Software Architect - Web Mobile App Architecture Design

@Microlent

Connecting NVIDIA Jetson edge inference with a Firebase and GCP backend requires a very specific approach to data orchestration, especially when delivering real-time coaching feedback. The biggest risk in elite sports tech is often the latency between the athlete movement and the cloud record. I've spent years building distributed systems that balance this edge-to-cloud handoff to ensure a small team doesn't get buried under architectural debt. We previously developed a Python-based deterministic scoring engine to handle high-stakes data accuracy for critical decision-making, which you can see at [freelancer_portfolio link: https://www.freelancer.com/portfolio-items/11337466-python-deterministic-scoring-engine]. I'll help you define the standards for your Slovenian contractor team and internal engineers so the telco white-label product integrates without breaking core services. My first step would be auditing how your event-driven pipeline handles simultaneous deployments across different facilities. I can put together a quick end-to-end system architecture document for free so you can see my approach first. Happy to jump on a quick call when you're ready. Rajesh

@shivmirthyusl

Hi, I’ve gone through the requirement and understand that you're building a scalable AI-powered sports performance platform where computer vision running on NVIDIA Jetson devices identifies athletes, recognizes exercises, and delivers real-time coaching feedback. The key challenge is designing a robust architecture that seamlessly connects edge AI inference with cloud services while supporting multiple institutional deployments, white-label integrations, and long-term scalability. I’ve worked on distributed platforms involving IoT, real-time data processing, cloud-native architectures, and MVP-to-scale product development. My focus would be establishing a clean event-driven architecture, defining data flow between edge and cloud, implementing Kubernetes-based deployment standards, and creating engineering patterns that allow the team to scale efficiently. A few questions: 1. What is the expected number of concurrent training environments and athletes per deployment? 2. Is low-latency feedback processed entirely on-device or partially in the cloud? 3. Are there compliance requirements around athlete performance data? 4. How mature is the current AI inference pipeline? Estimated timeline: 8–12 weeks for architecture definition, technical blueprint, and implementation roadmap. Happy to discuss further and share similar architecture experience. Best, SNR

@a4logic

Hello, With over seven years of experience in software engineering, I bring a wealth of knowledge and expertise to the table when it comes to architectural design. My competencies extend beyond mobile app and website development; I have a strong grasp of Python and Node.js backend systems, Firebase and Google Cloud infrastructures, as well as React-based web platforms. These are all pivotal for success in your project. Moreover, my familiarity with containerization, Kubernetes, and infrastructure-as-code will enable me to create a strong foundation that allows for multiple simultaneous deployments while connecting your edge AI layer to the cloud platform. As a leader who values high-quality code, testing, deployment, documentation, I would set the same standards for your team to ensure efficient scalability. Lastly, I am not only an excellent communicator but someone who can effectively explain architectural decisions to technical and non-technical stakeholders alike. The growing nature of your team necessitates someone who can handle onboarding new engineers seamlessly: this is an area where my extensive experience will really shine. Choose me and together we can design an end-to-end system architecture that maximizes both performance and potential! Thanks!

@n2rtechnologies

Hi, We've built performance tracking architectures for sports tech companies. Your infrastructure layer for movement intelligence needs solid cloud foundations and mobile-first design — we handle that stack daily with Python, Node.js, and scalable backend systems. Message me to discuss your architecture. Best Regards, Hasan

@dfordesigners

Hi there, I have extensive experience in designing and owning end-to-end system architectures for complex projects, including distributed systems with edge and cloud components. With a background in Python, Node.js, Firebase, Google Cloud, React, and React Native, I am well-equipped to lead the technical blueprint for your AI performance intelligence company. My strong grasp of real-time data pipelines and event-driven architectures, along with experience in sports technology and IoT environments, make me a valuable asset for defining integration patterns and setting engineering standards. Let's discuss how I can contribute to your project's success. Best, Kausar | Full Stack Developer

@diektech

Hi, This is Elias from Miami. I checked the details and understand you need a senior architect to own the technical blueprint across edge AI, cloud services, mobile, web, and real-time performance data for institutional sports deployments. The real challenge here is designing the integration layer between NVIDIA Jetson edge inference and the cloud platform so real-time coaching, athlete records, and multi-site deployments stay reliable as usage grows. I've worked on scalable platforms involving Python/Node.js backends, React/React Native, cloud infrastructure, real-time data flows, APIs, and system architecture. I’d approach this by first mapping edge-to-cloud communication, event flows, data ownership, deployment patterns, and failure modes. From there, I’d define clear standards for services, testing, observability, infrastructure, and documentation so the team can move quickly without creating technical debt. I have a few questions to get a better understanding: Q1 – Is the edge inference layer already running on Jetson hardware, or still being finalized? Q2 – Are you currently using event streaming/message queues between edge and cloud? Q3 – Is this role focused purely on architecture, or also hands-on implementation? I'd be happy to discuss the details and suggest the best approach for implementation. Looking forward to hearing from you.

@corpmember29

Hello, Most engineering teams focus on making AI models accurate. The real competitive advantage comes from building the infrastructure that allows those models to operate reliably across hundreds of training sessions, multiple venues, and future white-label deployments without architectural bottlenecks. As an experienced and versatile full-stack developer, I can bring immense value to your team and project as a software architect. My tenure spans over seven years, three of which I have served in senior architecture positions. Your need for a distributed system between edge and cloud components rings bells with my expertise, along with real-time data pipelines, event-driven architectures, containerization, Kubernetes, and infrastructure-as-code. A significant plus is my built-in familiarity with AI/ML deployment at the edge. Throughout my career, I've had some remarkable hands-on opportunities to integrate AI/ML into various domains which really resonate with your project’s context in sports technology, health technology, and IoT environments. I can assure you that my skills in Python and Node.js backend will be invaluable with regard to the project's mobile app development aspect based on React Native concept. Thanks Christian

@utamshingala

Hi, What caught my attention is that you're not looking for another engineer—you're looking for someone who can establish the architectural foundation that allows edge AI, cloud services, mobile apps, and real-time performance data to scale reliably across multiple deployments. Quick question: As institutional deployments grow, what do you see as the biggest architectural challenge today—real-time data synchronization, edge-to-cloud communication, or long-term athlete data management? Based on your requirements, I'd focus on: • Designing scalable edge-to-cloud architecture patterns for AI inference and real-time data flows • Establishing engineering standards, deployment strategies, and integration frameworks that support rapid growth • Creating a future-proof foundation across Google Cloud, Firebase, React, React Native, and NVIDIA Jetson environments Happy to discuss the platform vision and how to build an architecture that scales without accumulating technical debt. Best, Uttam Shingala

@Guptapuru304

Hello, We've thoroughly reviewed your project on designing a robust software architecture for an AI-driven sports technology platform. The requirements align perfectly with our expertise in AI-first product development and distributed systems architecture. Previously, we've successfully delivered a project involving AI-driven real-time feedback systems, integrating edge AI with cloud infrastructure, which resonates with your goal of enhancing athlete performance through computer vision. With over 8 years in AI-enabled SaaS and intelligent system architecture, we're adept at building scalable, maintainable solutions. Puru Gupta, ranked in the top 1% on Freelancer, will ensure that the technical blueprint of your platform is both innovative and resilient, accommodating multiple institutional deployments and seamless integration with your AI contractor team in Slovenia. Our experience with Python, Node.js, Kubernetes, and GCP, as well as AI expertise using LLMs and RAG systems, uniquely positions us to elevate your platform's design. We focus on uncompromised quality and transparent collaboration, ensuring engineering standards that empower your rapidly growing team. We invite you to message us with further details. Within 24 hours, we'll deliver a tailored proposal that addresses your specific needs. Looking forward to the opportunity to collaborate. Best regards, Puru Gupta

@ZohaibRoy

⭐⭐⭐⭐⭐ Design Scalable Systems for AI Performance Intelligence in Sports ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and see you're looking for a Senior Software Architect. You don’t need to look any further; Zohaib is here to help you! My team has successfully completed 50+ similar projects in system architecture. I will design the technical blueprint for your AI performance system, ensuring smooth integration across edge devices and cloud platforms. ➡️ Why Me? I can easily handle your project as I have over 7 years of experience in software engineering, specializing in system architecture, cloud infrastructure, and real-time data processing. My expertise includes designing distributed systems, event-driven architectures, and containerization. Additionally, I have a strong grip on AI/ML deployment and am familiar with sports technology, ensuring a comprehensive approach to your needs. ➡️ Let's have a quick chat to discuss your project in detail and let me show you samples of my previous work. Looking forward to discussing this with you in our chat. ➡️ Skills & Experience: ✅ System Architecture ✅ Cloud Infrastructure ✅ Real-time Data Processing ✅ Event-Driven Architectures ✅ Containerization ✅ Kubernetes ✅ Python Development ✅ Node.js Development ✅ Firebase ✅ Google Cloud ✅ React.js ✅ React Native ✅ AI/ML Deployment Waiting for your response! Best Regards, Zohaib

@onkarkulkarni8

Hi, your "Software Architect - Web Mobile App Architecture Design" project is right in my wheelhouse. I build modern JavaScript apps end to end — React/Vue/Next on the front and Node/Express on the back, in TypeScript where it helps. Working with python, website design, graphic design, mobile app development, cloud computing, uml design, software architecture, node.js, kubernetes, ai development, I focus on responsive, fast UIs, clean component structure, and reliable APIs — no page-builder shortcuts. I'll lock down the scope and key flows first, then ship in reviewable increments. Let's hop on a quick chat to align on your requirements? ⭐ 5.0/5 from a recent client: "This was wonderful experience and I also got an addtional choice of updating budget and other features which was not available in the old version of my existing software that I used to perform my d…" Final timeline and cost will be confirmed in chat after a complete understanding and documentation of the project expectations in detail.

@C0RETECHIES

Hello, What stands out here is that the computer vision layer is only one part of the challenge. The real architectural risk is supporting multiple facilities, edge inference on NVIDIA Jetson devices, real-time coaching feedback, and longitudinal athlete data while keeping deployments reliable, scalable, and easy to operate. We've worked on AI platforms and real-time analytics systems where large volumes of event data are processed, synchronized, and surfaced across web and mobile products. HERO2 is particularly relevant because it focuses on activity tracking, performance insights, and long-term analytics, while Recrugo demonstrates our experience building AI-driven platforms that convert complex inputs into structured intelligence. My focus would be defining the edge-to-cloud communication model, event-driven architecture, multi-tenant deployment strategy, data ownership boundaries, and engineering standards that allow new facilities and white-label partners to be onboarded without architectural rework. I believe getting these foundational decisions right early has a bigger impact on success than any individual technology choice. Best, Raksha

@nikhilgarg96

Hi, Your mission to build AI-powered performance intelligence for elite sports is exactly the kind of challenge I enjoy. I have 7+ years of experience designing scalable web platforms and distributed systems using Python, Node.js, React, Firebase, and Google Cloud. I have built cloud-native architectures, real-time data pipelines, REST APIs, and microservices, with hands-on experience in Docker, Kubernetes, CI/CD, and Infrastructure-as-Code. I understand the importance of connecting edge devices with centralized cloud services while maintaining low latency, reliability, and long-term scalability. Beyond development, I focus on creating clean architecture, enforcing engineering standards, and collaborating closely with cross-functional teams to deliver production-ready solutions. My experience working with AI integrations and data-driven applications enables me to quickly adapt to edge inference and computer vision workflows. I would be excited to help architect the foundation that powers your platform and supports rapid growth. Looking forward to discussing your project. Best Regards Nikhil...

@DrSyafiq

This needs a real architecture for an AI sports-performance platform: computer vision at the edge, athlete/exercise recognition, real-time coaching feedback, cloud sync, institutional deployments, and web/mobile interfaces that coaches can trust. The risk is letting CV, edge devices, backend services, and product UX evolve separately until scaling becomes impossible. I would start with the technical blueprint: capture/edge pipeline, model inference boundaries, identity/exercise data model, event streaming, cloud APIs, admin/coach roles, mobile/web app responsibilities, deployment environments, observability, and privacy/security controls. From there I would define milestones that prove simultaneous multi-athlete feedback and institutional rollout before building broad UI polish. I would focus on: - edge AI + cloud architecture, real-time event flow, API contracts, and data model - web/mobile role design for coaches/admins, feedback review, and deployment management - scalability, monitoring, failure recovery, security, and implementation roadmap If useful, I can start with a concise architecture plan and milestone breakdown so your engineering team has a stable blueprint before implementation starts. Best, Dr. Syafiq

@skalogir

Hi there, I understand you need a senior technical architect to define the end-to-end blueprint for an elite-sport AI platform spanning NVIDIA Jetson edge inference, Python/Node.js backend services, Firebase/GCP cloud infrastructure, React web, React Native mobile, real-time movement data, athlete profiles, telco white-label integration, and scalable institutional deployments. I have strong experience designing distributed edge-cloud systems, event-driven architectures, real-time data pipelines, Kubernetes/containerized infrastructure, infrastructure-as-code, engineering standards, API integration patterns, observability, testing strategy, and technical leadership across fast-growing product teams. I would map the current architecture, define scalable edge-to-cloud data flows, standardize service boundaries, deployment patterns, security, data models, CI/CD, documentation, and team engineering practices so the platform can scale reliably without accumulating technical debt. Q1: What is the current edge-to-cloud communication model between Jetson devices and GCP/Firebase? Q2: Are you looking for hands-on implementation leadership or primarily architecture governance? Q3: What are the main latency, availability, and deployment targets for institutional environments? Best regards, Stratos

@seefattechnologi

I have built and maintained similar distributed platforms spanning AI, cloud, mobile, and edge environments. My experience includes designing scalable architectures with Python, Node.js, React, React Native, Kubernetes, GCP, event-driven systems, and AI-powered applications. I can help define the technical blueprint, integration patterns, engineering standards, and deployment strategy needed to support reliable multi-site deployments while keeping the platform scalable and maintainable. How are the NVIDIA Jetson devices currently communicating with the cloud platform—directly through APIs, message queues, or a custom edge synchronization layer?

@vladang

What stands out here is that the challenge isn’t the computer vision itself—it’s making sure dozens of deployments can run reliably without every new customer introducing architectural complexity. I’d start by mapping the flow from Jetson inference outputs through cloud ingestion, storage, and real-time feedback delivery, then define clear contracts between edge and cloud so AI, backend, and frontend teams can work independently. From there, I’d establish the event pipeline, data model for athlete histories and movement records, and deployment patterns that support both your core platform and telco white-label environments without branching the product. I’ve spent the last several years designing Python and Node.js systems where reliability mattered more than feature velocity, including distributed services that needed clean operational boundaries as teams scaled. I’d also put strong emphasis on observability and failure handling at the edge, since intermittent connectivity and device state drift tend to become real-world problems long before cloud scalability does. I’m comfortable working directly with product leadership, engineering teams, and external AI partners, and can start contributing immediately.

@Srashtasoft

Dear Hiring Team, Your vision of building the infrastructure layer for human movement intelligence aligns closely with my experience designing scalable, AI-enabled platforms. With 7+ years of software engineering expertise, I have led the architecture and delivery of distributed systems spanning cloud, edge devices, mobile applications, and real-time data processing. I can help define the end-to-end technical blueprint connecting NVIDIA Jetson edge inference with Google Cloud services, establishing secure, event-driven communication patterns and resilient data pipelines for athlete performance analytics. My background includes Python and Node.js backend development, Kubernetes-based deployments, infrastructure-as-code, microservices, and designing systems that scale across multiple institutional environments without compromising maintainability. Beyond implementation, I focus on engineering excellence—setting standards for code quality, testing, CI/CD, documentation, and architectural governance that enable small teams to move quickly while avoiding technical debt. I am comfortable collaborating across multidisciplinary teams, including AI researchers, product leaders, and non-technical stakeholders, translating complex architectural decisions into practical outcomes. Best regards, Jemin Sagar

@ciss26

Hello, I hope you are doing well. I understand that you are looking to build a MOBILE APPLICATION, and I would be happy to help. I have extensive experience in designing and developing applications and have successfully delivered many projects. What I offer: -Development using the latest technologies -Daily project updates and clear communication -On-time delivery within the agreed timeline -Complete source code provided after project completion -One year of support for the developed work -10+ years of experience in web and app development -Fully responsive, fast-loading, and SEO-friendly design -A powerful super admin panel to manage the entire system Please feel free to initiate a chat so we can discuss your requirements in detail. Thank you and regards, Dheeraj K.