it support engineer

o&m engineer

ai applications engineer

ai architect

assistant o&m engineer

ai engineer

Treasury Cube

<div>
 About Treasury Cube
 
 Treasury Cube is a modern Treasury Management System (TMS) helping corporate treasury teams take control of cash, payments, bank connectivity, in-house banking, and FX exposure. We're building a platform that turns the daily grind of treasury operations, bank statement processing, cash positioning, intercompany settlements, payment workflows into something faster, smarter, and decision ready.
 
 
 We're now embedding AI deeply into the platform to give treasurers the kind of insight, automation, and conversational access that legacy TMS vendors simply can't deliver. This is where you come in.
 
 
 The Role
 
 We're looking for an
 
 AI Engineer
 
 to lead the design and delivery of AI capabilities across Treasury Cube. You'll own the AI engineering stack end-to-end from model orchestration on
 
 Azure AI
 
 , to retrieval pipelines over treasury data, to the production systems that put insights and automation in front of CFOs and treasurers every day.
 
 
 
 
 
 This is a hands-on, build-from-the-ground-up role. You'll shape architecture, set patterns, and ship features customers actually use within weeks, not quarters.
 
 
 What You'll Build
 <ul>
 <li>
 
 AI Insights Engine:
 
 Generate explanatory commentary and recommendations on cash positions, FX exposures, payment anomalies, forecast variances, and intercompany flows. Think: turning a 12-bank, 8-currency cash dashboard into a one-paragraph "here's what changed and why" briefing.
 </li>
 <li>
 
 AI Chatbox / Conversational Treasury Assistant:
 
 A natural-language interface where users can ask "what's my USD position next Friday?" or "show me payments held up in approval over $500K" and get accurate, grounded answers backed by the underlying treasury data.
 </li>
 <li>
 
 AI-Based Task &amp; Notification Automation:
 
 Intelligent routing, prioritization, and summarization of alerts (covenant breaches, sweep failures, payment exceptions, hedge effectiveness drift). Auto-generated tasks with context, suggested actions, and assignment logic.
 </li>
 <li>
 
 Monitoring &amp; Observability for AI Systems
 
 : Token usage, latency, hallucination detection, prompt regression, cost-per-customer tracking, and human-in-the-loop feedback pipelines. If we can't measure it, we won't trust it in front of treasurers.
 
 </li>
 </ul>
 What We're Looking For
 
 
 Must-haves:
 
 
 <ul>
 <li>
 3+ years of software engineering experience, with at least 1&ndash;2 years building production LLM or AI applications
 </li>
 <li>
 
 Strong, hands-on experience with the Azure AI stack
 
 Azure OpenAI Service, Azure AI Foundry, Azure AI Search (vector + hybrid retrieval), Azure AI Document Intelligence, and Azure Content Safety
 </li>
 <li>
 Solid grasp of
 
 RAG architectures
 
 , prompt engineering, function/tool calling, structured outputs, and evaluation frameworks
 </li>
 <li>
 Experience designing
 
 agentic workflows
 
 and multi-step automation (Azure Functions, Logic Apps, Durable Functions, or equivalent)
 </li>
 <li>
 Strong backend engineering fundamentals Python and/or C#/.NET, REST APIs, async patterns, SQL
 </li>
 <li>
 Production mindset: you think about cost, latency, observability, prompt versioning, and graceful degradation from day one
 </li>
 </ul>
 
 
 Nice to have:
 
 
 <ul>
 <li>
 Experience in FinTech, Treasury, ERP, or financial data domains
 </li>
 <li>
 Familiarity with ISO 20022 (CAMT, PAIN), SWIFT, or banking integrations
 </li>
 <li>
 Background in MLOps / LLMOps (Azure ML, Prompt Flow, model evaluation pipelines)
 </li>
 <li>
 Hands-on with Semantic Kernel, LangChain, or LlamaIndex
 </li>
 <li>
 Experience with multi-tenant SaaS architectures and data isolation patterns
 </li>
 </ul>
 
 
 
 Why Join Treasury Cube
 <ul>
 <li>
 
 Real ownership.
 
 You'll be the AI lead, not the third engineer on a team of fifteen. Architecture decisions you make this quarter will shape the platform for years.
 </li>
 <li>
 
 A domain that rewards intelligence.
 
 Treasury data is structured, high-stakes, and underserved by AI. The problems are genuinely hard, and the wins are visible to CFOs the day you ship.
 </li>
 <li>
 
 Fast feedback loops.
 
 Small customer base today (early-stage), which means you'll talk to actual users, see your features in production within weeks, and iterate based on real treasurer feedback.
 </li>
 <li>
 
 Work that compounds.
 
 Every insight, automation, and chatbox capability you ship becomes part of a platform that scales across customers not a one-off engagement.
 </li>
 </ul>
 
 
 
 How to Apply
 
 Send your CV, GitHub or portfolio (if relevant), and a short note on
 
 one production AI system you've built
 
 what it does, what you'd change, and why to
 
 HR@treasurycube.com
 
 .
 
 
 Bonus points if you include thoughts on how you'd approach building a treasury AI assistant that earns the trust of a CFO.
 
</div>

AI Engineer

Qureos

AI Engineer Company:** Qureos Location:** Karachi, Pakistan Employment Type:** Full-Time About Qureos Qureos is a dynamic and forward-thinking organisation dedicated to shaping the future of career development. We are committed to empowering professionals by connecting them with meaningful opportunities, mentorship, and the skills needed to thrive in a competitive landscape. Our innovative platform leverages technology to bridge the gap between talent and industry, and we are now seeking a talented AI Engineer to join our pioneering team. Job Overview We are looking for a highly skilled and motivated AI Engineer to join our team in Karachi. The ideal candidate will be passionate about artificial intelligence and its application in solving real-world challenges. You will play a crucial role in designing, developing, and deploying cutting-edge AI and machine learning models that power our platform's core features, from intelligent job matching and skill analysis to personalised career guidance. This is an exciting opportunity to make a significant impact within a growing company at the forefront of the EdTech and recruitment industries. Responsibilities - Design, build, and deploy robust machine learning models to enhance our platform's capabilities. - Develop and refine recommendation systems to accurately match candidates with relevant job opportunities, projects, and mentors. - Utilise Natural Language Processing (NLP) techniques to analyse and interpret data from resumes, job descriptions, and user interactions. - Collaborate with cross-functional teams, including software engineers, product managers, and data scientists, to integrate AI solutions into our products. - Manage the end-to-end lifecycle of AI models, including data collection, preprocessing, training, evaluation, and deployment. - Stay current with the latest advancements in AI, machine learning, and deep learning to drive continuous innovation. - Ensure the ethical and responsible use of AI, maintaining fairness and avoiding bias in all models. - Optimise AI models for performance, scalability, and efficiency. Qualifications - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field. - Proven commercial experience as an AI Engineer, Machine Learning Engineer, or in a similar role. - Strong programming proficiency in Python and extensive experience with key AI/ML libraries such as TensorFlow, PyTorch, and scikit-learn. - Solid understanding of machine learning algorithms, deep learning, NLP, and statistical modelling. - Experience with data processing and analysis using tools like Pandas and NumPy. - Familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) and MLOps practices is highly desirable. - Excellent problem-solving abilities and a creative, analytical mindset. - Strong communication skills and the ability to work effectively in a collaborative team environment. Benefits - A competitive salary and comprehensive benefits package. - Opportunities for professional development and continuous learning. - A vibrant and supportive work culture that encourages innovation and collaboration. - The chance to work on meaningful projects that directly impact people's careers. - Flexible and modern working environment.

Digitrends

AI EngineerKey Responsibilities<ul><li>Design, develop, and fine-tune LLM-based AI models for real-world applications.</li><li>Implement custom LLM training, reinforcement learning, and fine-tuning using open-source and proprietary models like GPT, Llama, Mistral, Claude, or Falcon.</li><li>Optimize model efficiency, inference speed, and resource utilization for deployment in cloud or on-premise environments.</li><li>Build data pipelines for training and evaluating AI models.</li><li>Implement prompt engineering, retrieval-augmented generation (RAG), and memory-based techniques for improved performance.</li><li>Integrate LLMs into applications using APIs, LangChain, vector databases (e.g., Pinecone, FAISS, ChromaDB).</li><li>Develop custom embeddings, transformers, and tokenization strategies for specific use cases.</li><li>Work closely with MLOps, backend engineers, and data scientists to ensure smooth deployment and monitoring of AI solutions.</li><li>Research and stay updated on emerging trends in NLP, generative AI, and model compression techniques.</li><li>Ensure compliance with ethical AI principles and data security standards when handling sensitive data.</li></ul>Required Skills:<ul><li>Strong knowledge of Python and frameworks like PyTorch, TensorFlow, JAX.</li><li>Experience with Hugging Face Transformers, OpenAI API, LangChain, and vector databases.</li><li>Understanding of LLM architectures, fine-tuning techniques (LoRA, QLoRA, PEFT), and model distillation.</li><li>Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).</li><li>Familiarity with distributed computing, GPU acceleration (CUDA, TensorRT), and multi-node training.</li><li>Knowledge of AI safety, bias mitigation, and responsible AI development.</li><li>Strong problem-solving, debugging, and optimization skills.</li><li>Excellent communication and teamwork skills.</li></ul>Preferred Qualifications<ul><li>Experience in building domain-specific AI assistants or chatbots.</li><li>Knowledge of multimodal AI, speech-to-text, text-to-image models.</li><li>Contributions to open-source AI projects or research papers in NLP/LLMs.</li></ul>Key Benefits<ul><li>Working in a fast-paced tech start-up environment</li><li>Attractive salary and incentives for high-quality work</li><li>Flexible schedule</li><li>Health Insurance</li><li>Five Working Days</li><li>Provident Fund</li></ul>Job Type: Full-timeWork Location: In person

Confiz

<div>We are seeking an exceptional Senior AI Engineer to join our team and drive the development of cutting-edge AI solutions that includes conversational, Agentic AI's. This role focuses on building advanced conversational AI systems, implementation AI Agents across different use cases, implementing sophisticated RAG architectures, and deploying production-grade voice AI applications. The ideal candidate will have deep expertise in LLM technologies and a proven track record of delivering scalable AI solutions.
Key Responsibilities
<ul><li>Design and implement advanced Retrieval-Augmented Generation (RAG) systems with sophisticated chunking strategies, multi-vector retrieval, and hybrid search architectures</li>
<li>Develop and optimize conversational AI agents with complex multi-turn dialogue management and context awareness</li>
<li>Build production-ready voicebot solutions integrating real-time speech processing pipelines</li>
<li>Architect and deploy Text-to-Speech (TTS) and Speech-to-Text (STT) systems with low latency and high accuracy</li>
<li>Design and Deploy PROD grade AI Agents that can scale up for various use cases.</li>
<li>Fine-tune large language models using various techniques.</li>
<li>Optimize model performance through prompt engineering, few-shot learning, and retrieval strategies</li>
<li>Implement evaluation frameworks and metrics for LLM outputs and conversational quality</li>
<li>Develop custom training pipelines for domain adaptation and specialized use cases</li>
<li>Design scalable AI infrastructure supporting real-time inference and high-throughput batch processing</li>
<li>Implement efficient vector databases and semantic search systems (Pinecone, Azure Search)</li>
<li>Build monitoring and observability solutions for AI systems in production</li>
<li>Stay current with latest developments in LLM architectures, RAG techniques, and voice AI technologies</li>
<li>Experiment with emerging models and frameworks to evaluate applicability to business problems</li>
<li>Contribute to technical documentation, best practices, and knowledge sharing within the team</li>
<li>Prototype and validate new AI capabilities through POCs and pilots</li>
</ul>
Required Qualifications
<ul><li>5+ years of software engineering experience with 4+ years focused on AI/ML engineering</li>
<li>Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow)</li>
<li>Master's or PhD in Computer Science, AI/ML, or related technical field</li>
<li>Experience with open-source LLMs (Llama, Mistral, etc.) and local deployment</li>
<li>Knowledge of reinforcement learning from human feedback (RLHF) and DPO</li>
<li>Familiarity with multi-modal AI systems (vision-language models, audio-visual understanding)</li>
<li>Experience with real-time streaming architectures and WebRTC</li>
<li>Published research or contributions to open-source AI projects</li>
<li>Experience with GPU optimization and distributed training</li>
<li>Knowledge of voice biometrics, speaker diarization, or emotion recognition</li>
<li>Background in linguistics, phonetics, or speech processing</li>
<li>Deep hands-on experience with advanced RAG systems:</li>
<li>Multi-stage retrieval architectures (hybrid search, re-ranking)</li>
<li>Embedding models and vector similarity search</li>
<li>Document processing, chunking strategies, and metadata filtering</li>
<li>Query understanding and retrieval optimization</li>
<li>Multi-turn dialogue management</li>
<li>Intent recognition and slot filling</li>
<li>Context tracking and memory management</li>
<li>Integration with LLM APIs (OpenAI, Anthropic, Cohere, etc.)</li>
<li>Production experience with voicebot development:</li>
<li>Real-time audio streaming and processing</li>
<li>Voice activity detection (VAD)</li>
<li>End-to-end latency optimization</li>
<li>Integration of STT, dialogue management, and TTS components</li>
<li>Expertise in TTS and STT technologies:</li>
<li>Modern TTS systems (ElevenLabs, Soniox, Azure Speech)</li>
<li>STT engines ( Deepgram, AssemblyAI)</li>
<li>Audio preprocessing and enhancement</li>
<li>Voice cloning and customization</li>
<li>Strong experience with LLM fine-tuning:</li>
<li>Proficiency with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)</li>
<li>Experience with MLOps tools and practices (MLflow, Weights &amp; Biases, experiment tracking)</li>
<li>Strong understanding of API design, microservices architecture, and system integration</li>
<li>Knowledge of version control, CI/CD pipelines, and deployment automation</li>
</ul>
We have an amazing team of 700+ individuals working on highly innovative enterprise projects &amp; products. Our customer base includes Fortune 100 retail and CPG companies, leading store chains, fast-growth fintech, and multiple Silicon Valley startups.
What makes Confiz stand out is our focus on processes and culture. Confiz is ISO 9001:2015 (QMS), ISO 27001:2022 (ISMS), ISO 20000-1:2018 (ITSM), ISO 14001:2015 (EMS), ISO 45001:2018 (OHSMS) Certified. We have a vibrant culture of learning via collaboration and making workplace fun.
People who work with us work with cutting-edge technologies while contributing success to the company as well as to themselves.
To know more about Confiz Limited, visit: https://www.linkedin.com/company/confiz-pakistan/</div>

Senior AI Engineer

Pivotize Consulting

Job Overview We aare in search of an experienced AI Engineer who will work as part of a diverse team of software engineers, data scientists, and machine learning (ML) experts to develop new models and algorithms to apply artificial intelligence to solve real-world problems and change the future.In this role, your curiosity and deep interest in AI, machine learning, and keeping pace with a rapidly evolving field will guide your path. You will delve into extensive data sets, identify patterns, and craft predictive algorithmic models, contributing to innovative projects.Responsibilities: . Design and develop cutting-edge AI solutions and systems that integrate with our products and services. . Implementing AI solutions using programming languages such as Python, R, Java, or C++, along with relevant frameworks and libraries like TensorFlow, PyTorch, or scikit-learn. . Collecting, preprocessing, and analyzing large volumes of data to train AI models. This may involve data cleaning, feature engineering, and exploratory data analysis. . Deploying AI models into production environments and integrating them with existing systems and applications. This may involve containerization, microservices architecture, and cloud computing platforms. . Conduct thorough testing and evaluation of AI systems to ensure they meet performance, reliability, and security standards. . Conduct research and experiments to improve the performance of AI systems. . Monitor the performance of AI systems and make recommendations for improvements. . Stay up-to-date with advancements in AI technologies and make recommendations for future development.Requirements: . Degree in Computer science, Information technology, or a related field. 4+ years of experience with strong programming skills in Python, R, MATLAB, or other relevant programming languages. . Deep understanding of data science, linear algebra, algorithms, and statistics. . Experience working with large data sets and writing efficient code capable of processing large data streams at speed . Familiarity with deep learning and machine learning algorithms and the use of popular AI/ML framework. . Excellent communication skills.Job Type: Full-timePay: From Rs250,000.00 per monthApplication Question(s):<ul><li>What is your current salary?</li><li>What is your expected salary?</li><li>What is your notice period?</li><li>Are you able to commute to Bahria Complex 1, Lalazar, M.T. Khan Road for onsite interview &amp; job? </li></ul>It's mandatory to be available on-site. No Freelance or Remote option / No online interviews &amp; assessment.Work Location: In person

Sr. Artificial Intelligence (AI) Engineer

DM Clinical Research

<div>We are seeking an AI Applications Engineer with deep expertise in AI systems development to join our engineering team. In this role, you&rsquo;ll bridge the gap between ML research and real-world software delivery &mdash; designing, developing, and deploying intelligent applications powered by modern AI technologies including LLMs, multimodal models, and agentic workflows. You'll work closely with data scientists, ML engineers, and product managers to ship cutting-edge, scalable AI-powered features across web, backend, and mobile platforms. 
DUTIES &amp; RESPONSIBILITIES<ul><li>
Design and build AI-native applications leveraging LLMs (e.g., OpenAI, Anthropic, Mistral) and multimodal models.</li><li>
Architect and implement agent-based workflows using frameworks like LangGraph, CrewAI, and AutoGen.</li><li>
Develop production-grade Python services using FastAPI or similar frameworks to expose AI functionalities via APIs.</li><li>
Fine-tune and serve custom LLMs for text, voice, and multimodal inputs; implement Retrieval-Augmented Generation (RAG) pipelines.</li><li>
Integrate vector search systems (e.g., Weaviate, Qdrant, Pinecone) for semantic memory and contextual reasoning.</li><li>
Use modern orchestration tools like LangChain, Flowise, Haystack, or n8n to prototype and scale intelligent flows.</li><li>
Leverage the OpenAI Function Calling / Tools API and Model Context Protocol (MCP) to build structured, dynamic LLM interactions.</li><li>
Implement continuous evaluation loops using synthetic data, human feedback (RLHF), and evaluation frameworks like Ragas or DeepEval.</li><li>
Collaborate with ML/infra teams to containerize, deploy, and monitor models using tools like Docker, MLflow, BentoML, or Kubernetes.</li><li>
Build scalable, secure, and efficient AI feature delivery pipelines across web and mobile platforms.</li><li>
Stay current with developments in foundation models, agent frameworks, multimodal AI, and open-source toolkits.</li></ul>
KNOWLEDGE &amp; EXPERIENCE
Education:<ul><li>
Bachelor's or Master&rsquo;s degree in Computer Science, Software Engineering, Artificial Intelligence, or related discipline.</li></ul>
Experience:<ul><li>
2&ndash;4 years of experience building and deploying AI/ML-powered software.</li><li>
Proven track record of delivering LLM-integrated applications and/or agentic workflows in production.</li><li>
Experience in any of the following domains is a plus: NLP, computer vision, multimodal models, or conversational AI.</li></ul>
Knowledge and Skills:<ul><li>
Proficient in Python and building production-grade RESTful APIs (FastAPI preferred).</li><li>
Experience working with foundation model APIs (OpenAI, Claude, Gemini, Mistral, Cohere).</li><li>
Familiarity with LangChain, LangGraph, CrewAI, Flowise, or similar frameworks.</li><li>
Experience implementing RAG pipelines and retrieval layers with vector databases (Pinecone, Qdrant, Weaviate, FAISS).</li><li>
Understanding of prompt engineering, structured memory (MCP), tool calling, and multi-turn conversation flows.</li><li>
Comfortable with tools like MLflow, Weights &amp; Biases, or BentoML for model versioning and tracking.</li><li>
Ability to integrate with third-party services, RESTful APIs, and webhooks (Zapier, n8n, etc.).</li><li>
Familiarity with MLOps and CI/CD workflows for AI applications.</li><li>
Experience working with containerized environments (Docker, Kubernetes).</li><li>
Git, agile software development practices, and collaborative code workflows.</li><li>
Experience with speech recognition (Whisper), text-to-speech (ElevenLabs), or multimodal APIs (e.g., GPT-4o).</li></ul></div>

AI Applications Engineer

<div>We are seeking an exceptional Senior AI Engineer to join our team and drive the development of cutting-edge AI solutions that includes conversational, Agentic AI's. This role focuses on building advanced conversational AI systems, implementation AI Agents across different use cases, implementing sophisticated RAG architectures, and deploying production-grade voice AI applications. The ideal candidate will have deep expertise in LLM technologies and a proven track record of delivering scalable AI solutions.
Key Responsibilities
<ul><li>Design and implement advanced Retrieval-Augmented Generation (RAG) systems with sophisticated chunking strategies, multi-vector retrieval, and hybrid search architectures</li>
<li>Develop and optimize conversational AI agents with complex multi-turn dialogue management and context awareness</li>
<li>Build production-ready voicebot solutions integrating real-time speech processing pipelines</li>
<li>Architect and deploy Text-to-Speech (TTS) and Speech-to-Text (STT) systems with low latency and high accuracy</li>
<li>Design and Deploy PROD grade AI Agents that can scale up for various use cases.</li>
<li>Fine-tune large language models using various techniques.</li>
<li>Optimize model performance through prompt engineering, few-shot learning, and retrieval strategies</li>
<li>Implement evaluation frameworks and metrics for LLM outputs and conversational quality</li>
<li>Develop custom training pipelines for domain adaptation and specialized use cases</li>
<li>Design scalable AI infrastructure supporting real-time inference and high-throughput batch processing</li>
<li>Implement efficient vector databases and semantic search systems (Pinecone, Azure Search)</li>
<li>Build monitoring and observability solutions for AI systems in production</li>
<li>Stay current with latest developments in LLM architectures, RAG techniques, and voice AI technologies</li>
<li>Experiment with emerging models and frameworks to evaluate applicability to business problems</li>
<li>Contribute to technical documentation, best practices, and knowledge sharing within the team</li>
<li>Prototype and validate new AI capabilities through POCs and pilots</li>
</ul>
Required Qualifications
<ul><li>8+ years of software engineering experience with 4+ years focused on AI/ML engineering</li>
<li>Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow)</li>
<li>Master's or PhD in Computer Science, AI/ML, or related technical field</li>
<li>Experience with open-source LLMs (Llama, Mistral, etc.) and local deployment</li>
<li>Knowledge of reinforcement learning from human feedback (RLHF) and DPO</li>
<li>Familiarity with multi-modal AI systems (vision-language models, audio-visual understanding)</li>
<li>Experience with real-time streaming architectures and WebRTC</li>
<li>Published research or contributions to open-source AI projects</li>
<li>Experience with GPU optimization and distributed training</li>
<li>Knowledge of voice biometrics, speaker diarization, or emotion recognition</li>
<li>Background in linguistics, phonetics, or speech processing</li>
<li>Deep hands-on experience with advanced RAG systems:</li>
<li>Multi-stage retrieval architectures (hybrid search, re-ranking)</li>
<li>Embedding models and vector similarity search</li>
<li>Document processing, chunking strategies, and metadata filtering</li>
<li>Query understanding and retrieval optimization</li>
<li>Multi-turn dialogue management</li>
<li>Intent recognition and slot filling</li>
<li>Context tracking and memory management</li>
<li>Integration with LLM APIs (OpenAI, Anthropic, Cohere, etc.)</li>
<li>Production experience with voicebot development:</li>
<li>Real-time audio streaming and processing</li>
<li>Voice activity detection (VAD)</li>
<li>End-to-end latency optimization</li>
<li>Integration of STT, dialogue management, and TTS components</li>
<li>Expertise in TTS and STT technologies:</li>
<li>Modern TTS systems (ElevenLabs, Soniox, Azure Speech)</li>
<li>STT engines ( Deepgram, AssemblyAI)</li>
<li>Audio preprocessing and enhancement</li>
<li>Voice cloning and customization</li>
<li>Strong experience with LLM fine-tuning:</li>
<li>Proficiency with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)</li>
<li>Experience with MLOps tools and practices (MLflow, Weights &amp; Biases, experiment tracking)</li>
<li>Strong understanding of API design, microservices architecture, and system integration</li>
<li>Knowledge of version control, CI/CD pipelines, and deployment automation</li>
</ul>
We have an amazing team of 700+ individuals working on highly innovative enterprise projects &amp; products. Our customer base includes Fortune 100 retail and CPG companies, leading store chains, fast-growth fintech, and multiple Silicon Valley startups.
What makes Confiz stand out is our focus on processes and culture. Confiz is ISO 9001:2015 (QMS), ISO 27001:2022 (ISMS), ISO 20000-1:2018 (ITSM), ISO 14001:2015 (EMS), ISO 45001:2018 (OHSMS) Certified. We have a vibrant culture of learning via collaboration and making workplace fun.
People who work with us work with cutting-edge technologies while contributing success to the company as well as to themselves.
To know more about Confiz Limited, visit: https://www.linkedin.com/company/confiz-pakistan/</div>

AI Architect

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