing innovative solutions to improve media and collateral reliability, manufacturability, and cost efficiency. Your contributions will directly support Intel's cutting-edge assembly packaging technology roadmap, driving advancements in semiconductor manufacturing processes. Business Group You will be part of Intel Corporation's Media Development organization, a team dedicated to advancing packaging technologies and manufacturing processes. This group operates at the forefront of innovation, enabling high-performance products and driving Intel's leadership in the semiconductor industry. By joining this collaborative environment, you will contribute to Intel's broader goals of delivering transformative technology solutions. Key Responsibilities Develop and optimize media and collaterals to meet quality, reliability, cost, yield, and productivity targets. Design and implement new media and collateral solutions, leveraging statistical methods like Design of Experiments (DOE) and Statistical Process Control (SPC). Conduct evaluations of media and collaterals under simulated field conditions, including tests for heat, humidity, temperature cycling, and dynamic forces. Lead initiatives to identify and mitigate media and collateral quality and reliability risks, utilizing innovative tools and methods. Provide technical consultation on media and collateral challenges and deliver solutions that align with operational and technology milestones. Document technical improvements and innovations through research papers and presentations. <p styl