Engineering Architect Jobs

Overview: We are looking for a Senior Data Engineer with deep expertise in Lakehouse architecture, real-time data streaming, cloud data infrastructure, and microservices development on Azure Kubernetes Service (AKS). You will play a central role in designing and delivering next-generation data pipelines, BI solutions, AI/ML platforms, streaming APIs, and scalable microservices that power Guidepoint's research and analytics products. This is a high-impact, hands-on engineering role. You will work closely with data architects, data scientists, analysts, frontend engineers, QA, and DevOps teams to translate complex business requirements into scalable, reliable, and observable data systems. This is a Hybrid role from our Pune office. What You'll Do: Data Engineering & Lakehouse Design, build, and maintain ETL pipelines, data ingestion workflows, and table schemas on Azure Databricks to support BI, analytics, and AI/ML use cases Architect and optimize the Lakehouse using Delta Lake on Databricks, ensuring reliability, performance, and cost efficiency Build and support data pipelines from business applications such as Salesforce, NetSuite, and other enterprise systems Develop and maintain Knowledge Graph models, entity relationship structures, and NLP-based insight pipelines Maintain data governance, data privacy standards, and compliance best practices throughout the data lifecycle Perform root cause analysis on data and processes to identify opportunities for improvement Collaborate with data architects, scientists, and business consumers to populate and optimize the data warehouse for reporting and analytics Microservices & AKS Development Develop and support scalable web APIs and microservices using Python and Azure Platform Services Build new applications, services, and platforms; optimize existing solutions and refactor legacy components using modern, scalable architec

We are looking for a Full Stack Developer to join our growing engineering team. In this role, you will design, build, and operate scalable software platforms that support analytics and AI solutions — owning the full journey from intuitive user interfaces to robust cloud-native backends. What This Involves: Front-End Development Develop and maintain user interfaces for web applications using React and Next.js. Translate wireframes and design mockups into functional, accessible UI components. Identify and resolve front-end performance bottlenecks to ensure smooth user experiences. Write and maintain unit and integration tests for front-end components (e.g. Jest, React Testing Library). Back-End Development Develop and maintain high-quality back-end services and APIs using Python. Deploy, operate, and monitor applications in cloud environments (AWS, Azure, or GCP). Manage containerized applications using Docker and Kubernetes. Contribute to the design and evolution of scalable, cloud-native software architectures. Contribute to and maintain CI/CD pipelines for web and back-end applications. Collaboration and Quality Work closely with data scientists, engineers and project managers to deliver integrated end-to-end solutions. Support the development and deployment of AI and analytics solutions. Write clean, well-documented, and maintainable code across the full stack. Participate in technical discussions, code reviews, and continuous improvement initiatives. Adhere to internal and client-mandated data protection and compliance policies, ensuring all handling, storage, and sharing of data meets required security and privacy standards. Requirements: Bachelor’s degree in Computer Science or related fields. 5+ years of software development experience, with meaningful time on both front-end and back-end systems. Experience designing systems in cloud-native or distributed environments is a plus. Excellent communication and collaboration skills — comfortable working acros

About the Team The GTM Enablement team helps OpenAI’s customer-facing organizations turn rapidly evolving AI capabilities into consistent, high-quality customer outcomes. We build the onboarding, learning experiences, playbooks, and knowledge systems that help teams develop technical depth, stay current, and confidently guide customers through successful AI adoption. About the Role We’re hiring a Field Enablement Lead, Technical Success to design and scale enablement for our rapidly growing technical customer-facing teams. You will own programs spanning onboarding, continuous skill development, technical pitches and demos, and subject-matter-expert knowledge sharing. Working closely with Technical Success leaders, Product Enablement, and technical SMEs, you will turn complex product knowledge and field experience into practical systems that improve readiness, consistency, and the quality of customer interactions and deployments. In this role, you will: Design, implement, and scale comprehensive enablement programs aligned to Technical Success onboarding, role-based skill development, and ongoing readiness needs. Redefine and operate the Subject Matter Expert (SME) program, creating clear pathways for technical experts to share knowledge and raise technical depth and consistency across GTM. Own and proactively maintain a versioned repository of technical pitches, demos, playbooks, and launch-ready assets. Partner with Technical Success leadership, Product Enablement, and product SMEs to identify skill gaps and deliver targeted learning interventions. Capture, vet, organize, and make field- and SME-generated technical content easy to discover, trust, and reuse. You might thrive in this role if you have: 5+ years of experience in technical enablement, solutions engineering, solutions architecture, technical success, or a related role. A proven track record of designing and scaling technical enablement programs in high-growth SaaS or technology environments. Exceptional

Become a part of our caring community The Senior Full Stack Engineer Performs software engineering activities in all layers of the stack, from setting up the database to programming in the back-end and the appearance at the front-end. The Senior Full Stack Engineer work assignments involve moderately complex to complex issues where the analysis of situations or data requires an in-depth evaluation of variable factors. As Centerwell builds its AI engineering function from the ground up, we need a platform foundation strong enough to support everything that comes next. As Lead Full-Stack Engineer focused on platform and API engineering, you will design and build the service layer that connects AI capabilities, data systems, and product frontends—setting the standards for how services are built, secured, and operated across the team. You will work with meaningful architectural scope, making decisions that span API design, security patterns, and deployment practices. The platform you build will serve care teams and patients across hundreds of Centerwell clinics. If you want to build platforms that others build on—and do it in service of better primary care—this is the role for you. Key Responsibilities Platform and API Architecture: ** Design and lead development of core backend services, REST and GraphQL APIs, and service-to-service integrations that connect all layers of Centerwell's AI product stack. Security and Compliance by Design: ** Establish patterns for authentication, authorization, rate limiting, PHI access control, and audit logging. Ensure HIPAA compliance is embedded in platform design from day one—not bolted on after the fact. AI and LLM Integration Patterns: ** Define and implement reusable patterns for integrating AI capabilities into product

NVIDIA is a leading artificial intelligence computing company, and we are paving the way with innovations in self-driving cars, machine learning, supercomputing, gaming, and visualization. We give automakers, tier-1 suppliers, automotive research institutions, and start-ups the power and flexibility to develop and deploy breakthrough artificial intelligence systems for self-driving vehicles. Our unified computing architecture enables training deep neural networks in the data center, and then seamlessly runs them on NVIDIA DRIVE Platforms inside the vehicle. The Hypervisor and RTOS Team within NVIDIA DRIVE Software plays a critical role in NVIDIA's expansion into the world of artificial intelligence and autonomous vehicles. Our job is to facilitate the sharing and separation of system resources while achieving real-time, safety, and security requirements. We develop Hypervisor and RTOS with a strong focus on automotive quality, safety and security needed for the real-time, highly available system level components of world-class Autonomous Vehicles. We are making extensive use of formal methods to automate our workflow and increase the quality of our SW. We are hiring now for the position of Senior System Software Engineer for Hypervisor and RTOS What you’ll be doing: Design and develop new features for RTOS and hypervisor software stack. Bring up and optimize RTOS and hypervisor stacks on new NVIDIA Tegra SoCs. Develop high-integrity software using best-in-class engineering, safety, and security practices. Debug complex system-level issues across hardware, firmware, RTOS, and virtualization layers. Lead team-wide technical initiatives by building alignment, coordinating execution, and driving them to completion. What we need to see: BS, MS in CS/CE/EE or a related engineering field or equivalent experience </

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

Location Details: India, Remote 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 remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. Join our Team Do you want to be an Information Security Lead at GoDaddy? GoDaddy’s Security organization is looking for a Cloud Security Engineer. We work out large-scale and cross-company security challenges while ensuring that partnership with the development and operational communities remains front of mind. At GoDaddy, Security Engineers apply their strong hands-on technical skills to craft scalable solutions for multiple problems. You must communicate with GoDaddy Engineering teams, perform security assessments, prioritize security risks, and design. We, as a team, implement high-quality security engineering solutions! What you'll get to do... The Senior Cloud Network Security Engineer will play a crucial role in designing, building, and securing large-scale, distributed cloud environments that support GoDaddy Services. This role operates at the intersection of cloud infrastructure, security architecture, and engineering execution. The successful candidate will collaborate closely with service teams, security leaders, and compliance partners to embed security-by-design principles into cloud services and internal platforms. This position requires advanced technical expertise in cloud-native security controls. It also needs a strong understanding of threat models in hyperscale environments. Additionally, it involves influencing architecture decisions across multiple teams. The role demands hands-on engineering, good judgment in ambiguous situations, and proficiency at translating security requirements into scalable, automated solutions. Bui

Data Engineer Description - Key Roles Designs and establishes secure and performant data architectures, enhancements, updates, and programming changes for portions and subsystems of data pipelines, repositories or models for structured/unstructured data. Analyzes design and determines coding, programming, and integration activities required based on general objectives and knowledge of overall architecture of product or solution. Writes and executes complete testing plans, protocols, and documentation for assigned portion of data system or component; identifies and debugs, and creates solutions for issues with code and integration into data system architecture. Collaborates within a project team of other data engineers to develop reliable, cost effective and high-quality solutions for assigned data system, model, or component. Analyzes data inaccuracies, identifies opportunities and supports the development of automated solutions to enhance overall quality of the enterprise data. Identifies problematic areas and conducts research to determine the best course of action to correct the data; identifies, analyzes and interprets trends and patterns in complex datasets. Works cross-functionally with different departments to assess, define, and develop report deliverables. Represents the software data engineering team for all phases of larger and more-complex development projects. Provides guidance and mentoring to less experienced staff members. Education & Experience Recommended Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, Statistics/ Mathematics, or any other related di

Job Title Senior Software Engineer - Image Reconstruction (C++/CUDA) Job Description Build the GPU-native engine that turns raw CT physics into life-saving images inside Philips scanners worldwide , wringing maximum performance from constrained hardware at the frontier of C&#43;&#43;, CUDA, and AI alongside world-class physicists. Your role: Help r e-architect an entire CT image-reconstruction pipeline, from raw detector physics to the final clinical image, as a fully GPU-native, massively scalable platform in C&#43;&#43; and CUDA. Work shoulder-to-shoulder with physicists, algorithm architects, and platform engineers, translating complex signal and image-processing models into high-performance GPU implementations that balance image quality against compute cost. Collaborate with CT platform teams around the globe to design, build, test, and deploy an industry-leading reconstruction software platform. Push the frontier of performance engineering and applied AI by profiling, parallelizing, optimizing memory use across caches and shared memory, and pioneering learned models that replace expensive physics with fast, accurate equivalents. This hybrid role is based in Cleveland, OH, with three flexible days in the office and two remote days each week . Regular travel is not typically </sp

NVIDIA Networking team is looking for an outstanding candidate who thrives in a multifaceted environment, to facilitate managing SW Releases for our leading SW products by taking responsibility for cross projects activities. In addition, ensure releases are delivered on time and in high quality, coordinate between development and testing groups and between global SW groups. The role will require to gain good understanding of products’ dependencies. What you’ll be doing: Be an effective leader in crafting and driving a delivery of high quality SW in an efficient way. Collaborate with Engineering, Operations, Architecture and Marketing across the globe to coordinate the release of products and ensure release will meet the schedule and with high quality. In parallel, partner with the QA teams to ensure alignment of all tests between the development, verification and QA groups. Take full ownership of projects from kickoff to signoff. Manage multiple parallel releases with strong attention to detail, ensuring clarity, alignment, and consistent communication across teams while tracking dependencies, milestones, and deliverables. Maintain clear, up-to-date visibility of the release status, ensuring all stakeholders have an accurate understanding of progress, next steps, priorities, and risks at any given time. Support Senior Release Managers with release activities. Own and manage selected cross-products topics (e.g., customer bugs, release checklists, RCAs, Triage, define and improve processes). Conduct release meetings and communicate release status. Resolve issues when they appear and raise red flags when needed. Work with planning and tracking systems to lead the release progress, and build release indicators. What we need to see: Bachelor's or Master’s degree or equivalent experience in Computer Science or industrial Engineering with techn

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The Role At SoFi, we're building AI capabilities that fundamentally change how our teams operate, innovate, and serve our members. We're looking for a Senior Director, AI Enterprise Transformation to lead enterprise-wide AI adoption by partnering with technology and business leaders to identify, prioritize, and deliver high-impact AI initiatives. This is a highly cross-functional leadership role for someone who combines deep technical understanding of modern AI technologies with exceptional executive influence and change leadership. You will work across Engineering, Product, Enterprise Architecture, Data, Corporate IT, Operations, and business functions to accelerate AI adoption, establish best practices, and drive measurable business outcomes. Success in this role requires someone who can translate emerging AI capabilities into scalable enterprise solutions while inspiring teams across SoFi to embrace new ways of working. You will serve as both a strategic advisor and transformation leader, helping shape SoFi's AI roadmap and ensuring AI investments deliver meaningful impact across the company. What You'll Do Lead enterprise-wide AI transformation initiatives that improve operational efficiency, employee productivity and growth for SoFi. Partner with executive leadership to develop and execute SoFi's AI tr

Base — $160k – $180k | OTE — ~$230k – $255k | Equity — 0.3% | In-person NYC About Datalab Datalab trains models that read documents reliably at scale. The world's most important information is trapped in PDFs, scans, and files that can't easily be parsed, and getting it out correctly matters. From frontier AI labs processing training data to Fortune 500s like Siemens extracting decades of engineering records, Datalab is where businesses turn to when extraction has to be right. We're at an 8-figure run rate with a team of 7. Anthropic is a customer. And we have hundreds more across FAANG, frontier AI labs, healthcare, finance, government, and legal. Our tools, chandra, surya, marker, and lift, have 70,000+ GitHub stars and broad developer mindshare. We're backed by founding members of OpenAI, FAIR, and Hugging Face. Role Overview We're looking for a Founding Customer Success Manager to own the relationship with our enterprise customers after they sign. You'll be accountable for adoption, retention, and growth — making sure customers get real value from our models, stay for the long run, and expand their usage over time. You'll be the face of Datalab for every account you own: their trusted advisor, their first call when something matters, and the person keeping their goals moving forward. You will be the commercial and relationship manager who owns the account strategy after a deal has been signed. You'll orchestrate the right people internally so the customer always feels progress. You'll know the product and the customer's architecture well enough to lead most conversations yourself, and you'll pull in Engineering when an account needs it. We also have a long tail of self-serve customers using our API. Many are strong candidates to expand into enterprise contracts, and you'll own that self-serve → enterprise motion end to end — from spotting high-potential accounts to closing the upgraded contract. This role is ideal for someone who thrives at the intersection of c

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 FinOps function is responsible for financial accountability, visibility, and optimization across all engineering-related spend at Plaid. This includes cloud infrastructure, AI/ML and data workloads, third-party SaaS tools, and other technical investments that support Plaid’s products and internal platforms. The team operates at the intersection of Engineering, Product, and Finance, ensuring that spending decisions are transparent, intentional, and aligned with product strategy and business priorities. Rather than functioning as a cost-control or approval layer, FinOps enables teams to understand, own, and optimize their spend while maintaining engineering velocity. Responsibilities Monitors and analyzes engineering spend across cloud, AI/ML, data platforms, and SaaS, identifying trends, anomalies, and optimization opportunities. Builds and maintains forecasts for engineering spend, partnering with Finance and engineering leaders to understand drivers, assumptions, and risks. Partners with engineering, product, and TPMs to incorporate cost considerations into roadmaps, architectural decisions, and execution plans. Leads cost optimization initiatives, such as rightsizing, commitment strategies, an