We are looking for an experienced full-stack developer with strong AI-assisted development skills to help us transform our existing payment administration web platform into a modern application. We operate a payment management/admin system and want to accelerate development using AI tools such as Cursor, Claude, ChatGPT, GitHub Copilot, or similar technologies. The goal is to rapidly build, improve, and scale our payment administration platform while maintaining high code quality and security standards.

We’re a product-focused team developing an AI-driven SaaS platform aimed at improving how businesses handle information, workflows, and internal processes. We’re looking for a developer who can build a smart feature that allows users to interact with their data and documents in a more automated and intuitive way. The goal is to reduce manual effort and enable faster, more informed actions through AI. This role involves designing and implementing the core logic behind the feature, connecting AI capabilities into the product, and ensuring everything works smoothly within the existing system. You should be comfortable building end-to-end functionality, working with modern web applications, and integrating AI services into real user-facing features. Experience with AI-powered products, automation tools, or data-driven applications is highly relevant.

ElevenLabs Conversational AI Expert — Long, Multi-Node Voice Agents with Tool Calls Project type: Hourly Experience level: Expert Duration: Short-term engagement with potential for ongoing work About the project We're building voice agents on ElevenLabs Conversational AI (Agents Platform) that run long, complex calls of 20+ nodes in the workflow builder, with multiple tool/function calls along the way. The agent is embedded directly into our app (using the ElevenLabs SDK) rather than the ElevenLabs widget. The agents work, but we're fighting duplicate questions/answers. The agent re-asks questions it already asked, or repeats information it already gave, at different points in the call. We need someone who has actually built and shipped long-running ElevenLabs voice agents (not just simple single-prompt bots) to help us fix the structural setup so calls stay coherent end to end. That covers workflow/node architecture, state handling, prompt design, tool orchestration, and our client-side integration. What you'll do ● Audit our current agent: workflow node structure, system/node prompts, tool definitions, and conversation flow. ● Audit our client-side integration (the ElevenLabs SDK embedded in our app): session/connection handling, event handling, client tools, and how local app state stays in sync with the conversation. Reconnects, double-fired events, or repeated client-tool calls can also cause re-asks. ● Diagnose the root causes of the duplicate question/answer behavior. Possible culprits include context/state not being tracked across nodes, overlapping node responsibilities, prompt ambiguity, retrieval/knowledge-base issues, or client-side state/event problems. ● Redesign the node graph and transitions so each node has a clear, non-overlapping job and the conversation can't loop or re-ask. ● Improve state/variable management across nodes: dynamic variables, captured data, and how it's passed forward so the agent "remembers" within a call. ● Tighten tool/function calling: when tools fire, how results are handled, error/timeout handling, and avoiding redundant calls. ● Address context-window and long-call degradation, plus turn-taking behavior that causes drift. ● Recommend the right structural patterns for flows this long (single agent vs. multi-agent/agent transfer, sub-agents, branching). ● Document the fixes and the patterns so our team can maintain and extend the setup. You're a strong fit if you have ● Demonstrable hands-on experience with ElevenLabs Conversational AI / Agents Platform. Please reference specific agents or projects you've built. ● Experience with the workflow/node builder for branching, multi-step calls, not just a single system prompt. ● Experience embedding ElevenLabs in a custom app via the SDK (React/JS, WebRTC/WebSocket), not just the drop-in widget. ● Solid grasp of tool/function calling (client tools and server tools/webhooks), including error handling. ● Strong prompt engineering for voice, plus understanding of LLM context windows, state, and conversation memory. ● Experience debugging long conversations for looping and repetition, including intermittent, hard-to-reproduce cases. ● Bonus: knowledge base / RAG, dynamic variables, multi-agent transfer, post-call analysis, and the ElevenLabs API/SDK. To apply, please include 1. A short description of a long, multi-node ElevenLabs agent you built: how many nodes, what tools, and what it did. 2. How you'd approach diagnosing duplicate question/answer issues in a 20+ node flow (a quick paragraph, since we want to see how you think). 3. Your availability and rate. Applications that just say "I'm an AI expert" without specific ElevenLabs experience will be skipped. We're looking for someone who has lived in this platform.

I am looking for an experienced ASR engineer to build a production-ready speech-to-text system for a low-resource language. I already have approximately 3,000 prepared audio segments, totaling about 10 hours of audio, with clean and consistent transcripts ready for immediate use. Data preparation and segmentation are already handled. The initial 10 hours of audio will serve as the first milestone. After that, the engineer will be expected to continue training and improving the model with additional data until the system reaches a target WER of 10% or below. Your responsibility will focus on: Fine-tuning a Whisper-based model for high transcription accuracy Optimizing word error rate (WER) over time Providing inline/embedded start timestamps per phrase Building an efficient inference pipeline for both real-time and batch transcription Structuring evaluation and improvement workflows Preparing the system for deployment and integration into a web platform Providing clear documentation and guidance so I can independently continue training and improving the model over time without ongoing engineer involvement The goal is to reach strong accuracy at launch, with a clear process for continued improvement as more data becomes available. Please describe your experience with Whisper fine-tuning or similar ASR model training in your proposal.

We're hiring a senior AI developer to build and deploy AI solutions for a fintech/credit-union platform. The work spans autonomous banking agents, fraud detection, credit scoring, and bill-pay/invoice automation — at the intersection of LLMs, cloud infrastructure, and financial-domain expertise, with security and compliance built in from the start. This is a long-term, ongoing engagement. What you'll do: AI agents & orchestration - Design, build, and deploy multi-agent systems using Amazon Bedrock Agents, LangChain, and related frameworks - Architect agentic workflows for core banking use cases: credit scoring, fraud detection, bill-pay automation, invoice management - Define agent personas, memory strategies, tool-use patterns, and escalation paths for production banking agents LLM engineering - Fine-tune, prompt-engineer, and evaluate LLMs for financial-domain tasks - Build RAG pipelines over credit-union knowledge bases, policy docs, and member data - Implement guardrails, content filtering, and compliance checks for safe, regulated outputs - Monitor performance, hallucination rates, and latency against SLAs Cloud infrastructure (AWS & Azure) - Architect and manage AI/ML workloads on AWS (Bedrock, SageMaker, Lambda, S3, IAM, VPC) and Azure (OpenAI Service, Azure ML, AKS) - Design secure, cost-optimized environments compliant with NCUA, PCI-DSS, and SOC 2 - Implement infrastructure-as-code with Terraform or AWS CDK DevOps & MLOps - Build and maintain CI/CD pipelines (GitHub Actions, Jenkins, CodePipeline, Azure DevOps) - Containerize services with Docker, orchestrate with Kubernetes (EKS/AKS) - Apply MLOps best practices: model versioning, A/B testing, canary deployments, automated rollback - Stand up observability with logging, tracing, and alerting Python development - Write clean, well-tested Python for AI pipelines, REST APIs, and data workflows - Build FastAPI/Flask microservices exposing agent capabilities to frontend and core banking systems - Integrate with financial data sources, core banking APIs, and third-party fintech services Banking applications - Build credit-scoring models using alternative data and explainable AI (XAI) - Develop real-time fraud detection with behavioral analytics, anomaly detection, and auto-decisioning - Create conversational agents for bill pay, account management, and member self-service - Automate invoice workflows: extraction, classification, approval routing, reconciliation - Partner with compliance/risk to keep AI decisions auditable, fair, and regulatory-compliant What you should have: - 5+ years software engineering; 3+ years in AI/ML or LLM engineering - 2+ years building AI for banking, credit unions, or financial services - Hands-on experience with Amazon Bedrock, LangChain, Python, AWS, and infrastructure-as-code - Working knowledge of NCUA, PCI-DSS, SOC 2, GLBA, and Fair Lending requirements - Bachelor's or Master's in Computer Science, Software Engineering, Data Science, or related field Nice to have: - AWS or Azure AI/ML certifications - Open-source LLM experience (Llama, Mistral, Phi) and self-hosted inference (vLLM, Ollama) - Vector databases (Pinecone, OpenSearch, pgvector) - Graph-based fraud networks and graph ML - AI governance / responsible AI framework experience - Prior work at a credit union, community bank, or fintech lending platform To apply, please share: - Your resume highlighting AI and banking project experience - A brief note on your most impactful AI agent or LLM project in a financial-services context - Links to GitHub, portfolio, or published papers (optional but encouraged)

We’re hiring an extraordinary developer to own and grow our Base44 apps and sales products. around the future of AI discovery 1. Future of AI Discovery Core Demo – https://pull-discovery-core.base44.app/ You’ll evolve https://pull-discovery-core.base44.app/ into a beautiful, fluid, high‑performance, full-functional future of AI discovery demo following our advanced and sophisticated technical blueprint Integrate and orchestrate AI models incorporating LLM's, Search and World Models into a seamless experience with no visible seams between UX and intelligence. Own front‑end performance, responsiveness, and micro‑interactions—animations, transitions, and state changes should feel intentional and “alive,” not bolted on. Implement robust logging and analytics to understand how users explore, where they get stuck, and how the discovery engine can adapt dynamically. 2. Book Sales Engine – Six‑Channel Publishing System The second current Base44 project is a system that operationalizes our comprehensive sales plan across six channels. SEE THE COMPREHENSIVE BOOKSALES PLAN ATTACHMENT UNDERNEATH THIS POSTING You will: Translate a detailed multi‑channel publishing strategy (KDP optimization, physical bookstores via IngramSpark, other digital platforms, libraries, bulk institutional sales, and authority‑engine content marketing) into concrete workflows, tools, and dashboards. Build internal interfaces and automations to: Track metadata, pricing, and promotions across Amazon KDP and other platforms. Monitor campaigns across TikTok, Meta, LinkedIn, YouTube, newsletters, and partnerships. Surface KPIs like BSR, review velocity, ad spend, email growth, library adoptions, and bulk orders in a single, coherent view. Design light internal UIs that make it easy for non‑technical team members to update copy, add titles, trigger campaigns, and view performance without breaking anything. Implement robust, testable integrations between Base44, external APIs, and data sources to keep everything in sync as we scale from 8 to 22+ titles and beyond. Who You Are We’re not looking for a generic “full‑stack dev.” We’re looking for an unusual combination of visionary and doer: Creative technologist mindset – You think in systems and interfaces at the same time. You care deeply about how a product feels as well as how it works. Obsessed with execution – You’re disciplined, structured, and relentless about shipping. You break ambiguity into sprints, reduce complexity into tickets, and never let projects stall. Proactive owner – You don’t wait for instructions. You propose better ways to do things, flag risks early, and bring options—not problems—to every conversation. Strong product sense – You can balance ideal UX with realistic constraints and understand when to ship v1 vs. when to invest in polish. Comfortable with complexity – Multi‑channel distribution, layered data flows, and evolving requirements don’t scare you; they energize you. Ideal Skills & Experience You don’t need all of these, but you should recognize yourself in most: 5+ years building production web applications, ideally with a strong front‑end/UI focus. Deep experience with modern web stacks (React/Vue/Svelte or similar) and TypeScript, plus comfort with Node or comparable back‑end runtimes. Strong visual/UI instincts: experience collaborating with designers or owning design yourself for data‑rich interfaces and dashboards. Experience integrating AI/LLM APIs and retrieval systems into real products (RAG flows, multi‑step tool use, chat‑like interfaces, recommendation engines). Experience with analytics and experimentation: event tracking, funnel analysis, A/B testing. Familiarity with publishing, ecommerce, or multi‑channel marketing systems is a plus (KDP, IngramSpark, email platforms, ad platforms, analytics). Prior work in environments like Base44 or other low‑code/agentic platforms is a strong plus, but not required if you learn fast.

We are a small software development team actively using Claude and GitHub Copilot for development on an ASP.NET and Azure technology stack. We’re looking for an experienced AI coach/consultant who can review how our team currently uses AI, identify opportunities for improvement, and help us work more effectively with Claude Code, agents, and AI-assisted development workflows. What we're looking for: Experience implementing and scaling AI-assisted development practices within agile software teams. Deep hands-on experience with Claude Code, agents, and agent-driven workflows. Experience designing and configuring agents for development, QA, testing, documentation, and other engineering processes. Ability to conduct team workshops, coaching sessions, and practical reviews of our current workflows. Strong understanding of software engineering best practices, not just AI tooling. Bonus skills: Software architecture and platform engineering experience. Experience setting up and optimizing MCPs (Model Context Protocol), tools, integrations, and custom Claude configurations. Knowledge of AI workflows beyond development, including QA, support, project management, and internal operations. The engagement would likely include a mix of: Reviewing our current processes and tooling One-on-one discussions with team members Team coaching and training sessions Recommendations for improving productivity, quality, and collaboration using AI Please include examples of teams you have coached, AI development workflows you have implemented, and your experience with Claude agents and MCP-based tooling

Seeking an experienced freelancer to scope an AI project focused on generating building floor plans. The ideal candidate will have a strong background in architectural design and AI technologies, with the ability to assess project requirements and provide detailed proposals.

I receive purchase requests, purchase orders, receivers, blankets and vendor requests in my email. I currently input this data into my excel checkbook. I would like an AI Agent do this work for me. I would also like for it to calculate total amounts for each GL code as well. So I just need the AI Agent created.

We are seeking an experienced AI Data Mining and Lead Generation Team to help us build and scale two distinct sales verticals through advanced AI prospecting, automation, data enrichment, and lead qualification. This is not a simple list-building project. We are looking for professionals who understand how to leverage modern AI tools, automation platforms, CRM systems, and data intelligence to identify qualified prospects, verify contact information, and create systems that consistently generate meetings and sales opportunities. Our goal is simple: Vertical #1: Custom Apparel Sales Through The Tee Shirt Store, we provide custom apparel solutions for: Schools Sports teams Churches Nonprofits Small businesses Corporate organizations Fundraising campaigns Events and conferences We need qualified buyers actively looking for custom apparel, screen printing, embroidery, promotional products, and branded merchandise. Vertical #2: Youth Entrepreneurship Education Through Education With A Profit, we deliver entrepreneurship education programs designed to help youth develop business, leadership, financial literacy, and entrepreneurial skills. We need introductions and meetings with: Youth organizations Community organizations Workforce development programs Nonprofits serving youth Corporate community outreach departments Foundations and grant-funded programs What We Need You To Build The ideal candidate or team will: AI Lead Generation Systems Develop AI-powered lead sourcing processes Build automated prospect identification workflows Create lead scoring systems Implement contact verification procedures Use data enrichment tools to improve lead quality Reduce manual prospecting through automation Qualified Lead Acquisition For Custom Apparel: Identify decision-makers responsible for apparel purchasing Verify contact information Capture buying signals Prioritize high-intent prospects For Entrepreneurship Education: Identify educational leaders and program decision-makers Locate grant-funded and budget-approved opportunities Identify organizations actively seeking youth programs Build targeted outreach databases Automation & CRM Integration CRM setup and optimization Automated lead routing Follow-up automation Meeting scheduling integration Reporting dashboards Pipeline tracking AI Outreach Optimization Email personalization systems Prospect segmentation Multi-channel outreach workflows Lead nurturing sequences Appointment-setting automation