We are looking for an experienced AI Architect / Senior LLM Engineer to design and build an enterprise-grade AI platform for the healthcare industry. You will lead the architecture and implementation of intelligent AI solutions that improve clinical operations, automate administrative workflows, and enable healthcare professionals to access trusted medical knowledge through advanced AI technologies. The ideal candidate has hands-on experience building production-ready Agentic AI systems, Multi-Agent architectures, RAG pipelines, and LLMOps using modern AI frameworks and cloud platforms. Responsibilities Design and develop scalable Agentic AI solutions for healthcare applications. Build Multi-Agent Systems using LangGraph, CrewAI, or AutoGen. Develop enterprise Retrieval-Augmented Generation (RAG) pipelines for medical knowledge retrieval. Create AI agents for clinical knowledge assistance, document intelligence, workflow automation, and care coordination. Build and integrate MCP servers and custom AI tools with internal healthcare systems. Optimize prompt engineering, retrieval strategies, and response quality for high accuracy. Implement AI guardrails, evaluation pipelines, monitoring, and observability for production deployments. Deploy secure, scalable AI infrastructure on AWS using Infrastructure as Code and CI/CD best practices. Collaborate with engineering, product, and healthcare stakeholders to deliver reliable AI solutions. Required Skills 5+ years of experience in AI/ML or Generative AI development. Strong expertise in Python and backend API development. Experience with LangGraph, CrewAI, AutoGen, or similar multi-agent frameworks. Hands-on experience with AWS Bedrock, Azure OpenAI, or Vertex AI. Strong understanding of RAG architectures, vector databases, embeddings, and semantic search. Experience with Pinecone, Weaviate, pgvector, or similar vector databases. Knowledge of LLMOps, evaluation frameworks, prompt engineering, and AI observability tools. Experience with Docker, Terraform, CI/CD, and cloud-native deployments. Familiarity with healthcare compliance, security, and responsible AI practices is highly preferred. Preferred Technologies LangGraph CrewAI AutoGen AWS Bedrock Claude GPT-4o Gemini Pinecone pgvector LangSmith Arize Phoenix FastAPI Docker Terraform GitHub Actions MLflow Nice to Have Experience developing AI-powered healthcare platforms. Knowledge of healthcare workflows, clinical documentation, or medical knowledge systems. Experience integrating AI solutions with enterprise applications through APIs and MCP. Familiarity with AI governance, model evaluation, and production monitoring. If you are passionate about building enterprise-scale AI solutions that transform healthcare through Agentic AI and Generative AI, we'd love to hear from you.

I am a Ph.D. and digital product business owner who uses AI (Claude, ChatGPT, and other AI tools) every day to build, market, and scale my business. My 12-year-old son and I are looking for an experienced AI tutor who can teach us how to work with AI effectively—not just how to ask questions, but how to think, build, create, and solve problems with AI. This is an ongoing coaching relationship, not a one-time class. I already use AI daily and want to become significantly more advanced in prompt engineering, AI workflows, automation, and business applications. My son is curious, creative, and highly motivated. We want someone who can grow with him over the coming years as AI continues to evolve. WHAT WE ARE LOOKING FOR • Weekly one-on-one coaching sessions (one for me, one for my son) • Hands-on learning using real projects—not lectures or slide presentations • Practical skills that can be used immediately • A structured curriculum that builds over time • Someone who enjoys teaching and can explain complex ideas clearly • Experience with Claude, ChatGPT, and current AI tools MY LEARNING GOALS I use AI every day and want to continue improving how I work with it. Topics include: • Advanced prompt engineering • AI workflow design • Prompt refinement and iteration • Research and fact-checking • Marketing copy • Product descriptions • Sales pages • Email sequences • Business automation • AI-assisted content creation • Website content • Productivity systems • Emerging AI tools and best practices JORDAN'S LEARNING GOALS Jordan is 12 years old. While we'll certainly use AI for school projects and writing, our larger goal is to help him develop future-ready skills that will grow with him through middle school, high school, college, and beyond. We are looking for someone who can progressively teach him how to use AI to create, build, and solve problems. Topics may include: • Learning how to communicate effectively with AI and using AI to support academic success • Critical thinking and verifying AI responses • Research and creative writing • Brainstorming and problem solving • Website design and development with AI • Creating simple games with AI • Building apps and digital tools as his skills grow • Learning basic programming concepts using AI as a coach • Entrepreneurship and business ideas • Using AI to help businesses become more efficient • Marketing and content creation • Responsible and ethical use of AI • Developing confidence as a creator—not just a consumer—of AI technology The ideal tutor enjoys helping young people build real-world skills and can gradually increase the difficulty as Jordan grows. WHAT WE ARE LOOKING FOR IN YOU • Demonstrated experience teaching AI—not simply using it • Strong prompt engineering knowledge • Comfortable teaching both an adult professional and a motivated 12-year-old • Patient, engaging, and adaptable • Able to build a long-term curriculum instead of isolated lessons • Reliable, organized, and an excellent communicator Bonus experience: • Programming or software development • Website development • AI-assisted coding • Game development • Digital marketing • Entrepreneurship • Small business consulting LOGISTICS • Two weekly sessions (one for Jordan and one for me--45–60 minutes each) • Zoom • Weekly to start • Start date: ASAP • Budget: Please include your hourly rate. TO APPLY Please include: Your hourly rate. Your experience teaching AI and prompt engineering. An example of how you would structure Jordan's first month of lessons. An example of how you would structure my first month of lessons. What you think will be the most valuable AI skills for a motivated 12-year-old to develop over the next five years. Applications that do not answer these questions will not be considered. We are looking for someone who enjoys teaching, stays current with AI, and is excited about helping both a business owner and a young learner become confident, capable AI users and creators.

About the opportunity: Come work with a world-class team of designers to create a range of video concepts. You’ll also collaborate with engineers working with generative AI. The role We're looking a creative thinker and doer with deep experience in the latest AI image and video generation tools, especially Google's Veo, Nano Banana, and Omni, who can build reusable prompt systems rather than one-off content. Your design and prompt skills translate to producing consistent, accurate outputs within a business category. For example, imagine there are 2 hair salons focused on getting new clients. Sarah's Salon and Freddie's Barbershop should have the same goal (to acquire clients) and story structure but visually look unique to each brand. We're looking for someone creative with an eye for knowing what kinds of content are scroll-stopping on social for businesses. And someone that can build prompt systems that can accomplish the same goal for different businesses. What you'll do - Build prompt templates for both image and video, covering scratch generation and reference based generation (image to video, or using a reference image to create a new post) - Test each prompt repeatedly to confirm it holds up with real, varied user submitted images, not just cherry picked examples - Document the interchangeable parts of each prompt (what changes per customer, what stays fixed) so the pattern is easy to reuse and hand off internally - Deliver content native to 9x16 vertical; video length varies by content type What we need from you - Strong hands on experience with Google's AI generation tools: Veo 3, Nano Banana, Imagen/Omni - Comfort with reference based workflows: image to video, using a reference image to build new content - Your own active subscriptions and access to these tools - A portfolio we can review showing consistent, high quality output, ideally with before/after or template style examples - Ability to document your process clearly. We need to understand why a prompt is structured the way it is, not just see the final output Nice to have - Experience across multiple industries or business types - A track record of spotting content trends early on social or in marketing.

I’m looking for an AI Engineer to help build an AI Safety Evaluation & Governance product powered by open-source models. This is a 1-month, hands-on project with an expected commitment of around 20 hours per week. The goal is to build an MVP that can automatically test AI models, identify safety failures, analyze failure patterns, and support continuous improvement. 🔍 What you’ll work on • Build an automated red-teaming engine that generates test cases across risk domains, severity levels, and attack strategies • Run tests against models such as Gemma, Llama, Qwen, and API-based models • Develop evaluators for jailbreak success, policy violations, over-refusal, under-refusal, and severity • Structure safety policies into consistent taxonomies and evaluation criteria • Turn confirmed failures into reusable eval datasets and regression tests • Build lightweight reporting for model comparison, human review, and policy-version tracking 🧠 What I’m looking for • Experience with open-source LLMs, inference pipelines, prompt optimization, fine-tuning, LoRA/QLoRA, and LLM evaluation • Ability to independently build an end-to-end MVP, including data pipelines, model orchestration, scoring, and reporting • Familiarity with AI safety, red teaming, jailbreaks, content moderation, or Trust & Safety systems • Bonus: experience with model-based evaluators, human-in-the-loop review, agentic testing, or multimodal safety ⏳ Project setup Duration: 1 month Time commitment: Around 20 hours per week Format: Flexible and remote-friendly Stage: Early-stage, 0-to-1 MVP This is not about manually writing red-team prompts one by one. The goal is to build a scalable system that can continuously generate tests, evaluate model behavior, identify safety gaps, and verify whether issues have been resolved. If this sounds like you, please DM me with a brief introduction and examples of relevant work.

We're building an AI Research Copilot for our financial analytics platform. The Copilot will help investors and financial professionals analyze market data, company financials, news, and earnings using natural language. This is a production AI project, not a basic chatbot. Responsibilities Build a production-ready AI Research Copilot Design and implement RAG pipelines Integrate LLMs with our financial data and APIs Implement semantic search and tool calling Build conversation memory and streaming responses Add source citations and improve response accuracy Optimize performance and reduce hallucinations Required Skills Python OpenAI, Claude, or Gemini APIs RAG and vector databases (Pinecone, Qdrant, pgvector, Weaviate, etc.) LangGraph, LangChain, LlamaIndex, or similar frameworks API integration Prompt engineering Production AI application experience Please include: AI products or copilots you've built Your experience with production RAG systems Your preferred AI architecture for this project Briefly explain how you reduce hallucinations and provide trustworthy AI responses. We're looking for an experienced engineer who can build scalable, production-quality AI systems and collaborate long term.

We are looking for a skilled, hands-on AI Engineer to help us build and optimize our AI product. You will be responsible for designing the AI architecture, integrating modern LLMs/frameworks, and ensuring our AI pipeline runs efficiently, reliably, and accurately in production. Responsibilities Design, build, and deploy custom AI solutions (LLM integration, RAG, AI agents, or fine-tuning). Build robust prompt engineering pipelines, function-calling workflows, or structured output mechanisms. Implement vector databases (e.g., Pinecone, Weaviate, Qdrant, ChromaDB) for semantic search and retrieval. Optimize latency, API costs, and context window efficiency across LLM providers (OpenAI, Anthropic, open-source models). Connect AI models to backend services via REST APIs / webhooks. Implement evaluation metrics (hallucination detection, retrieval accuracy, output validation). Required Skills & Qualifications Languages: Python (strong expertise required), TypeScript/Node.js (a plus). AI / ML Tooling: LangChain, LlamaIndex, AutoGen, CrewAI, or direct SDK integrations (OpenAI, Anthropic, Hugging Face). Databases: Vector databases (Pinecone, Chroma, Qdrant, pgvector) + relational/NoSQL DBs. Deployment & Cloud: Docker, AWS / GCP / Azure, FastAPI / Flask, Serverless architectures. Core Concepts: In-depth understanding of Embeddings, RAG, Fine-Tuning, Function Calling, and Agentic Workflows. Preferred (Nice to Have) Experience deploying open-source models locally or on dedicated hardware (vLLM, Ollama, Hugging Face TGI). Experience with fine-tuning techniques (LoRA, QLoRA). Background in frontend AI UI integration (Vercel AI SDK, Streamlit, Gradio).

We are a Managed IT Services Provider (MSP) serving small and mid-sized businesses (typically 10–100 employees) and have built our reputation on long-term client relationships and trusted technology advice. Our clients are increasingly asking us to help them adopt AI. We're looking for an experienced AI consultant to become an extension of our team and provide strategic guidance, solution design, and technical leadership. This is an ongoing partnership rather than a one-time project. What We're Looking For We are looking for someone who has successfully designed and implemented AI solutions for businesses and can confidently guide clients from initial discovery through implementation. You should be able to understand a client's business, identify where AI can provide meaningful value, recommend the appropriate technologies, build an implementation roadmap, and support our engineering team throughout the project. Our internal team will perform much of the implementation. We need someone who can provide the expertise, architecture, and strategic direction. Responsibilities You will work alongside our sales and engineering teams to: Join client discovery meetings Evaluate business processes and identify AI opportunities Recommend practical, ROI-focused AI solutions Help clients understand available AI technologies and select the right approach Design solution architecture Build implementation plans and project roadmaps Create scopes of work and technical requirements Assist with client presentations and proposal development Advise our engineers during implementation Provide ongoing consultation as projects evolve Required Technical Expertise You must have deep, hands-on experience with: Anthropic Claude (prompt engineering, Projects, MCP, API integrations, enterprise use cases, workflow design, and best practices) OpenAI / ChatGPT (GPT models, API usage, Assistants/Agents, function calling, enterprise deployments, and integrations) Microsoft 365 Copilot You should be the person our team turns to when deciding which model to use, how to architect a solution, and how to solve complex implementation challenges. Additional Experience Preferred Experience with several of the following is highly desirable: Microsoft Azure AI Google Gemini AI agents and autonomous workflows Retrieval-Augmented Generation (RAG) Model Context Protocol (MCP) Vector databases Knowledge management systems AI governance and security Business process automation Power Platform n8n Make Zapier CRM, ERP, and line-of-business integrations Custom AI application development The ideal consultant: Has led multiple successful AI implementations for businesses Understands both the technical and business sides of AI Can communicate effectively with executives as well as engineers Knows when AI is, and is not, the right solution Stays current with the rapidly changing AI landscape Can translate business problems into practical AI implementations Can implement lower cost solutions for smaller companies with limited budgets Typical Engagement A typical engagement might include: Meeting with a client's leadership team Understanding their workflows and business challenges Identifying the highest-value AI opportunities Recommending the appropriate technologies and architecture Estimating project effort and ROI Helping present recommendations to the client Supporting our engineering team during implementation Remaining available as a technical advisor as needed To Apply Please include: Your background designing and implementing AI solutions for businesses. A representative AI project you've personally led, including the technologies used and measurable business outcomes. Your experience with Claude and OpenAI, including APIs, enterprise deployments, and complex workflows. Your experience with MCP, AI agents, RAG, and business process automation. How you typically conduct an AI assessment for a new client. We're looking for a long-term strategic partner who can become the AI expert for our organization and help us deliver exceptional AI solutions to our clients.

I’m looking for a developer to help build a lightweight AI prototype using OpenAI or Anthropic APIs. This is NOT a full product build. This is a focused prototype to test a specific idea. Project Goal: Build a simple Python-based system that: Runs the same LLM task multiple times. Captures outputs and any intermediate state (memory/logs). Compares differences between runs. Classifies differences into simple categories: Stable Boundary Violation What This Means Think: •Run the same prompt 5–10 times. •Log results. •Detect where outputs or stored data differ. •Label those differences. That is it. Technical Requirements Must have: •Python •Experience with OpenAI API or Anthropic API •Ability to build simple, clean scripts (no over-engineering) Nice to have: •LangChain or similar frameworks. •Streamlit (for simple UI/dashboard). •Experience with logging or comparing outputs. Important Constraints This should be: •Lightweight. •fast to build. •easy to understand. Please DO NOT: •Design complex architectures. •build full systems. •over-engineer. Deliverables •Python script or small app. •Ability to run repeated LLM tasks. •Stored logs of runs (JSON or similar). •Basic comparison logic between runs. •Simple classification output. Timeline •3–7 days initial build •Max 1–2 weeks total Engagement Style •Fixed-price or hourly (open to discussion) •Will start with a small paid test task before full project Screening Question (Required) Please answer this: If you needed to run the same LLM task multiple times and compare outputs/state between runs, how would you build it quickly? Who This Is For Ideal candidate: •Builds fast prototypes. •Comfortable with LLM APIs. •Prefers simple solutions over complex systems.

About us: Luxe Intelligence is a Baltimore based AI consulting firm. We design and deliver custom AI agent systems for business clients, including regulated industries, with a growing security and government-adjacent practice. We design the system and own the client relationship. You build to spec. The kind of work: Real examples of project types on our roadmap: - Data matching and compliance checking agents that cross-reference large lists (10,000+ rows) with no shared ID, using fuzzy name matching, confidence scoring, and human review flags - Research agents that pull from defined sources and produce structured memos with citations, and say "unverified" instead of guessing - Workflow automations across webhooks, spreadsheets, CRMs, Slack, and email - Read and write-back integrations with systems of record like Salesforce - Deployments inside client cloud environments with audit logging and security review support Must haves: - Strong Python, including pandas and API work - Hands-on experience with LLM APIs (Anthropic, OpenAI): prompt design, structured outputs, cost control - Fuzzy matching or entity resolution experience on real data - Cloud deployment on AWS, Azure, or GCP - Security-minded engineering as a habit, not an afterthought: secrets management, least-privilege access, encryption in transit and at rest, audit trails, human-in-the-loop review steps - Clear written English and documented handoffs Nice to have: - A real cybersecurity background: security engineering, compliance frameworks (SOC 2, NIST, FedRAMP awareness), or secure deployment in regulated environments - US citizenship with eligibility for a government security clearance, or an active clearance, is a plus and worth mentioning - Make.com or similar automation platforms - Salesforce API - Experience answering client security questionnaires How we work: Fixed-price milestones scoped from agreed hour estimates, paid on delivery and approval. NDA signed before any project details are shared. No client contact; all communication runs through Luxe. Some overlap with US Eastern hours. Every engagement starts with one small paid test milestone. Strong performance can grow into a larger ongoing role. To apply, answer these four things, and start your reply with the word CHARCOAL so we know you read this far: 1. Describe a fuzzy matching or entity resolution project you built. How big was the data, and how did you score confidence? 2. Describe an LLM-powered system you deployed into someone else's environment. What broke, and how did you fix it? 3. Estimate this: two lists, about 10,000 rows and 2,000 rows, no shared ID. Need matches, confidence scores, and a monthly flagged-items report. Roughly how many hours, broken down however makes sense to you? 4. Your hourly rate, your weekly available hours, and any security or clearance background.

Upwork's Governance, Risk & Compliance (GRC) team is seeking an experienced freelancer with a strong background in AI tool automation to help streamline and enhance our compliance workflows. You will work closely with our GRC team to identify automation opportunities, design and implement AI-driven solutions, and integrate tools that improve efficiency across risk assessments, policy management, audit preparation, and compliance monitoring. Key Responsibilities: Assess existing GRC workflows and identify high-impact automation opportunities Design and implement AI-driven automations using Claude AI to support intelligent document analysis, risk summarization, policy drafting, and compliance Q&A workflows Integrate AI tools with Linear & Vanta to enhance compliance monitoring, evidence collection, and control mapping Build automated workflows for risk tracking, audit preparation, and policy lifecycle management Document solutions and provide handoff training to internal GRC team members Required Qualifications: Deep knowledge of GRC principles, practices, and frameworks — including SOC 2, ISO 27001, ISO 27018, ISO 42001, PCI-DSS, and Microsoft SSPA — with the ability to translate compliance requirements into functional automation logic Demonstrated experience building AI and automation workflows, including LLM integration, prompt engineering, and API-based tool development Strong understanding of risk management methodologies, control frameworks, and audit readiness processes Experience operationalizing compliance programs, not just familiarity — you should be comfortable owning GRC workflows end-to-end Proficiency with no-code/low-code automation platforms and/or Python scripting Excellent written and verbal communication skills, with the ability to document technical solutions clearly for compliance audiences Preferred Qualifications: Prior hands-on experience working within a GRC or Information Security team Relevant certifications such as CISA, CRISC, CISSP, or ISO Lead Implementer/Auditor Experience with AI governance frameworks and emerging standards around responsible AI (aligned with ISO 42001) Familiarity with Upwork's platform or similar marketplace environments