artificial intelligence engineer

Raqmiyat

<div><div><h3 class="jobSectionHeader"><b>Job Information</b></h3>
<ul><div><p>Date Opened</p>
<div><b>04/03/2026</b><b>
</b></div></div><div><p>Job Type</p>
<div><b>Full time</b><b>
</b></div></div><div><p>Job Opening Status</p>
<div><b>In-progress</b><b>
</b></div></div><div><p>Work Experience</p>
<div><b>4-5 years</b><b>
</b></div></div><div><p>Industry</p>
<div><b>Technology</b><b>
</b></div></div><div><p>City</p>
<div><b>Riyadh</b><b>
</b></div></div><div><p>State/Province</p>
<div><b>Ar Riyad</b><b>
</b></div></div><div><p>Country</p>
<div><b>Saudi Arabia</b><b>
</b></div></div><div><p>Zip/Postal Code</p>
<div><b>11564</b><b>
</b></div></div></ul></div><div><h3 class="jobSectionHeader"><b>About Us</b></h3>
<div><div>Raqmiyat is a UAE-based IT and digital transformation company specializing in consulting, staffing, and enterprise technology solutions. We empower banking, government, and enterprise clients across the Middle East to achieve their digital objectives.</div><br>
</div><p></p><h3 class="jobSectionHeader"><b>Job Description</b></h3>
<div><div>Job Overview:<br>
</div><div>
We are looking for a motivated and innovative <b>Artificial Intelligence Engineer</b> with <b>3+ years of experience</b> in designing, developing, and deploying AI/ML solutions. The ideal candidate should have hands-on experience in <b>machine learning, data modeling, Python programming, and AI solution development</b>, with the ability to transform business requirements into intelligent systems and predictive models.<br>
<br>
</div><div></div><br>
<p><b>Key Responsibilities:</b></p><br>
<ul><li>
Design, develop, and deploy <b>AI and machine learning models</b> for business use cases.<br>
</li><li>
Build and optimize <b>predictive, classification, and recommendation models</b>.<br>
</li><li>
Work with large datasets to perform <b>data preprocessing, feature engineering, and model training</b>.<br>
</li><li>
Develop AI-driven solutions using <b>Python and machine learning frameworks</b>.<br>
</li><li>
Evaluate model performance and improve accuracy through tuning and validation techniques.<br>
</li><li>
Collaborate with stakeholders to understand business problems and translate them into AI use cases.<br>
</li><li>
Integrate AI models into applications, dashboards, or enterprise systems.<br>
</li><li>
Monitor deployed models and ensure continuous performance improvement.<br>
</li><li>
Prepare technical documentation and support ongoing enhancements.</li></ul><div></div><h3 class="jobSectionHeader"><b><br>
Requirements</b></h3><ul><li>
3+ years of experience in <b>Artificial Intelligence / Machine Learning Engineering</b><br>
</li><li>
Strong proficiency in <b>Python</b><br>
</li><li>
Hands-on experience with <b>machine learning algorithms and model development</b><br>
</li><li>
Experience with libraries such as <b>TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy</b><br>
</li><li>
Good understanding of <b>data structures, statistics, and predictive analytics</b><br>
</li><li>
Experience in <b>data cleaning, feature engineering, and model evaluation</b><br>
</li><li>
Knowledge of <b>SQL and database management</b><br>
</li><li>
Strong problem-solving and analytical skills</li></ul></div></div></div><p></p>

Artificial Intelligence Engineer

Kaycha Labs

<div><p><b>About NodePlus</b></p><p>
NodePlus is an enterprise artificial intelligence operating system built for regulated industries. We are an application factory with a connector layer architecture that lets large organizations ship AI-native software at the speed of a startup and the rigor of an enterprise. Our live proof of concept is Kaycha Labs, a nine-state cannabis testing network, where NodePlus runs production workloads across operations, sales, compliance, and finance. We are a small team building a serious platform. We are funded, post-revenue, and currently raising a $50 million round to scale.</p><p>
</p><p><b>The Role</b></p><p>
We are hiring our next AI Engineer. You will own features end-to-end, from data model to deployed UI, with a particular emphasis on the AI systems that make NodePlus a category-defining product. You will work directly with the CEO/CTO and have outsized influence on our architecture, our hiring bar, and our product direction. You will ship in week one. You will own systems that customers depend on. You will build the evals before the features.</p><p>
</p><p><b>What You Bring:</b></p><p>
</p><p><b>Core Engineering</b></p><ul><li>Python 3.11 or newer, with FastAPI, async patterns, Pydantic, and pytest</li><li>TypeScript with Next.js 16 App Router, React 19 (including use() and Actions), Tailwind 4, and shadcn/ui</li><li>SQL and Postgres at depth, including schema design, Supabase Row-Level Security, migrations, window functions, and pgvector</li><li>Cloudflare Workers, including edge functions, Durable Objects, KV, and R2</li><li>Git and GitHub workflow discipline, trunk-based development, clean PRs, and CI via GitHub Actions</li></ul><p>
</p><p><b>AI and LLM Systems</b></p><ul><li>Production experience with LLM APIs across Anthropic (Claude 4.x), OpenAI (o-series), Google (Gemini), xAI (Grok), and DeepSeek</li><li>Prompt caching, tool use, structured output, and streaming via Server-Sent Events at production grade, not demo grade</li><li>RAG systems built end-to-end: chunking strategy, embeddings, metadata filtering, reranking, and evaluation</li><li>Vector databases, with ChromaDB as primary and pgvector as secondary</li><li>Embeddings model selection (such as snowflake-arctic-embed2) with a clear understanding of cost-quality tradeoffs</li><li>Ollama deployment at scale, including model quantization, context window tuning, and multi-GPU layouts</li><li>Fine-tuning with QLoRA or LoRA via Unsloth or Axolotl, including dataset curation</li><li>Model Context Protocol (MCP), including writing servers and registering them with Claude Code or Claude Desktop</li><li>Evaluation discipline: offline and online evals, with the standing rule that no AI feature ships without one</li></ul><p>
</p><p><b>Infrastructure and Operations</b></p><ul><li>Docker and docker-compose, Linux services via systemd, Windows services via NSSM and PM2</li><li>PowerShell 5.1 and 7, plus bash. Our fleet is Windows-heavy with Linux servers; you need to be fluent on both</li><li>Tailscale or WireGuard, SSH mesh networking, MeshCentral helpful</li><li>Monitoring with Prometheus, Grafana, or equivalent</li></ul><p>
</p><p><b>Product Sense</b></p><ul><li>You can ship a working feature end-to-end without hand-holding</li><li>You write the eval before the feature</li><li>You know when not to use an LLM, because deterministic code beats a prompt</li><li>You debug hallucinations by fixing retrieval, not by stacking more prompts</li></ul><br>
<p><b>How We Work</b></p><p>
Small team. Direct communication. Trunk-based. We measure shipping velocity and customer outcomes, not lines of code. We use AI tools aggressively in our own workflow because we believe in our product. We have strong opinions, weakly held, and we change them when the data says so.</p><p>
</p><p><b>What We Offer</b></p><ul><li>Meaningful equity in a company with real revenue and a serious enterprise wedge</li><li>Direct access to the CEO/CTO and to customers</li><li>Modern tooling and the budget to use it</li><li>The chance to build the operating system that the next generation of regulated enterprises will run on</li></ul><p>
</p><p><b>How to Apply</b></p><p>
To apply, email our CEO directly at <b>james@nodeplus.ai and cc careers@kaychalabs.com</b> with your GitHub, a link to something you have shipped that you are proud of, and one paragraph on the AI feature you would build first if you joined. We read every application and respond within five business days.</p></div>

OpenArc, LLC.

<div>
 <p>
  OpenArc - Empowering Your Career. As a leading IT staffing firm, we are dedicated to connecting talented professionals with your ideal opportunities. We are currently seeking a qualified AI Engineer to join our client&rsquo;s organization and contribute to their ongoing success.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Job summary
 </p>
 <p>
  The AI Engineer will be responsible for designing, building, deploying, certifying, and maintaining production-grade generative AI and agentic business and technology solutions.
 </p>
 <p>
  Responsibilities:
 </p>
 <ul>
  <li>
   Advance the organization&rsquo;s AI strategy with a strong emphasis on identifying high- value opportunities, defining technical roadmaps, prioritizing use cases, and advocating for responsible, extensible and scalable IA adoption.
  </li>
  <li>
   Collaborate with business and IT stakeholders to deeply understand current state processes and workflows in order to deliver AI powered solutions that deliver high-impact solutions driving measurable operational efficiency and transformation.
  </li>
  <li>
   Lead the full stack end-to-end development of custom AI solutions leveraging knowledge of MLOps, context management, and CICD practices to orchestrate AI agents and technology (e.g., Copilot AI, Snowflake AI, GitHub AI, AWS Bedrock, etc).
  </li>
  <li>
   Design, create, and implement reusable AI frameworks, prompt templates, reference architecture, and reference architectures to accelerate AI solution delivery across teams.
  </li>
  <li>
   Support the model evaluation, testing, and certification process: red-teaming, bias/fairness testing, accuracy benchmarking, hallucination detection, content safety filtering, and production readiness sign-off in regulated environments.
  </li>
  <li>
   Establish and enforce responsible AI governance practices, including aligning to the NIST AI Risk Management Framework.
  </li>
  <li>
   Collaborate with cloud, data and security architecture teams to build secure, extensible solutions
  </li>
  <li>
   Stay current with the latest capabilities in current and emerging AI agentic technology and frameworks.
  </li>
  <li>
   Experiment with alternative AI models and enhance the overall AI technology capabilities.
  </li>
  <li>
   Provide guidance on feasibility, risks and expected business impacts of AI initiatives.
  </li>
  <li>
   Draft clear documentation for AI models, data flows, AI solutions, APIs and operational procedures.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  Requirements:
 </p>
 <ul>
  <li>
   Experience in software engineering, data science, or related technical roles, with strong proficiency in coding, business and system design, and production deployment.
  </li>
  <li>
   Experience building and deploying generative AI solutions in enterprise environments
  </li>
  <li>
   Proficient in backend development using AI algorithms. Python, Java, Shell, Linux or Node.js, MCP, APIs, knowledge graphs, vector databases, &amp; data structures
  </li>
  <li>
   Demonstrated knowledge of MLOps, model lifecycle, and (CI/CD) practices.
  </li>
  <li>
   Designed and implemented full-stack AI solutions using modern MLOps and AI frameworks (e.g RAG) and platforms such as GitHub Agent, Snowflake agents, Copilot Studio and AWS Bedrock.
  </li>
  <li>
   Created reusable frameworks, prompt templates, and reference architectures to accelerate AI solution delivery across teams.
  </li>
  <li>
   Knowledge of Bank business applications is a plus
  </li>
  <li>
   Knowledge of data query, analysis, and scanning tools and techniques
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  At OpenArc, we prioritize your career success and strive to build exceptional technical teams for our clients. By understanding your experience and aspirations, we ensure to present you with rewarding and fulfilling opportunities.
 </p>
 <p>
  <br/>
 </p>
 <p>
  As an employee of OpenArc and our clients, you will be eligible to participate in a comprehensive benefits package.
 </p>
 <p>
  <br/>
 </p>
 <p>
  OpenArc is an equal opportunity employer and will consider all applications without regards to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.
 </p>
</div>


Latcha

<div>
 <p>
  <strong>
   About the Company
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  Latcha+Associates focuses on automotive marketing with full service capabilities in Farmington Hills, Michigan. We are Investing in growing our data and AI team focused on developing innovative solutions that enhance marketing performance, client personalization, and internal automation.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   About the Role
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  This is a hybrid role, and our office is located in Farmington Hills, Michigan.
 </p>
 <p>
  We are seeking an AI/ML Engineer to join our growing data and AI team. This individual will be responsible for developing, deploying, and scaling AI-powered solutions that directly impact marketing performance, client personalization, and internal automation. You will work closely with our data engineering team to leverage our existing data platform, and with business stakeholders to build AI agents and applications that deliver measurable business value. This role is both hands-on and strategic &mdash; ideal for someone who can rapidly prototype with LLMs and machine learning models, while also designing robust pipelines for training, retraining, and production deployment.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Responsibilities
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   <strong>
    AI Agent Development:
   </strong>
   Build and deploy AI agents that automate workflows, content creation, campaign optimization, and internal decision support.
  </li>
  <li>
   <strong>
    LLM Engineering:
   </strong>
   Train, fine-tune, and retrain large language models (LLMs) on proprietary data; manage model evaluation and continuous improvement.
  </li>
  <li>
   <strong>
    Data Integration:
   </strong>
   Work with data engineers to access and preprocess structured and unstructured data from Delta tables, APIs, and external sources.
  </li>
  <li>
   <strong>
    MLOps &amp; Deployment:
   </strong>
   Implement scalable pipelines for model training, deployment, monitoring, and retraining using modern MLOps practices.
  </li>
  <li>
   <strong>
    Prototype &rarr; Production:
   </strong>
   Rapidly build proofs-of-concept, then transition validated models into production systems.
  </li>
  <li>
   <strong>
    Collaboration:
   </strong>
   Partner with analysts, engineers, and business stakeholders to identify use cases, define success metrics, and deliver end-to-end AI solutions.
  </li>
  <li>
   <strong>
    Research &amp; Innovation:
   </strong>
   Stay current with emerging AI/ML techniques, frameworks, and tools.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Required Qualifications:
  </strong>
 </p>
 <ul>
  <li>
   3&ndash;6 years of experience in applied machine learning or AI engineering.
  </li>
  <li>
   Proficiency in Python with strong experience in ML/AI frameworks (PyTorch, TensorFlow, Hugging Face).
  </li>
  <li>
   Experience working with LLMs (training, fine-tuning, prompt engineering, RAG).
  </li>
  <li>
   Familiarity with MLOps tools (MLflow, Databricks, etc.).
  </li>
  <li>
   Strong SQL and data engineering fundamentals; ability to work with large datasets.
  </li>
  <li>
   Hands-on experience deploying AI solutions into production in a cloud environment; experience with Azure DevOps/GitHub Actions a plus.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Preferred/Nice-to-Have:
  </strong>
 </p>
 <ul>
  <li>
   Experience in marketing tech, ad tech, or personalization systems &ndash; automotive a big plus.
  </li>
  <li>
   Familiarity with LangChain, LlamaIndex, RAG pipelines, and vector databases (Pinecone, Weaviate, FAISS, etc.).
  </li>
  <li>
   Deep working knowledge of cloud platforms, ideally Azure Databricks.
  </li>
  <li>
   Strong understanding of model governance, bias, and ethical AI considerations.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What Success In This Role Looks Like:
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Within 3 months: You&rsquo;ve delivered a working AI prototype (e.g., an agent that generates campaign briefs or automates audience creation).
  </li>
  <li>
   Within 6 months: You&rsquo;ve deployed at least one AI/ML system into production, with monitoring and retraining in place.
  </li>
  <li>
   Within 12 months: You&rsquo;re leading the design of scalable AI capabilities, driving measurable revenue or efficiency gains for the business.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Work Location
  </strong>
  :
  <strong>
   In person at our office in Farmington Hills, MI
  </strong>
  . Must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future. Latcha+Associates will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa).
 </p>
 <p>
  <strong>
   Equal Opportunity Statement
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  We are committed to diversity and inclusivity in our hiring practices.
 </p>
 <p>
 </p>
</div>


YO IT Consulting

<div>
 <strong>
  Job Title:
 </strong>
 AI/ML Engineer
 <br/>
 <br/>
 <strong>
  Job Type:
 </strong>
 Full-Time
 <br/>
 <br/>
 <strong>
  Job Summary
  <br/>
  <br/>
 </strong>
 Join our team as a AI/ML Engineer and play a pivotal role in driving mission-critical government initiatives while also contributing to proprietary AI infrastructure, you&rsquo;ll harness advanced large language models (LLMs), retrieval-augmented generation (RAG), and multi-agent orchestration to deliver secure, scalable, and impactful machine learning systems. You&rsquo;ll work closely with cross-functional experts, leveraging frontier AI platforms and the latest in agentic AI tooling.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design, implement, and optimize AI/ML models particularly leveraging LLMs, RAG, and prompt engineering for production grade applications.
  </li>
  <li>
   Develop and orchestrate multi-agent systems using frameworks such as LangGraph and LangChain.
  </li>
  <li>
   Integrate and deploy solutions on secure cloud environments, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
  </li>
  <li>
   Build robust data pipelines, manage ETL processes, and develop metadata catalogs and ontologies to ensure high-quality data for AI training and inference.
  </li>
  <li>
   Create and maintain REST APIs and SDK integrations to facilitate seamless data and model interactions.
  </li>
  <li>
   Collaborate with product, security, and engineering teams to ensure best-in-class delivery, following secure coding and DevOps best practices (CI/CD).
  </li>
  <li>
   Document technical decisions and communicate complex concepts clearly to both technical and non-technical stakeholders.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Skills And Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Proficiency in Python for AI/ML development, including experience with REST APIs and SDK integration.
  </li>
  <li>
   Hands-on experience with LLMs, RAG systems, and prompt engineering in production environments.
  </li>
  <li>
   Familiarity with multi-agent orchestration, tool use, and frameworks like LangGraph and LangChain.
  </li>
  <li>
   Deep understanding of cloud AI services (AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, AWS Bedrock).
  </li>
  <li>
   Background in building and maintaining data pipelines, ontologies, metadata catalogs, and ETL processes.
  </li>
  <li>
   Strong grasp of secure coding and modern DevOps practices (CI/CD pipelines).
  </li>
  <li>
   Exceptional written and verbal communication skills for effective collaboration and documentation.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience with AI/agentic platforms, such as Anthropic for Gov, OpenAI Enterprise, Gemini Enterprise, or Grok Enterprise.
  </li>
  <li>
   Knowledge of metadata catalog platforms (MCP) and advanced API development techniques.
  </li>
  <li>
   Prior exposure to government or highly regulated cloud environments and compliance standards.
  </li>
 </ul>
</div>


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