We are academic researchers studying how software engineering work is organized and how it has changed over time, particularly in response to generative AI tools. We are looking to interview several software engineers about their professional experience. Any information you provide will be used as part of academic research outputs, and will not be attributed to your name or your company. Compensation: $30 fixed rate (i.e., $60/hour for a 30-minute Zoom interview) --- Who we're looking for - Currently working or recently worked (within the past 6 months) as a full-time software engineer at a company. Since we are interested in learning about your usage of AI within a software engineering team, we cannot accept individuals who do not have this form of recent experience. - Any level of seniority welcome What the interview covers - How engineering work is organized at your company (or past company) - How workflows have changed in response to AI - Your experience with tools and workflows Output - The qualitative interviews will be used to inform research hypotheses for the academic project - With permission, we would also include the information directly in the qualitative section of an academic paper, covering interviews with 30+ tech workers --- e.g., as paraphrased or anonymized quotes --- To apply, please briefly describe: 1. Your experience in software engineering roles, over the past 4 years -- company names, job titles held, and dates of positions held 2. Your availability for a 30-minute video call interview Thank you!

Looking for an HyperAgent Expert. You should have setup several AI Agents for clients and be familiar with several of the following: - HyperAgent - LangGraph - CrewAI - AutoGen - Make.com - n8n - MCP - API integrations - CRM automation Looking to hire immediately.

We are building a custom Drone Operating System for advanced UAVs and lighter-than-air platforms. The system requires robust flight control integration, real-time sensor fusion, edge AI capabilities, and reliable connectivity (including satellite and radio links).We need an experienced full-stack AI developer to: Design and implement core Drone OS modules (flight stack interfaces, sensor fusion, mission management) Integrate edge AI models for perception, decision-making, and optional voice interaction Build reliable communication layers (MAVLink/ROS 2, Starlink, radio) Create clean APIs, logging, and ground-station interfaces Ensure the system is modular, testable, and suitable for real-world flight testing Required skills: Strong experience with PX4, ArduPilot, or similar flight stacks + ROS 2 Python and C++ (production-quality code) Edge AI / onboard inference (NVIDIA Jetson or equivalent) Real-time systems and sensor fusion Full-stack capability (backend services + basic frontend/ground control interfaces) Nice to have: Experience with GNSS-denied navigation, anti-jam techniques, or multi-sensor fusion Prior work on UAV, robotics, or autonomous systems Familiarity with satellite connectivity or long-range radio links This is a hands-on development role with direct impact on a real flying system. We value clean architecture, reliable code, and clear communication. Please share relevant past projects (especially any drone, robotics, or edge AI work) and your availability. Looking forward to working with a strong technical partner.

We are seeking an AI developer to create systems for med spas and similar businesses. The role involves developing missed call recovery and AI follow-up systems to enhance customer engagement and response times. The ideal candidate will have experience in AI technologies and a strong understanding of customer interaction systems. We're going to have ongoing projects and would like to pay a flat-fee on a per project basis. Please respond with more details about your experiences and examples of similar projects you've implemented.

We're a US-based software consulting firm looking for a skilled full-stack engineer to join us long-term. This starts as an hourly engagement with a paid trial project, and converts to full-time for the right person. We have consistent client work and need someone reliable who ships fast and communicates well. This is not a vibe-coding role. We want a real engineer — strong fundamentals, solid architecture instincts, clean production code — who uses AI tools (Claude Code, Codex, Cursor) to move 5–10x faster. AI is your force multiplier, not your crutch. If you lean on AI to paper over gaps in your actual engineering ability, this isn't the fit. If you're a genuinely strong developer who has mastered AI-augmented workflows to ship more and better, keep reading. What you'll do: Build and ship full-stack web apps, APIs, integrations, and backend systems for our clients Own projects end-to-end: architecture, implementation, testing, deployment Juggle multiple client projects at once (AI leverage makes this realistic) Communicate clearly and proactively — updates, blockers, timelines Requirements: US-based. This is a hard requirement — please do not apply if you're not based in the United States. Native or fluent English, excellent written and verbal communication 4+ years professional software engineering experience Strong across a modern stack (examples: TypeScript/React/Next.js, Node, Python, Postgres, cloud — AWS/GCP) Genuine architecture and system-design skills, not just feature-wiring Fluent with AI-assisted development (Claude Code, Codex, Cursor) and able to speak to how you use it to ship faster without sacrificing quality Self-directed, reliable, and able to own work without hand-holding Nice to have: Experience across multiple client projects or agency/consulting background AI/ML integration experience (LLM APIs, RAG, agentic workflows) DevOps / secure cloud deployment experience How we work: Start: paid hourly trial on a real project so we can both evaluate fit Then: ongoing hourly, scaling toward full-time (40 hrs/week) Long-term, stable relationship — we're building a team, not filling a one-off gig To apply, include: A short note on your engineering background and your strongest projects How you specifically use AI tools in your workflow — be concrete, tell us your setup and where it makes you faster Links to work (GitHub, portfolio, shipped products) Your hourly rate Please start your application with the word "SHIPPED" so we know you read this in full. Applications without it will be ignored.

Summary NobleProg is seeking an experienced AI Trainer to deliver a live, instructor-led workshop for a corporate client in the Honolulu, Hawaii area. This four-hour workshop is designed primarily for the client’s Quality team, with invited participants from Pharmaceutical Sciences, Innovation Labs, and Clinical. The trainer should have strong expertise in enterprise generative AI and practical experience applying AI within pharmaceutical and life sciences organizations. The objective is to help AI Champions and business users identify meaningful opportunities to expand the responsible use of AI across regulated business functions. Engagement Details Location: Honolulu, Hawaii Duration: 4-hour workshop (9:00 AM – 1:00 PM) Audience: Quality team, with invited participants from Pharmaceutical Sciences, Innovation Labs, and Clinical Participants: Approximately 25 Format: Onsite + Remote Participants Rate: $750 Course Scope This interactive workshop introduces practical applications of generative AI across pharmaceutical quality, product development, clinical, and innovation functions. Participants will learn prompt engineering techniques, responsible AI practices, and practical business use cases while working within Microsoft Copilot and Enterprise ChatGPT. All exercises will use fictional or sanitized examples appropriate for a regulated pharmaceutical environment. NobleProg SOP: https://share.synthesia.io/a0788c6e-56d5-4da8-92c6-0d5c03ad6d52 Key Topics Include * Practical applications of generative AI in pharmaceutical product development, including research support, summarizing background information, comparing options, and planning early-stage activities * AI-assisted clinical patient screening using fictional scenarios to structure eligibility criteria, summarize screening considerations, and develop review checklists while maintaining human oversight * AI for quality and compliance workflows, including drafting review checklists, summarizing procedures, identifying documentation gaps, and improving internal quality documentation * Cross-department AI use cases supporting Pharmaceutical Sciences, Innovation Labs, Clinical, and Quality teams through meeting preparation, project planning, reporting, knowledge management, and process improvement * Prompt engineering techniques for producing reliable, structured, and business-ready outputs * Responsible AI practices, data privacy, governance, and compliance considerations in pharmaceutical environments * Strategies for AI Champions to identify, evaluate, and promote practical AI opportunities across their teams Trainer Responsibilities * Deliver an engaging instructor-led workshop for approximately 25 participants * Facilitate hands-on exercises using Microsoft Copilot and Enterprise ChatGPT * Demonstrate practical AI use cases relevant to pharmaceutical quality, clinical, research, and innovation teams * Lead discussions on responsible AI adoption, governance, and human oversight * Coach participants on prompt development, prompt refinement, and evaluating AI-generated outputs * Encourage participants to identify AI opportunities within their own business functions * Provide training materials (trainer retains ownership of content) Required Qualifications * Strong hands-on experience using enterprise generative AI platforms, particularly Microsoft Copilot and ChatGPT * Demonstrated experience applying AI within pharmaceutical, biotechnology, healthcare, or life sciences organizations * Strong understanding of AI applications supporting Quality, Pharmaceutical Sciences, Clinical, Innovation, Regulatory, Manufacturing, or related pharmaceutical functions * Experience delivering instructor-led corporate AI workshops or executive education * Excellent presentation and facilitation skills with mixed-experience audiences How to Apply Please include: * A brief overview of your AI and pharmaceutical or life sciences experience * Your experience delivering corporate AI workshops or executive education * Examples of AI use cases you have implemented or taught for Quality, Clinical, Pharmaceutical Sciences, or Innovation teams * Confirmation of your availability to deliver onsite training near Honolulu, Hawaii on Tuesday, September 8 * Any relevant presentations, publications, or previous AI training materials

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.

I’m looking to build a simple AI Practice Lab that allows learners in our professional development courses to have realistic, text-based or voice conversations with simulated students. After each conversation, the AI would score the learner against a custom rubric and provide personalized feedback, with the experience ideally embedded within or seamlessly connected to Thinkific. We’d also need an easy way to create and edit scenarios, student personas, and rubrics ourselves without coding.

We run a production backend for an AI-powered platform that helps users identify scams over voice and text in real time. It is live and functional today, built by our current lead backend engineer. We are hiring a second senior engineer to work alongside the existing codebase: validating the architecture, closing out remaining features, and adding capacity so the project is not dependent on a single developer. Stack: Python, FastAPI, Firebase, Firestore, Google Cloud Platform, Cloud Run, Twilio Voice and SMS, Stripe, LLM API integration (Anthropic, OpenAI, or similar), speech to text / text to speech pipelines. What you will do: Review and validate the existing backend architecture and Firestore data model Help close out remaining features ahead of a pilot launch Improve reliability, security, and production readiness where needed Work as ongoing backend capacity going forward You should have: Senior-level Python and FastAPI experience in production Real production experience with Firebase, Firestore, and Cloud Run Experience inheriting and working within an existing codebase, not just building from scratch Twilio voice or SMS experience strongly preferred Experience with Stripe and LLM API integrations a plus Clear written English and some overlap with US Eastern Time To apply, answer this: Describe a time you inherited another developer's production codebase. What was your approach to understanding it, identifying issues, and improving it without disrupting the existing system? Please skip generic template proposals. Repository access and full technical scope provided after a signed NDA.

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.