Conversational AI / LLM Consultant We are looking for a Conversational AI and LLM specialist to support the strategy, design, development, testing, and improvement of AI-powered chatbot and voice automation solutions across multiple business groups. Responsibilities: Help identify, evaluate, and prioritize Conversational AI and LLM use cases across defined business units. Advise on best practices for Conversational AI strategy, LLM architecture, prompt design, orchestration, retrieval, integrations, and development. Recommend improvements across AWS services, Amazon Lex integrations, LLM workflows, and supporting AI infrastructure. Collaborate with the development team on chatbot, voice bot, Lex, and LLM-based implementations and configurations. Conduct QA testing to validate Conversational AI functionality, accuracy, performance, reliability, and user experience. Support the development of solution frameworks, automation workflows, dashboards, application management tools, and fulfillment processes. Assist in designing and extending multilingual Conversational AI solutions in English and Spanish. Support multiple lines of business, call flows, customer journeys, and AI-assisted workflows. Ideal Candidate: Experience with Conversational AI, LLMs, and chatbot or voice automation systems. Familiarity with Amazon Lex and AWS AI services is helpful, but broader LLM architecture experience is equally important. Strong understanding of prompt engineering, AI orchestration, integrations, QA testing, and production AI workflows. Ability to translate business requirements into practical AI-driven solutions. Experience with multilingual conversational design, especially English and Spanish, is a plus.

AI Integration & Automation Specialist (OpenAI / ChatGPT): We’re an advertising agency looking for an experienced AI specialist to help build an AI-powered business infrastructure. Your role will be to integrate ChatGPT/OpenAI with the software we use every day, automate workflows, and help us identify opportunities to improve efficiency across the business. Responsibilities: * Integrate OpenAI with our existing software stack * Build custom workflows using APIs and automation platforms * Connect tools such as Microsoft 365, Outlook, HubSpot, Wrike, QuickBooks, WordPress, and other business applications * Develop AI assistants for operations, sales, project management, marketing, reporting, and customer service * Recommend scalable AI solutions and best practices * Document all work for future maintenance Requirements: * Strong experience with OpenAI APIs * Experience with APIs, MCP, Zapier, Make.com, n8n, or similar automation platforms * Strong understanding of business process automation * Ability to communicate with both technical and non-technical teams * Excellent English

Looking to build digital workflows to cover common tasks, such as responding to leasing inquiries, ingesting and analyzing bills from emails, proactively managing maintenance requests with self-service type questions, etc. Need someone who is proficient with building with LLMs, harnesses, and can demonstrate that they have build reliably operating systems Goal would be to reliably measure efficacy on each task, such that we could promote away from HITL into auto-act capabilities when confidence is sufficiently high Opportunity for much more work if can prove excellence here.

AI Engineer (RAG & Agentic Workflows). *LLM RESPONSES AUTOMATICALLY AVOIDED* We have already launched a production generative AI product that utilizes a custom Retrieval-Augmented Generation (RAG) architecture. We are now expanding the platform to include CRM intelligence, workflow automation, and agentic AI capabilities. This is **not** a prompt engineering role. Seeking an engineer with deep experience building and deploying production AI systems that combine LLMs with multiple structured and unstructured data sources. You should be comfortable walking into an existing, complex codebase, understanding the current architecture, and improving it. Existing AI Architecture Our current AI architecture consists of: * OpenAI embeddings * Embeddings stored in MongoDB * MongoDB Atlas Vector Search for retrieval * Retrieval from both structured SQL data and unstructured document collections * Existing tool/function-calling architecture **Please do not apply if you have not previously built or maintained production RAG systems using embeddings and vector search.** Experience specifically with **OpenAI embeddings and MongoDB Atlas Vector Search** is highly preferred. CRM Intelligence Layer We are currently building a CRM platform and need the AI to reason over CRM records, including the other records are RAG currently retrieves. You will be responsible for designing and implementing the AI integration layer that enables the LLM to intelligently retrieve and reason over CRM data. This work includes: * Designing AI tools/functions that expose CRM data to the LLM. * Implementing backend tool handlers that retrieve CRM records. * Defining tool schemas and instructions so the AI knows when and how to retrieve CRM information. * Building secure retrieval mechanisms that enforce strict user and organization-level access controls. * Transforming raw CRM records into structured, AI-ready context. The AI will need to reason across: * CRM contacts and organizations * client profiles * Deals and opportunities * Projects * Tasks and reminders * Notes * Email history * SMS and WhatsApp communications * Call transcripts * Meeting summaries * Documents and contracts * Workflow history Agentic AI & Workflow Automation * Build proactive AI agents that generate alerts, recommendations, follow-ups, reports, and suggested next actions. * Design systems capable of reasoning across both structured and unstructured data sources. * Architect and implement multi-step and multi-agent workflows. * Develop workflow intelligence that assists users in completing real-world business tasks. Required Experience * Demonstrated experience building and deploying production AI systems used by real customers. * Experience working with embeddings, vector databases, and retrieval pipelines. * Experience implementing LLM tool/function-calling architectures. * Experience integrating AI systems with business systems such as CRMs, ERPs, or other operational databases. * Experience combining structured and unstructured data within AI applications. * Strong backend engineering and systems architecture experience. * Demonstrated ability to quickly understand and improve existing codebases. * Ability to independently own and deliver complex technical initiatives. Strongly Preferred * Experience with OpenAI embeddings. * Experience with MongoDB Atlas Vector Search. * Experience building agentic AI systems and workflow automation. * Experience designing long-term memory architectures. * Experience building multi-tenant SaaS applications with strict authorization requirements. * Experience implementing evaluation and monitoring pipelines for production AI systems. What We Value * High accountability and ownership. * Strong communication skills. * Product thinking and user empathy. * Ability to understand user workflows before writing code. * Pragmatism and sound engineering judgment. PLEASE DO NOT WASTE OUR TIME IF YOU NOT MEET THE REQUIREMENTS 

Build Private AI Chat Tool Using Anthropic Claude API — Law Firm Budget: $1,500–$3,000 fixed price Description: I'm a managing attorney at a small law firm in New York. I need a private, secure web application that gives my 4-person team access to Claude AI for document summarization and legal drafting — using the Anthropic API with Zero Data Retention so no client data is stored externally. What I need built: Browser-based chat interface (works like claude.ai but private) Per-user login (4 users) PDF upload — user uploads a document, selects a task (summarize medical records, extract key facts, etc.), Claude returns structured output Conversation history saved to our own encrypted database, tagged by case number Admin view where I can see all conversations across all users Hosted on a private server with HTTPS/SSL No data logged or stored outside our own database Clean, simple UI — non-technical staff must be able to use it Tech requirements: Anthropic Messages API (claude-sonnet-4-6) Zero Data Retention configured on the API account PostgreSQL or similar database for history Per-user authentication (JWT or similar) PDF text extraction before sending to API Encrypted database at rest You must have: Prior experience with the Anthropic Claude API specifically Experience building secure web apps with user auth and databases Portfolio or examples of similar builds Please answer this in your proposal: have you configured Zero Data Retention on the Anthropic API before? This is a fixed-price project. I own all code upon final payment.

We're a growing service company looking for an experienced developer to build a Slack bot that answers employee questions about our HR policies, SOPs, and internal documentation. Team members will tag the bot in a channel, ask a question in plain language, and receive a conversational, accurate answer grounded in our documented materials. **This is a build + teach engagement.** I have no coding background, and a core requirement of this project is that you walk me through your decisions and architecture as you build, so I can understand, maintain, and eventually extend the system myself. If you're a strong developer but don't enjoy explaining your work, this isn't the right fit. ## What You'll Build A production-ready Slack bot with the following architecture: - **Slack integration** using Slack's Bolt framework (Python or Node.js — your recommendation welcome) - **Retrieval-Augmented Generation (RAG)** pipeline: questions are matched against our documentation via semantic search, and relevant context is passed to an LLM for a conversational answer - **Vector database** (Pinecone, Weaviate, or a comparable option you can justify) storing embeddings of our policies, SOPs, and transcripts - **OpenAI API** integration for embeddings and chat completions - **Document ingestion pipeline** that can handle multiple source formats: Word docs, PDFs, spreadsheets, and plain-text transcripts (e.g., exported Loom video transcripts) - **Source citations** in bot answers, so users can see which policy or document the answer came from - Deployment to a cloud environment (AWS, Heroku, Railway, or similar) with clear instructions for how it runs and how to restart or update it ## Technical Requirements You should have demonstrable experience with: - Slack app development (Bolt framework, event subscriptions, OAuth/permissions setup) - OpenAI's API (chat completions and embeddings) - RAG architecture and vector databases (Pinecone, Weaviate, Qdrant, pgvector, or similar) - Python or Node.js backend development - Cloud deployment and basic DevOps (environment variables, API key security, uptime) **In your proposal, please link to or describe at least one similar project you've built** — ideally a Slack bot, a RAG system, or an LLM-powered internal tool. ## Deliverables 1. A working Slack bot deployed to production and connected to our Slack workspace 2. Document ingestion process (with instructions or a simple tool for me to add new documents myself as our documentation grows) 3. Full source code in a repository I own, with clear comments 4. **Written documentation** covering: system architecture, how each component connects, how to add/update documents, how to update API keys, and common troubleshooting steps 5. **Teaching sessions**: recorded screen-share walkthroughs (or live calls) at each major milestone explaining what was built and why — I estimate 3–5 sessions of 30–60 minutes 6. A handoff session at the end where we test the bot together and review maintenance procedures ## Communication & Working Style - Regular progress updates (at minimum, 2x per week) - Willingness to explain decisions in plain English, not just technical jargon - Patience with beginner questions — teaching is part of the paid scope, not a favor - Fluent written and spoken English - Availability for scheduled video calls (please note your time zone in your proposal) ## Scope Notes - Initial document set is modest, but the system should be designed to scale as our documentation library grows significantly - Future phases may include: automatic transcript ingestion from Loom, additional Slack channels/workflows, and analytics on what questions get asked — mention if you have experience with any of these - I will provide: Slack workspace admin access, OpenAI API account, and all documentation to be ingested ## How to Apply In your proposal, please include: 1. A brief description of a similar project you've built (links or screenshots appreciated) 2. Your recommended tech stack for this project and a one-paragraph explanation of why 3. Your approach to the teaching/documentation component 4. Estimated timeline and total cost (fixed price preferred; open to milestone-based payment) 5. Your time zone and general availability Proposals that are clearly personalized and address the teaching component will be prioritized. Generic copy-paste proposals will be declined.

We have an existing application that includes several AI-powered features and integrations. Some features are currently not functioning as expected, and we are looking for an experienced developer to review the codebase, identify the root causes, and implement reliable fixes. The ideal candidate should be comfortable working with AI/LLM integrations, debugging complex systems, and improving existing functionality without disrupting the overall application.

We are a small AI consulting practice that helps financial services firms put AI to work inside their business. Our clients are owner-led firms like accountants, business appraisers, financial advisors, and insurance agents. We do not sell one-off scripts or disposable projects. We build practical AI systems that take real work off these firms' plates, delivered through ongoing monthly work. Demand is growing and the bottleneck is delivery. We are looking for one delivery partner to own that side of the work with us. How it works: we handle marketing, sales, and the paid advisory session that starts each client. Once a client moves to ongoing work, you take the lead on delivery. You build the systems against the priorities we set each month, and you run the weekly client meeting as their main point of contact. We stay in for support, to translate the client's business context, and to own the relationship at the top, but week to week the client works with you. What you would own: -Building AI and agentic systems for clients -Running the weekly client meeting and being the client's day-to-day contact -Taking each engagement from kickoff through delivery on the month's agreed hours, to a standard we can stand behind Compensation is $100/hour for your hours, which include both build time and client meetings. Straightforward and paid against tracked hours. As our client book grows, so do the hours available. Who we are looking for: -Genuinely fluent building real systems with modern AI tools. -Not just familiar with them. You should be comfortable architecting and shipping working systems for non-technical business owners. -Client-ready. You can run a working session, explain technical things plainly to a non-technical owner, and hold a client relationship week to week. -Native or fluent English. You are in front of clients every week, so clear, natural communication is non-negotiable. -Strong general technical judgment. The specific stack matters less than the ability to find the right solution and build it. -Reliable. We scope the work and stand behind it, so we need to count on what you deliver and how you handle the client. Who this is not for: anyone looking to own sales or pricing, anyone who only wants to build quietly and never talk to a client, and anyone new to this work hoping to learn on the job. To apply, tell us briefly: the most relevant AI system you have built and what it did for the business, how comfortable you are leading client calls, and how you approach building these systems. Start your reply with the word "Agentic" so we know you read this in full. Applications without it will not be reviewed. We will move quickly with the right person.

Project Overview We are building an AI-powered voice receptionist agent for a dental practice client. The agent will handle inbound calls 24/7 — booking, rescheduling, and canceling appointments, answering FAQs, and escalating complex situations to a human. The voice layer is built in Retell.ai and the orchestration/automation flows run in n8n, with integration into a dental practice management systems. This is a hands-on build role, not consulting. You will design, configure, and iterate the agent working directly with our founding team. What You'll Build: Conversational voice flows for new and returning patients (booking, rescheduling, cancellations, FAQs, insurance questions, urgent/emergency triage) Clean escalation paths to human staff when the agent can't handle the call n8n workflows connecting the voice agent to the practice management API for real-time schedule reads/writes HIPAA-conscious configurations and tool choices throughout the stack Performance tracking and iterative prompt/flow improvements based on real call feedback Seeking an Expert Who: You've built multiple production voice agents, ideally in healthcare or dental, and can own the full stack from architecture to delivery. You think critically about latency, barge-in behavior, edge cases, and HIPAA compliance — not just happy-path flows. Requirements: Deep expertise in Retell.ai — prompt tuning, latency optimization, interruption/barge-in handling, LLM selection, and cost modeling Advanced n8n automation — complex branching logic, dynamic data handling, external API integrations, and error recovery Experience with dental or healthcare organizations — you understand how practices operate, what front desks actually deal with, and how to translate that into agent logic HIPAA awareness — you know which tools and configurations are appropriate for PHI workflows Track record of full-cycle delivery: scoping → build → pilot → iteration Nice to have: Dentrix Ascend integration, NexHealth, prior AI receptionist or appointment-booking agent for a clinic/practice. 📋 To Apply, Please Answer Have you built a production voice agent with Retell.ai? If yes, briefly describe it. What's your approach to managing Retell.ai per-minute costs on an inbound call agent? Have you worked with dental or healthcare clients before? What was the workflow? Paste a relevant n8n workflow screenshot or describe your most complex flow.

Job Title - AI Native Developer Duration - 90 Days Initial Engagement (20 Hours/week) Work Mode- Onsite Work Location- Plano, Tx Position Summary: We are hiring a Senior AI Native Developer to join an active client engagement in the restaurant technology space. This is a hands-on, on-site role with a dual mandate: driving development execution as a Senior Engineer and acting as a client-embedded technical liaison — a Product Owner / Technical Lead hybrid — working alongside the client's CTO, stakeholders, and ISHIR's India-based development team. This role suits someone who thrives in ambiguity, translates business requirements into shipped code, and is equally comfortable presenting to executive stakeholders and writing production-grade AI features in the same week. WHAT YOU'LL DO Client Delivery & On-site Presence Serve as the primary on-site technical SPOC for the client engagement — attend stand-ups, sprint reviews, and stakeholder sessions Represent ISHIR's delivery team with clarity and professionalism; communicate progress, risks, and decisions to CTO and CFO-level stakeholders Facilitate product discovery, requirements refinement, and architecture review sessions on-site Own the client relationship day-to-day, proactively flagging issues before they escalate AI-Native Development Design and build AI-powered product features using LLMs, RAG pipelines, and agentic architectures Integrate AI capabilities — OpenAI, Anthropic Claude, Azure OpenAI — into production web and API systems Write clean, testable, production-grade code across the full stack (frontend through backend through data layer) Own feature delivery end-to-end: from acceptance criteria through deployment and post-go-live monitoring POD Coordination Collaborate daily with ISHIR's India-based developers and QA across time zones via Azure DevOps, Slack, and video standups Translate client decisions and feedback into clear development tasks and backlog items for the offshore team Review pull requests and maintain code quality standards across a distributed team Flag scope changes, technical blockers, and delivery risks to the Program Manager proactively WHAT WE'RE LOOKING FOR Must-Have 8+ years of hands-on software engineering experience, with at least 2 years building AI/ML or LLM-integrated products Proven ability to work directly with clients — comfortable in executive meetings and boardroom-level presentations Strong full-stack background: Python or Node.js backend; React or equivalent frontend Hands-on experience with LLM APIs (OpenAI, Anthropic, Azure OpenAI) — prompt engineering, RAG, tool/function calling Solid agile delivery experience: sprint planning, backlog grooming, coordinating distributed engineering teams US-based with ability to travel on-site to client locations (primarily Dallas, TX area) Exceptional written and verbal communication — you write as clearly as you code Strong Advantages Prior experience in a client-facing technical lead, senior PO, or solutions architect capacity at a services or consulting firm Familiarity with restaurant technology, hospitality SaaS, or B2B platform products Experience with Azure DevOps, CI/CD pipelines, and cloud-native deployments (Azure preferred) Hands-on with agentic AI frameworks — LangChain, LangGraph, AutoGen, or similar Anthropic Claude Certified Architect (CCA-F) or equivalent AI platform certification ABOUT ISHIR ISHIR is a digital innovation and enterprise AI services provider. We work with startups and enterprises to shape the future through accelerated innovation, deep technical expertise, access to global digital talent and a passion for complex problem-solving. With our help, our clients overcome their most difficult digital challenges leveraging AI. We are not just consultants, we are partners in our clients’ success, assisting them with re(gaining) competitive edge by identifying opportunities for differentiation, industry disruption, scalable innovation, and go-to-market strategies that deliver successful outcomes. At ISHIR, we help bold businesses accelerate innovation through Talent, Speed-to-Market, and AI. We help make an impact by solving real problems using innovation, improved customer experiences and the right technologies. As an ISHIR employee, you will get the advanced training you need to be successful, and the opportunity to apply it. You must be passionate about technology, crave responsibility, and be eager to apply your knowledge to real business solutions for our startup and enterprise customers. These are the qualities of a person destined for success at ISHIR. ISHIR attracts a special type of individual—someone who is proactive, thrives on challenges, feeds off success, and looks at moving targets not as obstacles but as opportunities. ISHIR is an exciting place to work. It is imbued with an entrepreneurial spirit and promotes self-reliance, open communication, and collaboration