Artificial Intelligence Engineer

AI Engineer – AllysAILocation: Remote (4+ hours overlap with UAE timezone / GMT+4) Type: Full-time Reports to: CEO/Founder THE OPPORTUNITYAllysAI is an AI Lab-as-a-Service that helps enterprises escape "pilot hell" and ship production AI in 60-90 days—not 12+ months. Our clients include Al Futtaim, Merz Pharmaceuticals, Abu Dhabi Government entities, and Sanofi. We don't do PowerPoint AI. We build systems that run in production, handle real workloads, and deliver measurable ROI. We're looking for an AI Engineer who doesn't just write code—you architect intelligent systems. You're the person who reads AI papers on weekends, has opinions about which vector database to use and why, and can explain transformer attention mechanisms to a CEO in plain English. You ship fast, iterate faster, and treat every project like it's your own company. This role is a launchpad. We're building the team that will define how enterprises adopt AI in the Middle East and beyond. The right person will grow into a CTO role as we scale. WHAT YOU'LL DOBuild Production AI SystemsDesign and deploy RAG architectures, multi-agent systems, and LLM-powered applications for enterprise clients Build process automation pipelines that replace manual workflows with intelligent agents Implement fine-tuning pipelines when off-the-shelf models don't cut it Ship solutions in 4-8 week sprints that meet enterprise security, scalability, and compliance standards Own the Technical VisionEvaluate and integrate emerging AI tools, frameworks, and models weekly Make architecture decisions that balance speed, cost, and performance Build reusable components and internal tools that accelerate future projects Document systems so they can be maintained, extended, and handed off to clients Bridge Tech and BusinessJoin client calls to understand requirements and translate them into technical specs Explain tradeoffs to non-technical stakeholders clearly and confidently Identify opportunities where AI can solve problems clients didn't know they had Contribute to proposals, scoping, and technical due diligence for new engagements Move at Startup SpeedPrototype solutions rapidly using AI-assisted development tools (Claude, Cursor, Copilot) Deploy to production environments confidently and frequently Debug, iterate, and improve based on real-world feedback Work autonomously while keeping the team aligned on progress and blockers WHO YOU AREAI-Obsessed You don't just use AI—you study it. You follow AI developments closely, read papers, experiment with new models the week they drop, and have strong opinions about prompt engineering, RAG chunking strategies, and agent architectures. Technically Exceptional You have expert-level Python skills. You've built production systems, not just Jupyter notebooks. You understand software engineering fundamentals: clean code, version control, testing, CI/CD, monitoring. You thrive debugging complex distributed systems. Business-Minded Builder You understand that code is a means to an end. You think about user problems, ROI, and adoption. You can scope a project, estimate effort, and make tradeoffs that balance technical excellence with business reality. Future Technical Leader You want to lead. You think about system design, team scaling, technical strategy, and how to build something lasting. You're looking for a high-growth environment where your trajectory matches your ambition. REQUIRED SKILLS & EXPERIENCEExperience3+ years building production software (not just ML experiments) 2+ years working specifically with LLMs, RAG, or generative AI in production Track record of shipping: show us what you've built Core Technical SkillsPython: Expert-level. FastAPI, Pydantic, async programming, clean architecture LLM Orchestration: LangChain, LangGraph, LangSmith, LlamaIndex—experience with at least two RAG Systems: Vector databases (Pinecone, Weaviate, Qdrant, Chroma), embedding strategies, retrieval optimization, chunking approaches Agent Frameworks: CrewAI, AutoGen, Pydantic, custom agent architectures—you understand when to use agents and when they're overkill Automation Platforms: n8n, Make, Relevance AI, or similar—you can build workflows that connect AI to business systems APIs & Integrations: REST, webhooks, OAuth—you can connect anything to anything Cloud Platforms: AWS, GCP, or Azure—you can deploy, scale, and monitor AI/ML DepthPrompt engineering: You write prompts that work, not prompts that sort of work Fine-tuning: You've fine-tuned models (LoRA, QLoRA, or full fine-tune) and know when it's worth it Evaluation: You can measure AI system performance beyond "it looks good" Cost optimization: You understand token economics and can architect for efficiency AI-Assisted DevelopmentYou actively use AI coding assistants: Claude, Cursor, GitHub Copilot You can scaffold applications rapidly and iterate quickly You know how to leverage AI tools for maximum productivity You understand the limits—when to trust AI-generated code and when to rewrite Bonus PointsGraduated from a Top-Tier Engineering School Experience with multi-modal AI (vision, audio, video) Knowledge of MLOps: model versioning, experiment tracking, deployment pipelines Familiarity with enterprise requirements: SOC2, GDPR, data residency Open source contributions or public projects in AI spac Experience in consulting, agencies, or client-facing technical roles TECH STACKLanguages & Frameworks: Python, FastAPI, Pydantic, TypeScript (for frontend integrations) LLM & AI: OpenAI, Anthropic Claude, Google Gemini, Mistral, Llama, Cohere, LangChain, LangGraph, LangSmith, LlamaIndex, CrewAI, AutoGen Vector & Data: Pinecone, Weaviate, Qdrant, Chroma, PostgreSQL + pgvector, Supabase Automation & Integration: n8n, Make, Relevance AI, Zapier, custom webhook architectures Infrastructure: AWS (Lambda, ECS, Bedrock), GCP (Cloud Run, Vertex AI), Azure, Vercel, Railway, Docker, GitHub Actions Development Tools: Claude, Cursor, GitHub Copilot HOW WE WORKRemote-first: Work from anywhere with 4+ hours overlap with UAE timezone (GMT+4) Async communication: We document decisions, write clear specs, and respect deep work time High ownership: You own projects end-to-end, from scoping to deployment to client handoff Fast feedback loops: Weekly demos, rapid iteration, direct client interaction Learning culture: We share what we learn, experiment with new tools, and grow together COMPENSATIONBase Salary: Competitive, based on experience and location Performance Bonus: Tied to project delivery and client outcomes Equity: Meaningful stake in AllysAI's growth Learning Budget: Resources for courses, conferences, and tools Equipment: What you need to do your best work WHY ALLYSAIImpact from Day One No six-month onboarding. No bureaucracy. You'll ship to production in your first week and see your work used by real enterprises. Work on Hard Problems Enterprise AI implementation is genuinely difficult. You'll solve problems that don't have Stack Overflow answers—and build expertise that's rare in the market. Technical Leadership Track We're explicit about this: we're looking for someone who wants to lead. As AllysAI grows, so does your role. The path from AI Engineer to CTO is real and achievable here. Front Row to the AI Revolution You'll work across industries (pharma, real estate, government, finance), use cases (sales, marketing, HR, operations), and technologies (RAG, agents, automation, fine-tuning). No two projects are the same. Founder Access You'll work directly with the CEO. No layers. No politics. Direct feedback, direct impact, direct growth.