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I offer deep expertise in enterprise application development and implementation, with a focus on comprehensive ERP solutions, including Odoo and Microsoft Dynamics 365 Finance and Operations. I have vast experience in setting up and tailoring various Odoo modules, including: - Odoo Accounting - Odoo Sales - Odoo Inventory - Odoo HR - Odoo Payroll - Odoo Purchasing My overall Odoo proficiency encompasses: - Odoo Development - Odoo Customizations & Reporting - Odoo Integrations - Odoo Module Development & API Integration - Odoo Functional Consulting - Odoo Support and Training I deliver tailored ERP solutions that drive efficiency, optimize processes, and maximize your business's potential. Let's discuss how I can help you make your business better. Odoo Expert | Odoo Developer | Odoo Consultant | ERP Implementation | Business Analyst | Python Developer | Odoo Partner | Odoo Customization | Odoo ERP | PostgreSQL | Odoo Migration | CRM | Odoo Accounting | Inventory Management | Odoo.sh | Odoo Community | Odoo Enterprise | XML | QWeb | Business Process Optimization | Fit and Gap Analysis

I help businesses extract and process data using Python, SQL, and web scraping. I’m a data-oriented developer and consultant with strong experience in Python and SQL, specializing in data extraction, web scraping, and data processing. I’ve successfully delivered multiple scraping-focused projects, turning raw data into actionable insights. Currently, I work as an MES systems consultant for external clients, supporting manufacturing and industrial environments. I’m actively involved in AI-driven projects, including data analysis, machine learning, and visualization, with a strong focus on practical, business-ready solutions. • Strong in Python, SQL, and web scraping • Experience delivering real-world data extraction projects • MES systems consulting for external clients • Active interest and hands-on work in AI and data visualization • Clear communication and reliability throughout the project lifecycle

Full Stack developer, SaaS developer & AI Architect, who focused on building AI SaaS MVP. I'm skilled AI developer & Web developer (Python FastAPI React) Top Rated Plus | 100% Job Success | $200K+ earned | Only 5-star reviews ⭐⭐⭐⭐⭐ You'll get your AI SaaS prototype in 2 days, your AI SaaS MVP shipped in 6-12 weeks🚀 💬 "Ilya led the work as the AI SaaS solutions architect and AI full-stack developer, taking ownership of the overall architecture and delivery. Ilya delivered as an AI SaaS developer — balancing product, engineering, AI work without losing speed or quality. As a founder, Ilya was exactly the kind of engineering partner I was looking for. Highly recommend Ilya" — Jake Kinzelberg, Founder, Insurance AI SaaS, USA 💬 "Thanks to Ilya for developing my AI-powered SaaS MVP / PoC. Even at this stage, Ilya proved himself as an excellent AI Software developer and fullstack developer, proposed a clean UI UX SaaS Web design, built a solid backend with Python, FastAPI, a front end with React, Next.js" — Dmitri Dalla-Riva, Founder of Aidtrade, Australia 🎯 WHAT I DO I ship production-grade AI SaaS end-to-end. You come to me when you need: 🔹 A working SaaS MVP in weeks, not quarters — built on architecture that scales beyond the prototype 🔹 AI development, AI Integration, LLM integration — RAG pipelines, AI agent SaaS, Voice Agent 🔹 Full Stack development delivery — one senior point of contact, one accountable owner 🔹 A technical co-founder mindset — scoping the SaaS MVP development, making architecture decisions, owning the result 🛠 HOW I WORK As a Senior Full Stack Developer react python, SaaS Architect with more than 8 years of experience, I lead a small team — Senior Backend Developer (Python, Node.js), Frontend developer (React, Angular, Next.js), Full Stack Developer AI (JavaScript SaaS AI, WordPress, PHP), AI ML Engineer, Mobile App Developer (Flutter), UI UX designer SaaS UX designer — all under my direct coordination. In my work as a Full Stack AI SaaS developer and Senior Python developer, I act as your delivery manager & CTO partner: one point of contact, the delivery capacity of a small agency. I work with Founders as a long-term Partner — calm execution, clear communication. 📌 AI-Powered SaaS Development As a Full Stack Web Developer AI SaaS full stack developer SaaS AI Software Architect, I design & ship SaaS Startup MVP that scale beyond the first version. Multi-tenant architecture, role-based access, billing, webhooks, pipelines 🔹 SaaS architecture → Multi-tenant, RBAC, OAuth2/JWT, Stripe 🔹 SaaS data layer → PostgreSQL, Redis, Supabase, multi-tenant isolation 🔹 SaaS infrastructure → Docker, AWS, Azure, Vercel, Cloudflare, CI/CD 🔹 SaaS delivery & AI MVP Development → SaaS design, MVP-to-production in 6 weeks 📌 AI Software Development As an OpenAI Developer LangChain Data Scientist Machine learning Architect, I integrate LLM, RAG into SaaS 🔹 LLM integration → Claude, ChatGPT-5, LLaMA, Mistral — fine-tuning, prompt design 🔹 RAG & Vector DB → LangChain, FAISS, Qdrant, Pinecone, ChromaDB, pgvector — Voyage embeddings, hybrid search inside SaaS, AI SEO 🔹 Generative AI → Stable Diffusion, SDXL, LoRA — custom image pipelines 🔹 AI ML Engineer → AI automation, deep voice agent, Computer Vision, MCP integrations, dashboards, LLM-powered SaaS 📌 Full Stack Development As an AI Machine learning Python Full Stack Developer React developer, Senior Web Developer python, I own the SaaS product end-to-end — ReactJS, Next.js frontends, Python FastAPI, Node.js backends with Superbase as the data layer, the API layer in between, the AI layer woven through; MERN stack, WordPress developer, PHP 🔹 Frontend development → React, Next.js, TypeScript, Tailwind CSS, JavaScript 🔹 Backend development → Python FastAPI, Django, Node.js, REST, GraphQL APIs 🔹 Real-time → WebSockets, Server-Sent Events for streaming AI 🔹 Web Application architecture & Web Development → modular monorepos, microservices 🤖 SENIOR AI-AUGMENTED DEVELOPMENT As an Senior AI Engineer & Python Backend Developer, I use modern AI tools — GitHub Copilot for code-level acceleration & Claude Code with MCP for architecture, complex refactoring. Senior engineering judgment + AI augmentation lets me deliver SaaS MVP faster without sacrificing code quality or production reliability 🏆 MY UPWORK TRACK RECORD ✅ Top Rated Plus Expert ✅ 100% Job Success Score ✅ $200K+ earned delivering AI & SaaS Solutions ✅ 15 completed Upwork jobs ✅ 5-star average rating ✅ Upwork Skill Certified — Python Developer; Back-End Development 🎓 BACKGROUND Master’s in Data Science & AI, currently preparing a PhD in AI. I’m a Senior Full-Stack Developer, SaaS Developer & AI Solution Architect with 8+ years across 60+ projects 🤝 LET'S WORK TOGETHER If you're building SaaS full stack or AI solution — you need a technical partner who ships, owns, thinks like a co-founder — message me. You’re taken from idea to deployment — faster and smarter

I have Expert-Vetted Talent (EVT) badge - it's Upwork's top 1% freelancers — pre-screened by Upwork Talent Managers and experts in their field. Out of ~30 million programmers worldwide, only a few thousand know Algorithms & Data Structures better than I do, which is proven by programming competitions. Please, contact me if you need that skill level (top 0.01%). I can do algorithmic/performance work in C/C++, Python, SQL, Java, MQL4, MQL5, C#, Assembly, JavaScript, Julia, Rust, and probably other languages - learning them rapidly. I also work with AI, mostly in NLP and NLU: large language models including OpenAI GPT-3, Bloom, BloomZ, GPT-J 6B, LLaMA, Alpaca, etc.; HuggingFace Transformers, Accelerate; Petals, Deepspeed, zfp/zfpy; CUDA, CPU, and MPS (AArch 64 M2 MacOS Metal GPU) backends. I have some work experience with Apple Neural Engine (ANE). In AI, I also worked with XGBoost for predictions (including trading), LibSVM, TensorFlow, PyTorch, Scikit-learn, etc. I have the hardware in my home office for training and inference with large language models and other AI. English: C1 (Grammarly plugin says I use more unique words than 95% of other users, native speakers included). Polish: B1 (86%). Russian, Belarusian: Native. - With unique skills in Algorithms & Data Structures, I improve programs asymptotically (often 100 or more times on large input data). - 29 years of programming (started Basic and assembler on ZX Spectrum), 24 years of C/C++, 16 years of commercial work experience + 3 years of research projects. - Contributed to widely used Open Source projects: LLVM/Clang (my contribution is XRay profiler on ARM32 and AArch64 systems), Katana Graph (multiple small contributions mostly driven by the proprietary part where I do GPU/CUDA), CBMC "C Bounds Model Checking" (I contributed parallelized output of DIMACS formatted Boolean Satisfiability formula), oatpp (C++ web framework, I contributed bug-fixes), OWL (OptiX Wrapper Library, I contributed build fixes for Ubuntu), Galois (research project for distributed computations on graphs, I contributed GPU improvements) - Actively participated in bug reporting and reproduction (for NVIDIA CUDA, Cadical&kissat boolean satisfiability solver, JBOSS, MariaDB, Tensorflow, Linux, etc) - Led several open-source projects of my own: ProbQA (a video game recommendation system based on a high-performance Bayesian inference engine with CUDA, SIMD, and multi-threading); InSoAr (automatic reconstruction of software architecture from source code ), a multi-threaded Boolean Satisfiability solver, etc. Working for hire, implemented: - efficient multi-threading, scaling real-world workloads almost linearly with the number of CPU cores (128x for AMD Ryzen Threadripper 3990X) - SIMD vectorization (SSE/AVX), up to 8x improvement in computing thread or even copying (see my "Faster alternatives to memcpy" answer on Stackoverflow, URL upon request). - cache-aware algorithms: up to 50x improvement on some workloads - up to 20 trillion operations/second in CUDA (thousands of times faster than CPU) - up to the theoretical limit (6.8 Gigarays/second on RTX 2080 laptop GPU) in ray-tracing with OWL and OptiX - AVX512 and RTM (Restricted Transactional Memory) based acceleration, 16x improvement for float numbers -up to 20x improvements to cryptocurrency miners on CPU using AVX512 and cache-friendly algorithms - crypto-miners for Ethereum, Bittensor, Qubic 15K reputation on Stackoverflow: (1915854/serge-rogatch) Topcoder SRM score: 1480 - among top 5K programmers in the world - top 0.02% (rSerge) I developed all kinds of networking applications, from Linux Kernel modules up to Web applications. The majority of work was, of course, done at TCP/IP level with socket calls like send/recv/select. Programming languages: C++, C++11/14/17/20, C, Python, x86/x64/ARM/AArch64 assembly, SQL, C# .NET, JavaScript, HTML, CSS, Java, MQL4, MQL5, XML, Cypher, Rust. Libraries/Frameworks: PyTorch, Tensorflow, HuggingFace Transformers/Accelerate/Safetensors, Hivemind/Petals, OpenAI, tiktoken, Django, Flask, STL, LibSVM, XGBoost, libcurl, Selenium, PyTorch, Transformers. Technologies: OpenMP, CUDA, SIMD (AVX&SSE, RTM), Linux Kernel Modules, OptiX/OWL, RTX, raytracing. Theory/Principles/Know-how/Methodologies: Algorithms & Data Structures, Performance Optimization, Artificial Intelligence, Multithreading, Vectorization, OOP, Low-latency, High-frequency, Blockchain. Open source code: Clang, LLVM, LLVM's compiler-rt library, Linux Kernel, a few of my own repositories, contributions to AI and Algorithm open-source projects such as Petals and CBMC. Tools/APIs/Architectures/Platforms: PostgreSQL, MSSQL, MySQL, Neo4j, MATLAB, CMake, GIT, MT4, MetaTrader 5, Conda, PyCharm. Virtual Machines / Containers: Docker, VMWare, VirtualBox, QEmu, Hyper-V. OSes: Windows, Linux, Android, macOS

I help growing AI and B2B SaaS companies reduce AWS costs, stabilize deployments, improve monitoring, and prepare cloud infrastructure for scale. I don’t just “run DevOps”. I find the 20% of infrastructure issues that cause 80% of failures and overspending: unstable pipelines, slow builds, noisy deployments, mis-sized compute, always-on non-prod environments, missing alerts, weak access controls, and unsafe infrastructure changes. You get a clear action plan, quick wins in the first days, and production-safe improvements shipped via Terraform, CI/CD, and rollback-ready delivery. What you get from a cloud infrastructure optimization engagement: ✅ 5x faster releases via stable CI/CD and Terraform-driven delivery ✅ Up to 40% AWS cost reduction by eliminating waste and rightsizing resources ✅ Safer AWS migrations with minimal downtime and rollback plans ✅ Scalable, production-ready cloud infrastructure for growing SaaS and AI products ✅ 99.9% uptime mindset: monitoring, backups, health checks, and safe rollouts ⚙️How I work as an AWS DevOps Engineer (simple workflow): 1️⃣ Discovery & Assessment: thoroughly analyze your current infrastructure and pain points 2️⃣ Plan: clear scope, milestones, and the fastest first win 3️⃣ Implement: Build and automate with AWS DevOps Engineer best practices and documentation 4️⃣ Verify + handover: release runbook, rollback path tested, and short documentation Real examples: Non-Production Cloud Cost Reduction (~30%) Problem: Dev and test environments were running 24/7 at near-production scale, burning budget overnight and on weekends with no business value. Risk avoided: Cloud bill growing unsustainably as team scaled, budget pressure forcing cuts to production capacity. 🎯Result: Reduced non-production AWS spend by ~30% through AWS DevOps Engineer cost review, rightsizing, Spot Instance adoption, and automated start/stop scheduling with zero production impact. Industry: eCommerce (cloud-heavy workloads with clear non-prod/prod separation) - CI/CD for AWS Lambda (Python/Node.js): built 30+ pipelines as an AWS DevOps Engineer for build + deploy with unit tests and quality/security gates (SonarCloud, Orca). 🎯Result: developers can provision a new Lambda from a template in minutes using the guide (consistent standards, less manual setup). - CI/CD modernization: migrated 10+ pipelines from TeamCity to GitHub Actions with equivalent build, test, and deploy stages as an AWS DevOps Engineer. 🎯Result: standardized workflows and easier maintenance without vendor lock-in. - AWS Terraform + runbooks: built the AWS stack as IaC with terraform modules and safe plan/apply workflow, aligned with linux system administration practices and AWS DevOps Engineer delivery standards. 🎯Result: performance environment provisioning in ~10 minutes, plus start/stop automation to reduce idle AWS spend. - Automated Sitecore CMS deployment on AWS Windows EC2 🎯Result: Created and implemented Ansible playbooks and reusable roles as an AWS DevOps Engineer to fully automate Sitecore CMS installation on Windows EC2 instances in AWS. This reduced manual configuration work, improved deployment consistency, and made infrastructure setup faster and easier to reproduce. - Redshift cross-account migration delivered as devops engineer: moved a provisioned Redshift cluster to a new AWS account (serverless), restored from backup, and automated backups via AWS Backup. 🎯Result: higher data reliability plus an incident runbook for fast recovery. - IBM Cloud to AWS migration design as aws architect, AWS DevOps Engineer, and cloud engineer: created target (EKS) architecture and rebuilt the stack with kubernetes (EKS) terraform, and aws kubernetes, including aws docker image patterns. 🎯Result: production-ready infrastructure migration foundation with automated Amazon RDS snapshots, EKS cluster, and apps deployed via Helm charts. - Dagster Cloud Hybrid Agent on AWS ECS using Fargate: As a Senior DevOps Engineer I built a docker image + ci cd pipeline GitHub Actions to deploy a versioned agent into a client AWS account, with python docker build steps. 🎯Result: self-serve deployments and automated dataflow runs after merge, with SonarCloud + Orca gates in the loop. - Automated Solr deployment and configuration on RHEL with Ansible 🎯 Result: As a DevOps engineer Developed Ansible playbooks and roles to automate Solr installation and server-side configuration on Red Hat Enterprise Linux servers. This improved deployment reliability, reduced setup time, and minimized the risk of manual misconfiguration. ☎️ Message me with your repo or a short description of the current pain, and I’ll suggest the fastest path to stabilize releases with Senior AWS DevOps Engineer support.

Python AI developer specializing in production-grade AI systems: OpenAI API integrations, RAG pipelines, AI agents, and custom chatbots built to run reliably at scale, not just as demos. I build AI that holds up under real load. My background is in high-stakes fintech payment platforms processing millions of transactions and systems handling KYC verification - so I treat latency, reliability, and security as first-class requirements, not afterthoughts. That same engineering discipline goes into every AI build, whether it's a customer-facing chatbot or an internal automation agent. My core work covers OpenAI and ChatGPT integration, RAG systems over private knowledge bases with vector search, conversational AI and AI agents, prompt engineering, and embedding AI into existing products through clean FastAPI backends and React frontends. I'm certified in Anthropic's Claude API and work daily across OpenAI, Claude, and open-source LLMs. How I work: I start by mapping the actual problem before reaching for a model sometimes the right answer is a smaller, cheaper approach, not the biggest LLM. I move fast, communicate clearly, and deliver working software with documentation and handover so your team can own it after launch. Recent work: Built a real-time AI fraud-detection agent for a payment platform handling 25M+ transactions and 500K+ KYC checks per month - flagging suspicious activity at under 50ms latency without slowing down legitimate users. Separately delivered a RAG-powered assistant over a company's internal documentation that cut support response times significantly. If you're integrating OpenAI into your product, building an AI chatbot or agent, or need a Python AI developer who can ship reliable systems for the long term, let's talk.