Principal Full-Stack Engineer (React Native • Node.js • AWS • AI Infrastructure) Mission Own the entire engineering stack and take FitCheck from its current state to a stable, production-ready application. You will architect, build, integrate, deploy, and lead all technical execution across mobile, backend, infrastructure, and AI services. Required Skills * React Native (Expo) * TypeScript * Node.js (NestJS) * PostgreSQL / Aurora * Kafka * Redis * REST APIs * WebSockets * AWS * EKS * ECS * EC2 * S3 * CloudFront * IAM * CloudWatch * Kubernetes * Docker * GitHub Actions CI/CD * Cloudflare * Firebase * GPU deployment on AWS * PyTorch model deployment * AI inference APIs * Authentication * Performance optimization * Security * Monitoring * Production deployments Responsibilities * Own the entire codebase. * Lead architecture decisions. * Build frontend and backend features. * Design and implement APIs. * Deploy and maintain AWS infrastructure. * Build and maintain CI/CD pipelines. * Deploy and manage GPU inference servers. * Optimize performance and scalability. * Review all code. * Fix production issues. * Ship new releases. * Coordinate any additional contractors if needed. * Take full ownership of technical delivery. Requirements * 10+ years software engineering. * Led production applications from development through launch. * Expert in React Native and Node.js. * Expert in AWS. * Experience deploying AI workloads on GPUs. * Experience scaling applications to hundreds of thousands of users. * Strong architectural and DevOps experience. * Excellent communication and ownership. Success Criteria Within the first 90 days: * Complete integration of frontend and backend. * Production-ready CI/CD. * Stable AWS infrastructure. * Reliable AI inference pipeline. * End-to-end testing. * Production deployment. * Documentation. * Clear engineering roadmap.

Existing founder is looking for a full stack engineer to be the founding engineer at Socratix, an agentic AI powered data platform for sales teams connecting Zoom, Teams and other communication data together to drive insights and deals. Product is currently in MVP state and requires development to a SOC II production grade platform for early customers. Ideally, this role becomes full time as part of the founding team presenting to investors later in the year. Must have an understanding and appetite for startups and working in an unstructured environment with a build mentality. Part time is an option for Sr. experienced engineers who have the capacity to execute rapidly due to their experience. Equity and salary will be discussed. Founder is in NY, NJ, but open to locations. Remote role.

About Us We are a forward-thinking AI enterprise software company building governance solutions. Our systems combine Python engineering, Natural Language Processing, and Machine Learning to deliver secure governance solutions. We’re seeking a Back-End Python Engineer with expertise in AWS deployed applications, GITHUB CI/CD pipelines, DJANGO, ML Pipelines, Endpoint Integration, Sagemaker, containerization, Use of AI to design front end applications and debug code. Key Responsibilities Design, develop, and maintain back-end services in Python to support software application Debug Application for Quality and Assurance Build Data Connectors for Application Integration Implement new features with front end design as needed Containerize and deploy services across AWS infrastructure. Build and scale RESTful APIs and microservices (Django + DRF) that integrate into automated pipelines. Tune system performance (network, I/O, memory, GPU utilization) for optimization. Architect and maintain databases (SQL & NoSQL), ensuring query optimization, high availability, and caching (Redis). Integrate background processing (Celery) and real-time communication (WebSockets) into containerized environments. Collaborate with DevOps, front-end, and AI/ML teams to deliver end-to-end automated workflows. Apply best practices in system design (SOLID, DRY, KISS), Python standards (PEP8), and secure infrastructure deployment. Qualifications Core Skills Proficiency in Python (OOP, async, functional programming, data structures). Expert-level knowledge of AWS Infrastructure (deployment, operators, CI/CD, scaling). Strong background in containerization (Docker, Podman) and Kubernetes-native orchestration patterns. Experience supporting AI Dev automation workflows and integrating back-end services with automated pipelines. Deep knowledge of Django & DRF: ORM, serializers, view sets, permissions, HTTP methods. Advanced database design & optimization for high-throughput applications. Familiarity with Redis caching, Celery task queues, and uWSGI/ASGI communication layers. Solid testing skills (pytest/unittest) and CI/CD pipelines with Git. Preferred Expertise Hands-on experience with GPU-enabled workloads and hardware acceleration in containerized environments. Familiarity with infrastructure automation tools (Ansible, Terraform, or similar). Agile/Scrum team experience and use of task tracking (Jira, Trello). What We’re Looking For We want an engineer who: PRIORITIZES SECURITY OF SYSTEMS AND INFRASTRUCTURE ACROSS SECURITY FRAMEWORKS Builds automation-first systems that support AI Dev workflows from code to deployment. Thinks about performance and scalability at the infrastructure + software level. Collaborates across teams (DevOps, AI/ML, product) to deliver fully integrated, automated platforms.

Eligibility: This role is open to U.S. citizens only due to client security and compliance requirements. Please apply through this posting only — do not contact Data-Sleek directly regarding this position. Applications received outside this channel will not be considered and reported to Upwork. Data-Sleek is looking for a Senior AI Solutions Engineer to lead our on-premise and government-cloud AI deployments. You will design, build, and deploy AI-powered data pipelines for clients who cannot use commercial cloud due to ITAR, CMMC, or other data residency constraints, beginning with a client in the aerospace and defense sector. Beyond this first engagement, you will become Data-Sleek's go-to engineer for AI deployments across defense and aerospace clients, building the practice rather than just executing a single project. About Data-Sleek Founded in 2020, Data‑Sleek® is a U.S.-based AI and data consulting firm that helps mid-market companies build the data foundation that AI actually runs on. We own the full path — data strategy, architecture, integration, warehousing, and AI implementation — so organizations can adopt AI with confidence, stay compliant, and scale, without first hiring an internal data team. Our distributed U.S. team (San Francisco, Los Angeles, Irvine, Dallas, Chicago, and New York) partners with clients across healthcare, finance, insurance, logistics, and technology, modernizing data platforms with best-in-class tools like Snowflake, dbt, Fivetran, Tableau, and AWS. Trusted by Fortune 500 institutions and growing companies alike, Data‑Sleek turns complex data into measurable outcomes — faster insight, lower cost, and AI projects that deliver. About the Role You will own the technical delivery of AI-powered data pipelines in restricted environments where commercial cloud is not an option. The immediate engagement centers on a Product Lifecycle Management (PLM) data migration: building a pipeline that connects to a client's SharePoint on a restricted Microsoft 365 government tenant, reads engineering documents, classifies and summarizes them, detects duplicates, and rates naming-convention compliance to produce a migration-readiness report. You will start on-premise, then help the client evaluate and move to government cloud for production. Key Responsibilities AI Pipeline Development Build AI pipelines that connect to a client's SharePoint on a government cloud tenant, read engineering documents, classify them by type, generate summaries, detect duplicates, and rate naming-convention compliance in support of PLM data migration. Catalog large document repositories and produce migration-readiness reports and Excel catalogs that give clients a clear, measurable picture of their data. Engineer document-parsing workflows across DOCX, PDF, and XLSX formats, including embedding generation and database operations. On-Premise & Government Cloud Deployment Deploy on-premise first — a Mac Mini running Gemma via Ollama — standing up, serving, and tuning local inference infrastructure. Evaluate and migrate to production on Azure OpenAI (Azure Government) or AWS Bedrock (GovCloud) when the client is ready to scale. Keep deployments compliant within ITAR-sensitive, restricted-network boundaries throughout. Architecture & Cost Advisory Produce cost models and architecture recommendations that help client IT teams make informed platform decisions based on measured data, not vendor pitches. Compare deployment options — local, Azure Government, and AWS GovCloud — on cost, performance, and compliance, and explain the trade-offs clearly. Practice Building & Delivery Serve as Data-Sleek's go-to engineer for AI deployments across defense and aerospace clients. Build a reusable capability — a repeatable AI-solutions practice — rather than executing a single one-off project. What You Bring Required U.S. Citizen: U.S. citizenship is required and non-negotiable due to ITAR and client security and compliance requirements. Production LLM deployment: You have stood up inference infrastructure — not just called an API. You've handled model loading, memory constraints, failure modes, and throughput tuning in a real deployment. Local inference: Ollama, vLLM, llama.cpp, LM Studio, or TGI. You've served open-source models (Gemma, Llama, Mistral) on local hardware. Cloud AI platforms: Azure OpenAI or AWS Bedrock — at least one. Service configuration, model access, authentication, and token-based pricing. Python: Pipeline engineering — document parsing (DOCX, PDF, XLSX), API integrations, embedding generation, and database operations (SQLite, Postgres). Experience: 5+ years post-degree in software engineering, data engineering, or ML engineering. Strong Preferences Microsoft ecosystem: Entra ID, Microsoft Graph API, and SharePoint REST API at the API level. GCC High experience is a bonus. MCP (Model Context Protocol): Experience building or consuming MCP servers — a significant plus for a fast-evolving protocol. Workflow orchestration: n8n, Temporal, Airflow, or similar. The pipeline is orchestrated, not scripted. Government cloud awareness: Understanding of what FedRAMP High, IL4/IL5, and ITAR mean for cloud architecture decisions. Embeddings & vector similarity: sentence-transformers, pgvector, Qdrant, or FAISS for duplicate detection. 
Bonus (valued if present) Aerospace or defense experience: Familiarity with ECOs, BOMs, and AS9100 saves ramp time. Apple Silicon optimization: MLX, Metal acceleration, and Ollama tuning on M-series chips. Agentic frameworks: Bedrock AgentCore or Azure AI Foundry — the future direction involves agentic AI workflows on government cloud. What This Role Is Not Model training or fine-tuning. This is deployment engineering, not research. Data science or statistical modeling. The AI here is document understanding and classification, not predictive analytics. Frontend development. The deliverable is an Excel catalog and a report, not a web app. Sales or client acquisition. Data-Sleek's leadership manages the client relationship; you focus on delivery. Engagement & Compensation Remote, US-based. Occasional on-site travel to client facilities for hardware deployment and workshops may be needed. An average of 2–3 trips for the first engagement may be possible. Compensation. $40-$55/hour Why Join Data-Sleek? At Data-Sleek, you'll lead AI deployments in environments most engineers never touch — government cloud and on-premise systems where commercial tools simply aren't an option. Your work will directly shape how defense and aerospace clients adopt AI, and you'll build a reusable capability the company grows around. We focus on doing the right thing architecturally rather than selling the most expensive option, and we give our engineers the autonomy to deliver real solutions for real constraints. How to Apply If you've shipped real LLM deployments with real constraints, we'd like to hear from you. Please submit: Your resume A brief note describing one LLM deployment you've shipped — what model, what infrastructure, what data source, and what went wrong. Data-Sleek® is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all contractors.

Looking for someone who used to hand code before the day of AI, especially in PHP/node, now proficient in claude code and using AI in servers and CLI. Really good at devops, security, and lead generation and marketing. Looking for an all around Ops guy and software engineer

Description: I am looking for an experienced freelancer to help me build a centralized AI-integrated knowledge management system in Notion. This system will serve as the backbone for managing large-scale projects, organizing 1,000+ PDF documents, and leveraging AI tools for semantic search, automated categorization, and document summarization. It must be scalable, user-friendly, and designed to support long-term collaboration and growth. The ideal candidate will have expertise in Notion, AI integrations (e.g., Claude, OpenAI, LangChain), automation workflows (e.g., Zapier, Make, or APIs), and file management processes (including OCR). The system should be operational from day one, with all files uploaded, categorized, and fully searchable. Project Goals: 1. Fully Functional System in Notion: Create a centralized knowledge management hub in Notion to organize and manage all scanned files and documents. Upload and categorize 1,000+ PDF files into the system during setup. Build a clean, intuitive interface for managing projects, tasks, and documents. 2. AI Integration: Integrate AI tools (e.g., Claude, OpenAI, Notion AI) for the following: Semantic search: Search by meaning rather than keywords. Document summarization and tagging: Automatically generate summaries and metadata for files. Automated categorization: Categorize files by topics, projects, and metadata (e.g., project name, date, type). AI conversation logs: Enable collaborative decision-making and log AI-generated insights for shared review. 3. File Management and Automation: Automate workflows for importing, renaming, tagging, and categorizing files based on pre-defined rules. Ensure the system can handle OCR (Optical Character Recognition) to make PDFs fully searchable. Provide a blueprint for OCR settings, file-naming conventions, and file preparation best practices. 4. Collaborative Features: Enable multi-user access with role-based permissions for specific projects or categories. Set up dashboards and shared views for collaboration and task tracking. 5. Scalability and Independence: Design the system to handle thousands of files and multiple projects without performance issues. Provide training and documentation so I can independently manage and expand the system in the future. Deliverables: A. Scanning and File Preparation: Provide a step-by-step blueprint for scanning files, including OCR settings and file-naming conventions. Ensure all 1,000+ PDF files are uploaded, tagged, and categorized in Notion during setup. B. Notion Knowledge Base Setup: Build a clean and interconnected workspace in Notion with: Categories, tags, and metadata for file organization. Dashboards for managing projects, tasks, and documents. Automated workflows for file renaming and categorization. C. AI Integration: Integrate Claude, OpenAI, or Notion’s AI for: Semantic search and document summarization. Automated tagging and categorization based on file content. D. Collaboration Features: Set up shared access for multi-user collaboration with role-based permissions. Incorporate an AI conversation log feature to track collaborative decisions and insights. E. Testing and Final Documentation: Test the system with all files uploaded to confirm functionality. Provide a short video tutorial or detailed written guide explaining how to use, maintain, and expand the system. Requirements: The ideal candidate will have: Proven experience with Notion, including advanced setups and database design. Expertise in AI integrations, such as Claude, OpenAI, LangChain, or Notion’s native AI. Familiarity with OCR workflows, file automation, and document management best practices. Strong communication skills to provide clear documentation and training. A proactive approach to safeguarding data, including locking pages, setting permissions, and creating backups. Budget and Timeline: Budget: $900–$1,200 for the full setup and integration. Timeline: Completed within 2–3 weeks from project start. To Apply: Please include the following in your proposal: A brief overview of your experience with similar projects. Examples of previous work, including Notion setups, AI integrations, or file management workflows. Your proposed timeline and approach to completing this project. Any suggestions you have for improving the system.

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I have an app built in Google AI Studio and am using Google Cloud Run and Firebase. Everything works on the dev site, but I need assistance with launching the app and addressing issues related to Google Cloud Run and Firebase. The ideal freelancer will have experience in these platforms to ensure a smooth launch.

Need a freelancer to install and configure a Chatbase AI chatbot on a local service business website. Project Scope: * Install a pre-built Chatbase chatbot on the client’s website. * Configure lead capture to collect: * Name * Phone number * Email address * Service requested * Project details * Project timeline * Configure email notifications so the client receives new lead information automatically. * Verify the chatbot is functioning correctly on desktop and mobile devices. * Test the lead capture process from start to finish. * Provide screenshots or a brief walkthrough showing successful installation and testing. Requirements: * Experience with WordPress websites. * Experience installing website chat widgets or AI chatbots. * Familiarity with Chatbase is preferred. * Ability to troubleshoot website integration issues. * Strong communication and ability to complete projects quickly. Deliverables: 1. Chatbot installed and visible on the website. 2. Lead capture functioning correctly. 3. Email notifications functioning correctly. 4. Successful test lead submitted and verified. 5. Brief documentation of what was completed. Expected turnaround: 3 business days.

We are a fast-growing telecom / AI-First CPaaS serving sms and voice API's. We are building the first AI-first communications platform (SMS, Voice, RCS, AI agents) designed for speed, simplicity, and real-world business outcomes. We are not looking for a “task completer.” We are looking for a true senior engineer who: thinks in systems moves fast makes decisions independently writes clean, scalable code uses AI tools (Claude, etc.) as a force multiplier ⚠️ Read This First *DO NOT APPLY IF YOU ARE PRETENDING TO BE IN A DIFFERENT COUNTRY. PROOF OF RESIDENCY IS REQUIRED. Most applicants will not be a fit. If you need: detailed tickets hand-holding constant direction This is NOT the role for you. If you are the type of engineer who: sees a problem and solves it end-to-end improves architecture without being asked ships quickly without sacrificing quality You will thrive here. What You’ll Do Build and ship full-stack features across our platform (messaging, voice, AI workflows) Make architectural decisions (not just implement) Improve system performance, reliability, and scalability Work directly with founders (no PM layers) Move from idea → production very quickly What We Expect (Non-Negotiable) 5+ years real full-stack experience (not just titles) Strong backend experience (Node.js / APIs / infra) Strong frontend experience (React or similar) Experience building production systems at scale Ability to work autonomously with minimal direction High ownership mentality Bonus (but highly valuable) Experience with telecom / CPaaS / messaging Experience with AI integrations (LLMs, agents, workflows) Experience optimizing performance at scale Startup experience (especially early-stage or fast growth) How We Work Small, high-output team Very fast iteration cycles No unnecessary meetings High trust, high expectations We use AI tools heavily (Claude, etc.) — you should too What We Care About Most Not your resume. We care about: How you think How you build How fast you execute The quality of your code To Apply Please include: Links to projects you’ve built (real production work) A short explanation of: a system you designed end-to-end a difficult technical decision you made independently Your GitHub Optional (but strong signal): Share how you use AI (Claude, etc.) in your workflow Compensation Competitive (based on experience) Long-term opportunity with a fast-growing, profitable company If you are truly senior, this will feel obvious. If not, this role will be very uncomfortable. **THIS IS A FT, HOURLY ROLE. PROVIDE YOUR REQUESTED HOURLY RATE IN PROPOSAL**