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)

Project Overview We are looking for an experienced AI workflow, process design, and prompt engineering expert to help us automate part of our sales and proposal development process. Currently, our project management team spends 4–12 hours developing a custom research plan and proposal for each active FSI lead. In busy weeks, we may work on 5–6 leads, which creates a significant time burden and slows down response time. We want to build a custom ChatGPT skill or AI workflow that can take sales notes, email context, and call notes, then help generate a research plan and proposal in our existing format. What We Need We need someone who can: Learn and map our current sales/proposal process Translate that process into a structured AI workflow Write effective prompts and decision trees Train or configure a custom ChatGPT skill/workflow Help the AI ask the right follow-up questions Generate proposal sections based on uploaded notes Recommend research scope, segmentation, targets, and options Output the final proposal in our existing template Desired Workflow The ideal AI workflow would allow us to upload notes from emails and sales calls. The AI would then ask a series of structured questions to determine how to write each section of the proposal. The AI should be able to: Recommend the appropriate research process Suggest project scope Identify demand segmentation opportunities Create tables for the proposal Recommend constituencies and companies to target Suggest research options Draft the proposal using our template Provide a strong first draft that our team can review and adjust Business Goal The goal is to significantly reduce the time spent developing research plans and proposals, especially for early-stage leads and marketing-generated opportunities. This is particularly important for new leads from companies we have not worked with before, where the probability of closing may be relatively low. We want to respond quickly and professionally without taking excessive time away from active client projects. Ideal Freelancer You should have experience with some or all of the following: AI workflow design Prompt engineering Custom GPTs or ChatGPT skills Sales/proposal automation Business process documentation B2B research or consulting workflows Template-based document generation AI-assisted decision trees Knowledge management or internal AI tools Experience with market research, consulting, or proposal development is a plus. Deliverables We expect the freelancer to deliver: A documented AI workflow/process map A set of structured prompts and instructions A functioning custom GPT, ChatGPT skill, or equivalent AI workflow Question logic for gathering missing proposal inputs Proposal section drafting logic Testing and refinement using sample lead notes Documentation so our team can maintain and improve the workflow Project Type This will likely begin as a one-time project, with potential for ongoing support as we refine the workflow and expand it to other proposal types. To Apply Please include: Examples of AI workflows, custom GPTs, or prompt systems you have built Your experience with proposal automation or business process automation Your recommended approach for this project Any questions you would need answered before starting

We are looking for a skilled Full-Stack Developer with experience in AI and software engineering to support client communication and technical requirement gathering. In this role, you will be responsible for engaging directly with stakeholders through calls, understanding their technical and business needs, and accurately translating those requirements into clear, actionable documentation for the development team. The ideal candidate should have a strong technical background in full-stack development, AI systems, and modern software architecture, enabling them to ask the right questions, validate assumptions, and ensure that project requirements are correctly captured without ambiguity. You will act as a bridge between clients and engineering teams, ensuring smooth communication and reducing misunderstandings during project execution. Responsibilities include conducting requirement-gathering calls, clarifying technical specifications, documenting system needs, and collaborating closely with developers and product teams. Strong understanding of AI-driven systems, web technologies, and software development workflows is essential to perform effectively in this role. We are seeking someone who can combine technical expertise with clear communication skills, ensuring that complex requirements are translated into structured, developer-ready specifications that support successful project delivery.

Hi We are looking for someone who is expert in Replit/Lovable to for 3 week series of workshops of app building. We are looking for someone who can enjoy imparting knowledge to kids worldwide and align with our vision of giving a level playing field to all kids around the globe. We believe most kids are being shelled by their ecosystem, and we have to expose them to the world. We are looking for someone who can enjoy the process, enjoy working with young brains and can make the workshops fun learning. If this is something you can enjoy. Let's talk. Best Sam

I am working through a design agency on an application for their end client. I think the agency will need you to contract with them directly, but I will manage the project for them. I have scoped out the project already, and our plan is to internally perform a design phase with the client to produce a prototype with Lovable. There may be minor changes to scope after that design phase. The purpose of the app is to create bespoke wedding gown concept images for potential customers of an online wedding dress store. I have provided the details below and attached as a PDF 1. Customer opens an AI dress/gown design experience from a link in their separate e-commerce site. - This can be presented in its own page, we don't want a chat window to be present on any other page - This will be a chat-based interface built into the content area of the page, instead of a popup - The design must be elegant, and match the theme of the e-commerce site - The top navbar and footer don't need to be exactly recreated in this subdomain site, but should look similar enough to create a seamless experience - There will be no integration with the e-commerce site, we need to keep these web apps completely separate 2. The customer must sign up for an account and purchase one credit to begin the AI session - We will need to set up the subdomain site with its own payment processing system and login system - The payment integrations are Stripe to facilitate credit card and Apple pay, and a basic Paypal integration 3. The customers should be able to use a magic link to sign into their accounts, instead of having to remember a password - The account should automatically remember the browser to reduce friction for future access to the app 4. When an AI session begins, we will ask the customer a series of questions programmatically to prime the AI agent so that it can deliver better results - The questions will need to use conditional logic, such that the first question which determines one of 3 main conditional tracks: What type of gown are you looking for? Wedding Gown, Evening Gown, Cocktail Dress - If Wedding Gown is selected, the AI should suggest for the customer to take go to a bridal store and pictures of themselves in different dresses they like and upload the pictures, and describe what they do and don’t like about each dress. It can ask this in the freeform chat, since it may make the most sense to let them fill out the entire questionnaire to stay engaged, and we should reduce the costs of development for the questionnaire by omitting any unnecessary UI that the freeform chat can provide. - It may be best to always just prompt for them to upload the inspirational image at the beginning of the freeform chat so we can omit unnecessary programmatic UI, but in the case of the Wedding Gown it will specifically ask the customer to peform the above task. - We may have other specific questions to add to the questionnaire depending on what conditional track the customer chooses, though only the 3 main branches of conditional logic based on dress type will be required. - Examples of general questions it will need to ask are as follows: -- silhouette -- neckline -- sleeves -- fabric -- embellishments -- color -- train -- length -- closure -- lining -- structure -- inspiration -- event type -- I didn’t get the exact list of questions yet from my client that we should ask in the initial questionnaire. Let me know if you will need this information to accurately provide a price for the development of this application 5. We should not display a concept image after the programmatic questionnaire, the customer will be taken directly into the freeform chat from the questionnaire. - The AI agent may start with an overview of the selected choices from the questionnaire, then can generate concept images at its discretion. 6. The AI should guide the customer through a freeform conversation - The conversation should begin with the AI asking the customer to subjectively describe their dream dress 7. The AI should also make a suggestion near the beginning of the conversation for the customer to upload at least one inspirational photo, but photo upload is optional - If the customer uploads an initial inspiration image, the AI agent should not attempt to figure out body type, measurements, or any other information that we can gather programmatically. - It should treat the inspirational image the same way it would treat any image the customer uploads during the freeform chat, to reduce the cost of development as much as possible. 8. Customer can proceed with a freeform conversation description - The customer should have the option to type in a chat and to upload images - The purpose of the conversation is for the customer to describe the desired dress or gown in an open-ended way 9. AI generates one or more concept images based on the conversation, as soon as it can once it has enough information - The AI model we select should be very good at generating these types of images, this is probably the most important quality the AI model needs to have - The concept images should have the same quality as the final image 10. It is acceptable to generate the gown on a mannequin or a real human model, however the dress must be photorealistic, not a sketch or cartoonish rendering. 11. The concept images that the AI generates and the final image should portray the body type and skin color which the customer specifies - It is very important for us to render the image of the garment on the correct body type - ex. Hourglass, pear-shaped, thin, plus sized, etc. -- Specific body measurements do not need to be factored into the rendering of the body type, it just generally needs to be able to render the garment on different body types. - It is also very important for us to render the garment on a human model or mannequin which has the same or similar skin color as the customer inquiring -- This is important for the customer to judge the garment color and fabric type that will look best on them -- This is also important to make the app inclusive for people of all racial backgrounds who might use the app -- It may be best not to display the face, or if human models are used, to use pictures of models with different racial backgrounds, to avoid bizarre mismatches between facial characteristics and skin tone - The AI agent should ideally prioritize pictures of garments from our client’s website to use as inspiration when it generates renderings in the freeform conversation, along with the customer’s description of what they want. However this is not a hard requirement, so it could be eliminated from the requirements if it greatly increases devlopment effort. - The requirement for the quality of the images that are generated will be somewhat subjective and so we will need to budget time for our client to request revisions to this based on their review of the system. - We need to build the image generation part upfront to ensure the quality is acceptable before we spend time on other parts of the application. 12. AI asks whether the generated concept is generally what the customer wants - Customer can revise the concept conversationally 13. AI can regenerate or refine images after customer feedback 14. The tone of the conversation the AI has with the customer is important. - We will want it to speak like a friendly expert seamstress. - This requirement will be somewhat subjective and so we will need to budget time for our client to request revisions to this tone based on their review of the system. 16. We ideally want the agent (both chat and image generation) to have deep expertise about fabrics and these types of garments in general, so it can guide the user through prompts, and render the chosen fabrics correctly - I think freeform chat will be necessary for the customer to explain which fabrics should be used where on the garment, instead of gathering this informaton in the programmatic questionnaire - The customer will likely revise the fabric selections after they see the initial renderings of the garment - We would like to avoid the costs of training an AI for this, so ideally we should use commercially available AI models which have been trained for this purpose, instead of having to train our own model. Prompting the AI with this information might be a cost-effective way to teach it this expertise 17. There will be certain restrictions on what types of colors or fabrics can be used in the dress designs - So, the agent should know these restrictions when it has the freeform conversation with the customer. - For example, the store owner will not be able to produce dresses with neon colors, tie dye colors, etc. - Our client will articulate a list of restrictions for us before we begin the project. 18. AI should never display links to other websites, or suggest for the customer to navigate to other websites 19. This AI might not need to be trained specifically for this industry, but we should at least use prompting to direct it to gather this kind of information, and to give it some background about what each of these things mean, so it can describe them to the customer. We basically need to make it as knowledgable as possble while keeping costs low. 20. The AI system the system should remember their active conversation - Since the customer will be required to have an account to use the AI system we can use that to automatically save the AI conversation - The saved conversation should preserve all the information that the customer input since the beginning of the AI session - A customer can only have one active AI session at a time - The customer cannot resume an AI session that has been completed - We don't need to provide a way for the customer to see the details of completed AI sessions 21. AI should have a fallback/human-help option if the customer gets stuck or the AI fails. - The fallback should collect enough information for an admin to follow up manually, so it should present a form in order to ensure that all the necessary information gets collected - A message should be displayed above the form, or somewhere on the page, to inform the customer that the entire conversation will be sent along with the form submission, so they know that they do not have to type all the details of the AI conversation - The app must present a button outside of the chat prompts after 3 - 5 chat messages have been sent, so the customer knows they have the option to terminate the AI conversation and manually ask for help. - That button would display the form - We don't want to display the button before any conversation has happened because we don't want customers to skip the chat altogether. -- One of the business goals of this app is to allow custom inquiries without overwhelming the support staff - Site admins must have the ability to adjust how many messages the button will display after, so they can control this threshold after they observe the results of real conversations - After the button initially displays, it should remain present in the view so the customer can easily access it at any point in the conversation 22. The freeform chat must be limited to something like 50 to 75 messages, in order to avoid excessive charges from the 3rd party AI services - This threshold should be adjustable from an admin portal - If this threshold is reached during the conversation, then we should force the customer to use the fallback form from requirement #21 to submit their inquiry 23. Customer can submit the completed design inquiry when satisfied. - During the submission process, the chat must ask for the following information, and present the following pre-written messages. This doesn't actually need to be executed by the AI model, but it can just be programmatically presented to the customer: - Ask for customer contact info, including name, email, and phone number. - Ask for requested event/date, while making clear the date is not guaranteed. - Ask for seamstress-relevant measurements, including bust, waist, hips, hollow-to-hem, shoulder width, bust point, underbust, waist-to-floor, arm length, bicep, wrist, back width, torso length, height, shoe height, and preferred fit. -- I still have to refine this list with the client, I am not sure if it needs to ask for all these things, or if there are some different things that I haven't listed here which it needs to ask for -- When it asks for this information it should display links under each measurement type to articles which describe how to produce each of the measurements. We can hardcode these links or allow the admin to specify each, they don't need to be generated by AI. - Prewritten disclaimer text should display. 24. The final submission should notify a list of email addresses set by a site admin. 25. The final submission will completely consume the credit used to purchase this AI session - The AI conversation cannot be resumed after the final submission - Another credit must be purchased to start a new AI conversation - New AI conversations will not have any memory of the previous conversations, any new AI conversations will start from a clean slate 26. Admins must have the ability to manually reset a credit, or assign a credit for free and cancel a current session, so the customer can start a new AI conversation. - This doesn't need to be very user friendly for the admin. If a session is reset this way, no knowledge of the previous conversation needs to be preserved. 27. Admins should be able to review partial, or completed conversations within a list in the admin portal - Each line item should display a status indicator to show if the conversation has been submitted yet, if an admin has began the review process, or if the item has been handled: Ex. In Progress, Submitted, In Review, Awaiting Payment, Handling, Ready To Ship, Closed - Admin should be able to see the answers to the programmatic questionnaire - Admin should be able to review the full conversation history - Admin should be able to review all uploaded photos/files - Admin should be able to review all AI-generated images, and the final one should be clear to them - Admin should be able to see the collected technical design details and measurements 28. Pricing of the garment remains manual and is handled by after review, the AI should not give any quote or present any pricing even if asked by the customer. 29. If the customer asks for pricing, the AI should display a prewritten script like this: "Pricing will be determined by the store owner after this conversation has been reviewed." 30. Invoices and payment will be handled manually through native WooCommerce custom order/invoice functionality which is already present in the e-commerce site, the AI system doesn't need to handle this at all. I mentioned this above on the requirements, but I want to reiterate since it is important and a hard requirement for how the development milestones must be structured: - The requirement for the quality of the images that are generated will be somewhat subjective and so we will need to budget time for our client to request revisions to this based on their review of the system. - We need to do the image generation part upfront to ensure the quality is acceptable before we spend time on other parts of the application As an optional add-on to the scope of this project, can you give a separate estimate to enhance the AI such that it understands which kinds of modifications will increase or decrease the cost of producing the gown, so it can guide the customer in case they are asking for very expensive things. - It shouldn’t give any specific price numbers, but should give the customer guidance if additions or alterations will significantly increase or decrease the cost of production. - This will be to prevent the customer from being surprised when the store owner manually follows up with them with the price of the garment they designed. This client did agree to adhere to a strict schedule to provide feedback after each round of development, given that we complete each round of development on the schedule we agreed to. - However, this client has deviated from agreed schedules multiple times in the past on other projects I did with them, so you should factor that into your timeline and cost estimations - We cannot increase the development cost mid-way through the project, however we can adjust the development timeline if the client deviates from the schedule In your proposal, please also include a quote or estimate for the cost of hosting and ongoing maintenance after the app has launched - Our client can pay for the hosting directly - We will need at least ongoing updates to patch security vulnerabilities and ensure uptime of the app and all its features which will be defined by the scope of this project - We don't need a 100% 24/7 uptime SLA, but basically just keeping everything up to date so it stays stable, and we'd need someone to respond to outages within 24 hours - Outage response can consist of simple rollbacks, if necessary, as long as all the chat session info is at least provided to the client as a CSV or similar, along with all graphic assets from any conversations, so they don't lose any data from an outage - I would set the expectation with my client that we would treat any future support or enhancement requests to be additionally charged for on an as-needed basis

Type: Hourly, ongoing (part-time to full-time, room to grow) Stack you'll work in: Notion, Slack, HubSpot, Google Workspace/Gmail, Claude + other LLM APIs, Zapier/Make/n8n About us We're a fast-moving sports and fan-engagement startup. We're small, we ship quickly, and we want AI woven into how the whole company operates, not as a side experiment, but as the default way we work. You'd be the person who makes that real. What you'll do Map our current workflows across sales, marketing, ops, and content, then find the highest-leverage places to automate. Build automations and agent workflows that connect our tools (Notion, Slack, HubSpot, Gmail/Google Workspace) using platforms like Zapier, Make, or n8n plus LLM APIs. Design and ship AI agents for real jobs: lead routing and CRM enrichment, content drafting, customer/fan response triage, internal knowledge search, reporting digests. Stand up the connective tissue (prompts, integrations, guardrails, and monitoring) so automations are reliable, not brittle demos. Train and enable our team: build SOPs, run working sessions, and create lightweight docs so non-technical people actually adopt what you build. Help set our AI strategy and roadmap as we scale. You're a strong fit if you Have shipped real automations and AI agent workflows in production (not just prototypes). Are fluent with Zapier / Make / n8n and at least one major LLM API (Anthropic/Claude, OpenAI). Know your way around HubSpot, Notion, Slack, and Google Workspace integrations and APIs. Can write clean prompts and think in systems: edge cases, error handling, human-in-the-loop checkpoints. Can explain technical work to non-technical people and get them to adopt it. Communicate proactively and move fast without breaking trust on things that touch customers or revenue. Nice to have Experience taking a small company "AI-native" end to end. Background in sports and/or blockchain. Comfort with light scripting (Python/JS) when no-code hits its limits. How to apply In your proposal, please: Describe one AI agent or automation you built, the tools involved, and the measurable result. Tell us how you'd approach training a non-technical team to actually use what you build. This part matters as much as the build. Share your hourly rate and weekly availability. Proposals that skip these will be passed over. We're looking to start with a small paid task and grow the engagement from there.

We are building an AI-powered hospitality assistant for full-service restaurants. The product helps guests find the right dishes, increases average check size automatically, and reduces pressure on staff during peak hours — all with zero hardware required. What we need: • Mobile-first web app — opens in the browser, no download required • AI conversation layer using OpenAI GPT-4o or Anthropic Claude API • Owner dashboard for menu management, daily priorities, and live order notifications • Multi-tenant architecture — each restaurant’s data is fully isolated • Real-time notifications between guest interface and staff • Multilingual support: English, Spanish, Arabic • Milestone-based payments with a functional demo at each stage • Full IP transfer on project completion Required: • Live web apps in your portfolio that are currently active • Hands-on experience with OpenAI or Anthropic APIs — name the project • Multi-tenant SaaS experience • Willingness to sign NDA and work-for-hire agreement before project start

Project Capital Advisors (PCA) is seeking an experienced AI Solutions Architect to support a government modernization consulting engagement. The initial project involves helping a county government modernize its citizen telephone operations using Voice AI, workflow automation, and enterprise system integrations. The selected consultant will work directly with executive leadership and public sector stakeholders to assess existing operations, develop technical recommendations, and help define an implementation roadmap. Responsibilities include: * Leading technical discovery sessions with client stakeholders * Evaluating existing phone systems and call workflows * Designing Voice AI and Contact Center AI solution architectures * Recommending enterprise platforms and integration strategies * Creating technical documentation and architecture diagrams * Supporting project scoping, budgeting, and executive presentations Preferred experience: * Enterprise Voice AI or Contact Center AI * Twilio, Amazon Connect, Genesys Cloud, Five9, Retell AI, ElevenLabs, Azure AI, or OpenAI APIs * API integrations and workflow automation * Experience with government or other regulated industries is preferred Engagement Details: * Contract/Fractional * Approximately 10–20 hours per week initially * Remote with occasional travel * Opportunity for additional engagements as PCA expands its Government AI consulting practice Please review the attached position description for complete responsibilities, qualifications, and application requirements.

We are seeking a skilled software developer to finialize our Software development and create a multi-agent orchestration platform. The role involves fininalizing/creating our software development of out Ai-Native TMS, creating a multi-agent orchestration platform that creates all necessary agents to improve system reliability, and optimizing performance. The ideal candidate will have experience in software development and a strong understanding of multi-agent systems. You will work closely with our team to ensure seamless integration and deployment of new features.

Upwork Job Description Title: AI Agent Coach — Teach Me to Set Up & Build Agents with Claw (Beginner-Friendly, 1-on-1) Overview I'm a business owner who is comfortable with software but not a developer. I want to learn how to set up and use an open-source AI agent platform ("Claw" / OpenClaw-style agent framework) to build my own AI agents. Most importantly, I'm looking for someone who is genuinely comfortable explaining things in plain, non-technical terms and can help me build a strong, lasting understanding — not just get something working. What I'm Looking For You'll act as my personal coach and guide. The #1 requirement is teaching ability: you can take technical concepts and explain them simply, check that I actually understand, and build my confidence step by step. The goal is for me to truly understand how everything works so I can set up the platform and build agents on my own afterward. Teaching is the priority — not doing it all for me. Scope of Work Walk me through installation and setup from scratch, explaining each prerequisite in plain language Explain core concepts in beginner-friendly terms: what an agent is, tools/actions, prompts, memory, and how the pieces fit together Help me connect API keys and any required accounts safely Build 1–2 simple agents together so I learn by doing Show me how to test, debug, and troubleshoot when something breaks Pause regularly to make sure I understand before moving on Provide a short written "cheat sheet" or recording of our sessions so I can refer back About Me Comfortable with platforms like Google Workspace and basic automation Not a programmer — please explain things without heavy jargon, or define terms as we go I learn best by doing, with clear step-by-step guidance, and I like to fully understand things Ideal Candidate (Most Important) Excellent at explaining technical topics in simple, non-technical language Patient, encouraging, and focused on helping me genuinely understand — not just finishing the task Proven experience setting up and building AI agents (please share examples or a portfolio) Hands-on experience with Perplexity (including Comet / Computer) and Claude workspace is strongly preferred Comfortable with live screen-share sessions and teaching in real time Available for follow-up questions between sessions Format & Logistics Live 1-on-1 sessions via screen share (Zoom/Google Meet) Estimated 3–5 sessions of 60–90 minutes each (open to your recommendation) Sessions recorded for my reference To Apply, Please Include A brief description of your experience teaching beginners and building AI agents