Job Description We are looking for an experienced AI/automation developer to build a reusable conversational agent that can book appointments, collect payments, and integrate with different third-party systems through APIs. The solution should not be limited to one industry. It should have a modular, API-first architecture so it can be configured for healthcare, beauty, consulting, home services, restaurants, professional services, and other appointment-based businesses. The agent should be capable of communicating with customers, checking real-time availability, booking or rescheduling appointments, collecting required customer details, processing payments securely, and sending confirmations and reminders. Core Features AI-powered conversational booking flow Check real-time staff, service, and location availability Book, reschedule, and cancel appointments Support multiple services, employees, locations, and time zones Collect customer information and custom booking questions Calculate service prices, deposits, taxes, and discounts Generate secure payment links or payment sessions Confirm payment status before finalizing appointments Send booking confirmations and reminders Handle common customer questions Escalate conversations to a human when required Maintain conversation, booking, and payment logs Admin configuration for business rules and integrations Integration Requirements The platform should support integration through REST APIs, webhooks, and reusable connectors. Initial integrations may include: Google Calendar and Microsoft Outlook Calendly or similar scheduling platforms Stripe, PayPal, Square, or other payment gateways CRM and ERP systems Custom booking platforms Email, SMS, WhatsApp, web chat, or voice systems Zapier, Make, or n8n where appropriate We understand that no solution can automatically integrate with every system without configuration. The goal is to create a standardized integration layer that makes adding new systems fast and manageable. Technical Expectations Secure and scalable backend architecture OpenAI, Claude, Gemini, or another suitable LLM Function calling/tool calling for reliable actions Structured workflows rather than relying only on free-form AI responses Authentication and role-based access API key and credential management Webhook handling and retry mechanisms Time-zone and daylight-saving support Idempotency to prevent duplicate bookings or payments Proper error handling and audit logs PCI-conscious payment implementation without storing raw card details Documentation for adding new integrations Deliverables Technical architecture and database design Working MVP of the AI booking and payment agent Calendar and payment integrations Reusable connector or adapter framework Admin configuration interface API and webhook documentation Testing and deployment Source code and setup instructions Ideal Candidate Strong experience with AI agents and LLM function calling Experience building appointment-booking systems Experience with Stripe or similar payment APIs Strong Node.js, Python, or equivalent backend experience Knowledge of webhooks, OAuth, REST APIs, and third-party integrations Experience with conversational workflows, chatbots, or voice agents Ability to design a reusable multi-tenant architecture Strong understanding of security and payment compliance Please include relevant examples, your recommended architecture, development timeline, estimated cost, and the integrations you recommend for the first MVP.

EroFlow Intelligence is an enterprise-grade, autonomous AI orchestration pipeline designed to mitigate global supply chain disruptions for aerospace manufacturing. Built using a multi-agent framework, the system automates the entire lifecycle of risk detection, impact analysis, and procurement mitigation without requiring human intervention for standard operational anomalies. The architecture coordinates three specialized, asynchronous AI agents that communicate via a centralized event bus to solve complex logistical bottlenecks in real-time. Core Agent Architecture & Workflow 1. The Sentinel Agent (Data Ingestion & Extraction) Role: Continuous Global Monitoring. Function: Utilizes advanced LLM-driven web scraping and unstructured data extraction to monitor global news feeds, geopolitical shifts, weather anomalies, and shipping port telemetry. Trigger: If it detects a disruption (e.g., a port strike or critical mineral shortage), it extracts key entities (materials affected, estimated delay times) and passes a structured JSON payload to the orchestration layer. 2. The Impact Assessment Agent (Predictive Modeling) Role: Deep Cross-Referencing & Analytics. Function: Upon receiving a trigger, this agent cross-references the disrupted material with the company’s internal ERP (Enterprise Resource Planning) database and current inventory levels. Output: It runs a predictive analysis to determine exactly which production lines will stall and calculates the financial risk, assigning a high/medium/low priority score to the event. 3. The Mitigation & Logistics Agent (Autonomous Execution) Role: Operational Resolution. Function: If the risk score exceeds a specific threshold, this agent is authorized to take action. It autonomously queries pre-vetted alternative suppliers via APIs, negotiates standard volume pricing based on historical contract data, drafts a comprehensive procurement proposal, and queues the purchase order for final human sign-off (or executes it automatically if under a certain dollar cap). Technical Stack (The Blueprint) Frameworks: LangGraph / CrewAI (for multi-agent state management and deterministic routing). Core Language: Python 3.11+ Data Layer: PostgreSQL (for ERP syncing) & Pinecone / Qdrant (Vector database for storing and querying supplier contract PDFs and historical compliance documentation). LLM Orchestration: OpenAI GPT-4o / Anthropic Claude 3.5 Sonnet utilized via structured outputs (Pydantic parsing) to ensure strict API data integrity. Hosting & DevOps: Containerized via Docker, orchestrated via Kubernetes, and deployed on AWS with asynchronous task queues managed by Celery and Redis. Quantifiable Business Results (The Hook) 92% Reduction in supply chain anomaly response time (from 48 hours down to 14 minutes). Automated Recovery: Successfully mitigated over 140 potential production line stalls autonomously in simulated stress tests. Cost Efficiency: Saved an estimated $1.2M in expedited shipping fees by predicting bottlenecks 10 days before they impacted manufacturing floors.

About us We're a consulting firm building agentic AI solutions for clients in law, healthcare, education, retail, commerce, and regulatory consulting. Our work sits at the intersection of LLM orchestration, workflow automation, and compliance-sensitive deployment. We're not building toy demos. We ship production systems for organisations where reliability, auditability, and regulatory posture actually matter. The role We're hiring a lead full-stack developer to take technical ownership of our agentic automation builds and grow a small delivery team. You'll be the person clients trust to architect the solution, and the person our team look to for direction. You'll be doing a mix of: Designing end-to-end agentic workflows (planning, tool use, memory, retrieval, human-in-the-loop checkpoints) Building and shipping client solutions across the stack — backend orchestration, integrations, frontends, infrastructure Leading and reviewing the work of other developers as we scale Working directly with clients to translate ambiguous business problems into reliable automation Setting our technical standards: evals, observability, prompt and tool governance, deployment patterns Required experience 5+ years full-stack development, with strong backend fundamentals (Python and/or TypeScript) Demonstrable production experience with agentic systems — not just chatbots. We want to see agents that plan, use tools, recover from errors, and operate over real workflows Hands-on with at least one major agent framework or orchestration approach (LangGraph, CrewAI, custom orchestration, Claude/OpenAI tool use, MCP, etc.) Experience integrating with enterprise systems via APIs and webhooks (CRM, email, document stores, internal databases) Cloud deployment experience (AWS preferred; Azure or GCP acceptable) Frontend competence in React or similar — you don't need to be a designer, but you should be able to ship a clean client-facing UI Strong written English and clear communication. You'll be talking to non-technical stakeholders regularly Nice to have Experience working in or with regulated industries (healthcare, legal, financial services, education) Familiarity with RAG pipelines, vector stores, and retrieval evaluation Exposure to compliance frameworks (SOC 2, ISO 27001, GDPR, sector-specific regs) Prior tech lead or solo founder experience Comfort with infrastructure-as-code (Terraform, CDK) Comfortable working with and reviewing the output from agentic coding systems to speed up development (Codex, Claude Code etc.) What we're offering Long-term engagement, starting with a paid trial project Competitive hourly rate (share your expectation in your application) Real ownership and the opportunity to shape how we deliver Interesting, varied work across sectors — no two builds the same How to apply In your proposal, please include: A short summary of an agentic system you've shipped to production. What did it do, what was the architecture, and what broke that you had to fix? Your stack of choice for a new agentic build today, and why Your hourly rate and approximate weekly availability A link to code or a portfolio if you have one

We are looking for an experienced API Integration Engineer to help finalize and optimize integrations for our security platform. The ideal candidate will have strong experience working with third-party APIs, authentication mechanisms, cloud-based AI services, and troubleshooting production integrations. Your primary responsibility will be to validate and configure API credentials for URL classification and IP reputation services, identify and integrate the correct Large Language Model (LLM) endpoint (OpenAI, Claude, Azure OpenAI, or custom/internal models), and ensure the overall system is secure, reliable, and high performing. This is a short-term contract with the potential for ongoing work if the engagement is successful. Responsibilities 1. Verify and configure API credentials for: - URL Classification services - IP Reputation services - Threat Intelligence APIs 2. Validate authentication methods including: - API Keys - OAuth 2.0 - Bearer Tokens - JWT 3. Identify the correct LLM provider and endpoint, including: - OpenAI - Claude (Anthropic) - Azure OpenAI - Google Gemini - Internal/custom LLM deployments 4. Confirm that all required API keys, secrets, and access tokens are correctly configured. 5. Test API connectivity and verify successful authentication. 6. Troubleshoot integration issues across development and production environments. 7. Optimize API performance, latency, retry mechanisms, and error handling. 8. Collaborate closely with our development team to resolve integration challenges. 9. Document the configuration process and provide recommendations for future maintenance. 10. Ensure best practices for credential management and secure secret storage. Required Skills 1. Strong experience integrating REST APIs 2. Experience with authentication protocols: - API Keys - OAuth2 - JWT - Bearer Tokens 3. Experience working with AI APIs including one or more of: - OpenAI - Anthropic Claude - Azure OpenAI - Google Gemini 4. Familiarity with URL reputation and threat intelligence services 5. Experience integrating IP reputation APIs 6. Strong debugging and troubleshooting skills 7. Knowledge of HTTP/HTTPS, JSON, webhooks, and API testing tools (Postman, Insomnia, etc.) 8. Experience with Python, Node.js, or similar backend technologies 9. Familiarity with cloud environments (AWS, Azure, or GCP) To Apply Please include the following in your proposal: - Brief overview of your experience with API integrations. - Examples of projects involving OpenAI, Claude, Azure OpenAI, or other LLM integrations. - Experience integrating URL classification, IP reputation, or cybersecurity APIs. - Your preferred development stack. We are looking for a highly skilled engineer who can quickly identify integration issues, ensure secure API connectivity, and help us deliver a robust, production-ready solution. If you have strong experience with API authentication, AI integrations, and troubleshooting complex systems, we'd love to hear from you.

Looking for an expert developer to build a private, highly secure creative and financial workspace using the Google AI Studio / Gemini 1.5 Pro API. The absolute priority of this project is a 100% complete data migration. You will take a 6-week raw chat log containing precise financial checking/savings ledgers, business blueprints, and long-form biographical story notes, and ingest it flawlessly into a permanent vector database. You will connect this repository to the Gemini API so the system maintains permanent context retention across both a laptop and an Android phone without losing a single digit or syllable. Must deliver a clean, private, password-protected web interface that allows for seamless text dialogue, image uploads (for inventory tracking), and audio processing. Security, privacy, and flawless data retention are non-negotiable.

I’m looking for a developer to build a tool that tracks recruiting prospects, pulling daily updates from different platforms/websites, & filters results based on custom metrics.

We are building a semiconductor manufacturing intelligence platform designed to help engineers rapidly identify yield excursions, investigate root causes, and capture institutional process knowledge. A working foundation already exists, including yield dashboards, lot tracking, process-route visualization, maintenance-event correlation, and investigation timelines. We are now looking for a highly capable developer to extend and refine the system into a production-grade engineering decision-support tool. This is not a basic dashboard project. The goal is to enhance an existing platform into a system that connects manufacturing data, equipment history, and engineering knowledge with lightweight AI-assisted analysis. Key Objectives Help engineers answer questions such as: * Why did yield drop? * What changed before the excursion started? * Which tools or chambers are most likely responsible? * Have we seen a similar issue before? * What corrective actions worked previously? Scope of Work Investigation Workspace * Improve investigation timelines * Correlate process events, SPC/FDC signals, maintenance activity, and yield changes * Enhance interactive debugging workflow Historical Excursion Search * Simple similarity matching using rules or embeddings/API-based methods * Retrieve past investigations and outcomes Engineering Knowledge Layer * Searchable notes, documents, and reports * Store corrective actions and process changes AI-Assisted Summaries (lightweight) * Generate investigation summaries using an LLM API * Suggest possible contributing factors based on available data Ideal Candidate * Strong full-stack or data engineering experience * Comfortable working with existing codebases * Experience with analytics dashboards or industrial systems * Familiarity with APIs, databases, and data modeling * Bonus: exposure to manufacturing or semiconductor data Notes * This is an extension of an existing platform, not a rebuild * Focus is on practical implementation rather than complex architecture * Speed and execution matter more than theoretical design * Potential for ongoing work if collaboration goes well

Seeking a motivated, entry-level Full-Stack Developer to help build an AI-powered dashboard that monitors factory equipment in real-time. This system is designed to catch problems before they become breakdowns and allows managers to ask questions about the machinery in plain English, like having an attentive engineer on call 24/7. This is an excellent opportunity for an emerging developer to gain hands-on experience with modern data acquisition, HMI/SCADA concepts, streaming data pipelines, and artificial intelligence within a manufacturing and aerospace context.

I’m running a real estate investment platform called ToInvested.com. The project is about 90% finished, and most of the code was built with Claude together with another engineer. Now I need a senior engineer to step in, review the full product carefully, test every major workflow, and help verify that everything is working correctly before it goes live. This is not just a “write more code” role. I need someone who can look at the platform like a real product, find hidden bugs, catch weak logic, test edge cases, review the AI-generated code, and tell me honestly what is ready and what still needs fixing. Because this is a real estate investment platform, accuracy and trust matter a lot. Users may rely on property data, investment logic, calculations, and AI-driven insights, so even small issues can create a serious problem later. The ideal person has strong full-stack experience, understands AI-assisted development, and has a good testing mindset. Real estate tech experience would be a big plus, especially with property platforms, investment tools, marketplaces, mortgage systems, or financial workflows. My main goal is simple: I want someone to break the project before real users do. If you’re the kind of engineer who can take a nearly finished product, test it deeply, clean up weak areas, and help make it production-ready, I’d be happy to talk.

I need someone to help me build KPIs, tech leaderboards (individual and company), and automate commission/bonus payouts based on sales data. The ideal candidate will have experience in data analysis and automation, ensuring accurate and timely payouts. Familiarity with tools like C#, D3.js, and Python is preferred. Currently, I manually enter all sales date into a google sheet and copy the pertinent information to another google sheet to calculate the commission/bonus payouts. We are looking to have the information auto pulled from our CRM (using an API key?) to create the sales dashboards, company KPI dashboard, and individual tech sales board with their commission/bonus earned/payouts. Budget is open to discussion