Join our team as a senior AI Architect working closely with our product and engineer teams to design practical AI capabilities within our SaaS platform. This is a hands-on role focused on building reliable, production-grade conversational and AI-assisted features — not experimental research projects. You will work closely with product and engineering teams to design scalable AI patterns, integrate modern LLM technologies, and help shape how AI capabilities are embedded into real operational workflows. You will focus deeply on architecture, implementation quality, reliability, usability, scalability, observability, and operational robustness. This role is ideal for someone who understands both modern AI tooling and the realities of shipping enterprise SaaS software in production environments. We value people who can think critically about architecture, tradeoffs, operational realities, and long-term maintainability — not just prototype AI demos.

Senior Software Engineer (AI-Focused, Contract – US) Position Summary W Energy is seeking a Senior Software Engineer (Contract) to help drive the integration of AI capabilities into our core platform. This role is focused on building AI-powered product features, not just experimenting with models—embedding intelligence directly into workflows across our upstream and midstream solutions. You’ll design and implement AI-driven functionality that improves automation and user experience. This includes leveraging LLMs, machine learning models, and modern AI tooling within a production SaaS environment. This is a hands-on role for someone who can move quickly, make pragmatic decisions, and bring AI concepts into real, scalable product features. Responsibilities • Design and implement AI-powered features within the platform (e.g., automation, recommendations, copilots) • Integrate LLMs and/or ML models into existing services and workflows • Evaluate, select, and optimize AI tools, APIs, and frameworks for production use • Collaborate with Product to translate business problems into AI-driven solutions • Build and maintain scalable backend services to support AI functionality • Profile, test, and optimize performance of AI-integrated systems • Ensure reliability, security, and cost-efficiency of AI components in production • Contribute to architecture decisions around AI integration and system design • Partner with engineering teams to embed AI into existing applications without degrading stability Requirements • 5+ years of experience as a software engineer in a SaaS or cloud-based environment • Strong backend engineering experience (RoR and/or Golang preferred) • Experience integrating APIs and working within distributed systems • Hands-on experience with AI/ML tools (e.g., OpenAI, Anthropic, Hugging Face, or similar) • Experience building or integrating AI-powered features into applications (not just experimentation) • Strong understanding of data flow, system design, and performance optimization • Experience with relational databases (SQL Server or similar) • Familiarity with microservices architecture, Kubernetes, and CI/CD pipelines • Experience deploying applications in Azure or similar cloud environments • Strong problem-solving skills with ability to work in ambiguous, fast-moving environments • Builder mindset—someone who can take an idea and turn it into a working feature quickly • Pragmatic approach to AI (focus on value, not hype) • Ability to work independently in a contract environment while collaborating closely with internal teams • Strong communication skills and ability to explain AI concepts to non-technical stakeholders Preferred • Experience with prompt engineering, embeddings, or retrieval-augmented generation (RAG) • Exposure to model evaluation, fine-tuning, or AI performance monitoring • Experience with event-driven architectures or real-time data processing • Background in energy, fintech, or other complex data-driven industries

The Role: As a Software Engineer on our AI Infrastructure team, you will help design the core systems that power Prism AI’s generative AI platform. You will help build infrastructure and tools that ensure the reliability, performance, quality, and availability of our AI system. Our mission is to make Prism AI the most reliable and user friendly generative AI platform in the world. You will partner closely with our cloud infrastructure team, product team, and performance team to deliver infrastructure that bridges the gap between our customer and the ultra-performant proprietary Prism inference engine. Key Responsibilities: Contribute to the design and development of scalable backend infrastructure that supports distributed training, inference, and data pipelines Build and maintain core backend services such as LLM CI/CD pipeline, control plane, and model serving systems Support performance optimization, cost efficiency, and reliability improvements across compute, storage, and networking layers Building frameworks and safeguards to ensure Prism AI has the best model quality in the industry Collaborate with performance, training, and product teams to translate research and product needs into infrastructure solutions Participate in code reviews, technical discussions, and continuous integration and deployment processes Minimum Qualifications: Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience) 3 years of experience in software engineering, with a focus on infrastructure or machine learning systems Strong programming skills in Python, Go, or a similar language Proven experience in ML infrastructure and tooling (e.g., PyTorch, MLflow, Vertex AI, SageMaker, Kubernetes, etc.). Basic understanding of LLM knowledge (e.g., context length, disaggregated prefill, KV cache memory estimation, etc) Preferred Qualifications: 5+ years of experience in software engineering, with a focus on infrastructure or machine learning systems Experience with open source inference engine like vLLM, Sglang, or TRT-LLM Contributions to open-source infrastructure or ML projects Experience in building large scale ML/MLOps infrastructure

Project Title: Build Fast Web-Based AI Anime Companion MVP (RAG + Merch Gen) – 15–30 Days, $25K Budget: $18,000–$25,000 fixed Timeline: 15–30 days (3 weeks preferred) Must-Have Skills: FlowiseAI (or LangChain/LlamaIndex), RAG pipelines, OpenAI/Claude/Grok, anime image generation (Leonardo.ai/Ideogram/PixAI), Vercel or Railway deployment Project Goal Build a mobile-friendly web AI Companion for Big A Anime that converts passive FAST viewers into active fans. The key objective is to connect our Pluto TV channel experience directly to the AI companion, allowing viewers to scan QR codes during live programming and instantly access interactive content, recommendations, and merch tied to what’s currently airing—no downloads required. Core MVP Features Web Chat Interface Clean anime-branded chat UI with voice input Mobile-first, responsive Custom domain (e.g., companion.biganime.tv) RAG Knowledge Base Ingest episodes, schedules, transcripts, and metadata Provide accurate recaps, lore, and “what’s on now/next” tied to Pluto TV programming Session memory + light user profiles AI Merch Generator Anime-style image generation (“me as [character]”) Leonardo.ai or similar integration Export + links to Printful/Printify FAST / TV Integration Tools Dynamic QR codes for on-screen use Deep linking between Pluto TV programming and companion experience Voice-friendly prompts (“Ask Big A Companion…”) Admin & Analytics Simple CMS for content uploads Dashboard: usage, queries, merch clicks Technical Requirements Global hosting (CDN) FlowiseAI preferred Full source + documentation 30 days post-launch support Out of Scope Native apps, payments, deep integrations, multi-language Deliverables Live URL, admin access, training, source code, 30-day support Application Fixed bid + 3-week plan 2–3 relevant project links Willingness for small paid test ($500–$800)

We're building an AI health companion for women's health and need an experienced AI Architect for weekly consulting sessions (3-5 hours/week). What You'll Do Meet with our team 1-2x per week to review architecture and provide technical guidance Help optimize our AWS Strands/RAG integration for latency, cost, and scalability Advise on conversation management, context handling, and orchestration decisions Guide us through key technical tradeoffs as we move from prototype to production Our Stack Django backend, Flutter frontend, AWS Strands What We Need 5+ years with AI/ML in production, especially RAG/LLM integration and orchestration Experience with AWS Strands and Bedrock Track record with conversation AI architecture and scaling constraints Bonus: healthcare/HIPAA experience, startup advising, Django/Python knowledge Details 3-5 hours/week, flexible remote schedule Initial 3-month engagement Mix of live calls and async reviews

Overview I have a Next.js website with a newsletter signup form that currently submits directly from the browser to HubSpot's Forms v3 endpoint. I want to add a lightweight LLM-based spam filter that inspects each submission *before* it reaches HubSpot, and silently rejects (or flags) anything that looks like spam/bot/junk input. Current setup - Framework: Next.js (App Router, TypeScript, React client component) - The form component (`NewsletterForm.tsx`) POSTs directly to `https://api.hsforms.com/submissions/v3/integration/submit/[portalId]/[formGuid]` - Fields collected: `firstname`, `lastname` (optional), `jobtitle`, `email` - Portal ID and Form GUID are public form identifiers (no secrets today) What I want you to build 1. Create a server-side API route in the Next.js app (e.g. `app/api/subscribe/route.ts`) that: - Receives the form fields from the client - Runs an LLM spam/quality check (e.g. OpenAI or similar) to classify the submission as legit vs. spam — checking for gibberish names, fake/disposable emails, nonsense job titles, injection attempts, etc. - If legit → forwards the submission to HubSpot (server-side) - If spam → rejects gracefully with a generic message (no HubSpot write) 2. Update the existing `NewsletterForm.tsx` to POST to the new internal API route instead of calling HubSpot directly. 3. Keep the LLM API key server-side only (use an environment variable — never expose it to the client). 4. Preserve the existing UX: loading / success / error states should still work. Deliverables - Working API route with the LLM spam check + HubSpot forwarding - Updated form component - Brief note on which env vars to set (`OPENAI_API_KEY`, etc.) and how to configure them - Clean, typed TypeScript that matches the existing code style Nice to have (optional) - Basic rate limiting / honeypot field as a cheap first line of defense before the LLM call - Configurable spam threshold or a logged "reason" when something is rejected Requirements to apply - Strong Next.js App Router + TypeScript experience - Experience calling an LLM API (OpenAI or equivalent) from a server route - Familiarity with HubSpot Forms API is a plus To apply, please briefly answer: 1. Which LLM/provider would you use and roughly what would it cost per submission? 2. How would you handle the case where the LLM API is slow or down — do you fail open (let it through) or fail closed (block it)? 3. Have you integrated with HubSpot Forms before? (yes/no is fine)

I'm looking for a skilled developer who can move fast, think creatively, and act more like a partner than a contractor. If you're someone who builds things quickly, brings ideas to the table without being asked, and genuinely cares about creating great experiences for end users, keep reading. -—————- **What You'll Be Working On:** This product sits at the intersection of AI, data, and customer experience. At its core, it needs to: - Monitor and process large volumes of data** in or near real time — surfacing insights, anomalies, and patterns that matter. - Send automated personalized outreach via SMS and email — based on the data signals and triggers, the system should be able to generate and send personalized messages to the right person at the right time, without manual intervention - Integrate with POS systems and CRMs** — pulling, syncing, and acting on data across platforms - Deliver a seamless, intuitive customer-facing experience** — this isn't just a backend tool, how users feel when they interact with it matters enormously - Be built on top of **Claude (Anthropic's AI)** using **Claude Code** as a core part of the development workflow We're in early stages, which means we're figuring things out as we go. That's not a warning — it's an opportunity for the right person. --- **What I'm Looking For:** - Hands-on Claude Code experience** — you've actually built with it, not just read about it. Experts only please - CRM and POS integration experience** — you've connected to platforms like Salesforce, HubSpot, Square, Toast, Lightspeed, or similar, and you know the quirks - Data monitoring and pipeline experience** — you've built systems that ingest, process, and surface meaningful signals from large datasets - Customer experience mindset** — you think about the end user constantly, and you've built tools that real customers interact with - Fast builder, fast thinker** — you're comfortable with ambiguity, can ship quickly, and know how to iterate without everything being perfectly defined upfront - Collaborative and opinionated** — I want someone who pushes back, brings ideas, and helps shape where this goes — not someone waiting for a spec I also want to **learn as we build** — so being able to explain what you're doing and why, in plain terms, is important to me. --- A Note Before You Apply: Please only submit a proposal if you have deep, hands-on experience with Claude Code — not surface-level familiarity, not currently learning it. We're looking for someone who has already put in the reps, knows the ins and outs, and can hit the ground running from day one. We respect your time and ask that you respect ours. If Claude Code isn't already a tool you've mastered, this isn't the right fit. **When You Apply, Please Include:** - Specific examples of tools you've built that involve **CRM or POS integrations** — name the platforms and describe what you built - Examples of **data monitoring or real-time data tools** you've worked on — what did it track, how did it work, what was the scale? - Any **AI-powered products** you've shipped, especially using Claude or other LLM APIs — links, screenshots, or descriptions - How you approach building something when the full picture isn't defined yet - A thought or two on what makes a truly great AI-powered customer experience — I want to see how you think --- **What This Could Become:** This is the beginning of something bigger. The right person won't just be a hire — they'll grow with the product. There's real potential for a long-term working relationship as this evolves.

### Job Description: AI Chatbot Developer We are excited to announce an opening for an experienced and innovative developer to join our dynamic team in the pursuit of creating an advanced AI Chatbot. This chatbot will be designed to perform essential business functions, including but not limited to lead generation, quoting, and providing exceptional customer support. Our ideal candidate will possess a robust background in AI technologies, particularly in the realm of chatbot development, and will be equipped with outstanding problem-solving skills that enable them to tackle complex challenges with creativity and efficiency. As a key member of our development team, you will collaborate closely with various departments to gain a comprehensive understanding of our specific operational needs and requirements. Your ability to translate these needs into a functional and user-friendly chatbot solution will be critical to enhancing our overall operational efficiency. We are looking for someone who is not just technically proficient but also possesses a keen sense of business acumen to ensure that the chatbot aligns with our strategic goals. In this role, you will be responsible for various aspects of the chatbot development lifecycle, including but not limited to: - Designing and developing the conversation flow and user interface of the chatbot, ensuring it is intuitive and engaging for users. - Implementing natural language processing (NLP) capabilities to enable the chatbot to understand and respond to user inquiries accurately. - Integrating the chatbot with existing systems and databases to facilitate seamless access to information necessary for lead generation, quoting, and customer support functions. - Conducting rigorous testing and quality assurance to ensure the chatbot performs reliably and meets user expectations. - Analyzing user interactions and feedback to continuously improve the chatbot's performance and expand its capabilities over time. - Staying current with the latest advancements in AI technologies and chatbot development to incorporate best practices and innovative solutions. You will also play a crucial role in training team members on how to utilize the chatbot effectively and will be expected to provide ongoing support and maintenance to ensure the chatbot remains up-to-date and functional. If you have a passion for artificial intelligence, a deep understanding of customer engagement strategies, and a desire to make a significant impact within our organization, we would love to hear from you! Join us in revolutionizing the way we interact with our customers and streamline our business processes through cutting-edge technology. This is a fantastic opportunity for someone looking to advance their career in a fast-paced, forward-thinking environment. Apply today and be part of our exciting journey towards enhancing our customer experience through AI!

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 are looking for a hands-on Forward Deployed AI Engineer to help build practical AI systems This is not a pure backend role and not a strategy-only consulting role. You will work close to end users, understand how their workflows actually operate, and then build AI-enabled tools that solve specific business problems. The ideal person is a strong software engineer who is comfortable with ambiguity, can communicate clearly with non-technical stakeholders, and can take an AI prototype from idea to something reliable and usable. What you will do - Learn the business workflows, systems, data, and constraints. - Build AI applications using Claude or similar large language models. - Use the right mix of prompting, retrieval, tool use, agents, and workflow automation. - Own delivery from scoping through prototype, testing, hardening, and handoff. - Create evaluations to determine whether the system is accurate, reliable, and safe enough to use. - Translate between domain experts and technical implementation. - Work carefully with sensitive or regulated data. - Document what you build so it can be maintained and reused. What we are looking for - Strong Python engineering skills. - Hands-on experience building with LLMs, preferably Claude or the Anthropic API. - Experience with RAG, structured prompting, tool use, evaluation, or agentic workflows. - Ability to operate independently in a messy, ambiguous environment. - Strong communication skills with both technical and non-technical stakeholders. - Track record of shipping working software, not just demos. - Comfort working with real-world data, integrations, and imperfect requirements. Helpful but not required - Prior forward deployed engineering, solutions engineering, or technical consulting experience. - Experience building AI tools for enterprise customers. - Experience in regulated or sensitive-data environments. - Familiarity with validation, auditability, traceability, or compliance-oriented workflows.