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azure ai agentic specialist team lead

NorthBay Solutions

<div>
 
 
 Role: Team Lead - Azure AI (Agentic) Engineer
 
 
 
 
 Location:
 
 Pakistan (hybrid work model)
 
 
 
 
 Client: Middle East (Government)
 
 
 
 
 
 
 About the Role:
 
 
 
 
 NorthBay Solutions, an AWS global Consulting Partner with distributed teams across the US, Canada, UAE, India, and Pakistan, is hiring a high-caliber&nbsp;
 
 Azure AI Specialist (Team Lead)
 
 with deep expertise in building enterprise-grade
 
 Generative AI, RAG, and Agentic AI solutions
 
 on the Azure ecosystem.
 
 
 This role requires hands-on experience in designing scalable, multi-tenant AI systems, integrating LLMs, and building intelligent pipelines using Azure-native services.
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design and deploy
 
 LLM-powered applications
 
 using Azure OpenAI for enterprise use cases
 </li>
 <li>
 Build and optimize
 
 Retrieval-Augmented Generation (RAG)
 
 pipelines using Azure AI Search (vector + hybrid search)
 </li>
 <li>
 Develop
 
 Agentic AI systems
 
 leveraging frameworks and tool-based reasoning approaches
 </li>
 <li>
 Implement
 
 custom Document Intelligence models
 
 for high-accuracy data extraction (e.g., IDs, structured documents)
 </li>
 <li>
 Architect
 
 multi-tenant AI deployments
 
 with scalability, security, and cost-efficiency in mind
 </li>
 <li>
 Develop and manage
 
 Knowledge Graphs
 
 for structured reasoning and contextual intelligence
 </li>
 <li>
 Apply advanced
 
 prompt engineering techniques
 
 (Few-shot, Chain-of-Thought, ReAct)
 </li>
 <li>
 Use
 
 Prompt Flow in Azure AI Studio
 
 for experimentation, testing, and versioning
 </li>
 <li>
 Design
 
 intelligent conversational systems
 
 with fallback handling and contextual memory
 </li>
 <li>
 Build and manage
 
 MLOps pipelines
 
 using Azure Machine Learning
 </li>
 </ul>
 
 
 Required Skills &amp; Experience
 
 
 <ul>
 <li>
 Overall 10+ years experience, with a focus on&nbsp;
 
 Azure OpenAI API
 
 (deployments, scaling, optimization)
 </li>
 <li>
 Proven expertise in building
 
 RAG pipelines using Azure AI Search
 
 </li>
 <li>
 Experience with
 
 vector databases and hybrid search architectures
 
 </li>
 <li>
 Practical experience in
 
 Agentic AI / multi-agent systems
 
 </li>
 <li>
 Hands-on with
 
 Azure AI Document Intelligence (Form Recognizer)
 
 </li>
 <li>
 Solid understanding of
 
 Knowledge Graphs and semantic modeling
 
 </li>
 <li>
 Expertise in
 
 prompt engineering &amp; LLM optimization techniques
 
 </li>
 <li>
 Experience with
 
 Prompt Flow (Azure AI Studio)
 
 </li>
 <li>
 Strong background in
 
 Python and cloud-native development
 
 </li>
 <li>
 Experience with
 
 Azure ML / MLOps pipelines
 
 </li>
 <li>
 Ability to design scalable and secure
 
 enterprise AI architectures
 
 </li>
 </ul>
 
 
 Nice to Have
 
 
 <ul>
 <li>
 Experience with
 
 LangChain, Semantic Kernel, or similar frameworks
 
 </li>
 <li>
 Exposure to
 
 multi-agent orchestration tools
 
 </li>
 <li>
 Prior experience working with
 
 enterprise clients or large-scale AI deployments
 
 </li>
 </ul>
</div>

Azure AI (Agentic) Specialist - Team Lead

NorthBay - Pakistan

<div>
 
 Role: Team Lead - Azure AI (Agentic) Engineer
 
 
 
 
 Location:
 
 Pakistan (hybrid work model)
 
 
 
 
 Client: Middle East (Government)
 
 
 
 
 
 About The Role
 
 
 
 NorthBay Solutions, an AWS global Consulting Partner with distributed teams across the US, Canada, UAE, India, and Pakistan, is hiring a high-caliber
 
 Azure AI Specialist (Team Lead)
 
 with deep expertise in building enterprise-grade
 
 Generative AI, RAG, and Agentic AI solutions
 
 on the Azure ecosystem.
 
 
 This role requires hands-on experience in designing scalable, multi-tenant AI systems, integrating LLMs, and building intelligent pipelines using Azure-native services.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design and deploy LLM-powered applications using Azure OpenAI for enterprise use cases
 </li>
 <li>
 Build and optimize Retrieval-Augmented Generation (RAG) pipelines using Azure AI Search (vector + hybrid search)
 </li>
 <li>
 Develop Agentic AI systems leveraging frameworks and tool-based reasoning approaches
 </li>
 <li>
 Implement custom Document Intelligence models for high-accuracy data extraction (e.g., IDs, structured documents)
 </li>
 <li>
 Architect multi-tenant AI deployments with scalability, security, and cost-efficiency in mind
 </li>
 <li>
 Develop and manage Knowledge Graphs for structured reasoning and contextual intelligence
 </li>
 <li>
 Apply advanced prompt engineering techniques (Few-shot, Chain-of-Thought, ReAct)
 </li>
 <li>
 Use Prompt Flow in Azure AI Studio for experimentation, testing, and versioning
 </li>
 <li>
 Design intelligent conversational systems with fallback handling and contextual memory
 </li>
 <li>
 Build and manage MLOps pipelines using Azure Machine Learning
 
 
 </li>
 </ul>
 
 Required Skills &amp; Experience
 
 
 
 <ul>
 <li>
 Overall 10+ years experience, with a focus on Azure OpenAI API (deployments, scaling, optimization)
 </li>
 <li>
 Proven expertise in building RAG pipelines using Azure AI Search
 </li>
 <li>
 Experience with vector databases and hybrid search architectures
 </li>
 <li>
 Practical experience in Agentic AI / multi-agent systems
 </li>
 <li>
 Hands-on with Azure AI Document Intelligence (Form Recognizer)
 </li>
 <li>
 Solid understanding of Knowledge Graphs and semantic modeling
 </li>
 <li>
 Expertise in prompt engineering &amp; LLM optimization techniques
 </li>
 <li>
 Experience with Prompt Flow (Azure AI Studio)
 </li>
 <li>
 Strong background in Python and cloud-native development
 </li>
 <li>
 Experience with Azure ML / MLOps pipelines
 </li>
 <li>
 Ability to design scalable and secure enterprise AI architectures
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Experience with LangChain, Semantic Kernel, or similar frameworks
 </li>
 <li>
 Exposure to multi-agent orchestration tools
 </li>
 <li>
 Prior experience working with enterprise clients or large-scale AI deployments
 </li>
 </ul>
</div>

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

<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

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

Al Rafay Consulting

Job Overview:We are looking for a Senior Python Developer to assist in building and maintaining backend services, APIs, and automation scripts for enterprise applications. The role involves collaborating with senior developers and AI/ML engineers to implement features, integrate tools, and support solutions such as chatbots and data automation.Key Responsibilities<ul><li>Develop Python-based backend services for AI-powered enterprise applications.</li><li>Build and maintain APIs, automation scripts, and data pipelines.</li><li>Collaborate with AI/ML engineers to integrate NLP, OCR, and LLMs into business tools.</li><li>Work on intelligent solutions like chatbot frameworks, document automation, and enterprise assistants.</li><li>Integrate with Microsoft technologies (SharePoint Online, Power Automate, Azure Cognitive Services).</li><li>Use Azure DevOps for CI/CD and project lifecycle tracking.</li><li>Participate in sprints, peer code reviews, and collaborative design sessions.</li></ul>Required Skills &amp; Qualifications<ul><li>Bachelor&rsquo;s degree in Computer Science, Software Engineering, or related field.</li><li>6&ndash;8 years of experience with Python (Flask/Django or similar frameworks).</li><li>Solid understanding of REST APIs, microservices, and backend architecture.</li><li>Experience with AI tools: NLP, OCR, or integration with language models (OpenAI, Azure OpenAI).</li><li>Familiarity with Microsoft ecosystem (Azure Functions, SharePoint, Power Platform).</li><li>Good understanding of databases (SQL/NoSQL), data extraction, and automation.</li><li>Version control systems (e.g., Git) and CI/CD tools (Azure DevOps) experience.</li><li>Strong debugging, analytical, and communication skills.</li></ul>Preferred Qualifications<ul><li>Experience with Microsoft Cognitive Services, Azure OpenAI, or Power Automate flows.</li><li>Familiarity with chatbot frameworks (e.g., Rasa, Bot Framework).</li><li>Understanding of information security and data privacy in enterprise environments.</li><li>Exposure to enterprise-scale automation or document processing projects.</li></ul>Experience:<ul><li>IT: 7 years (Required)</li></ul>Work Location: In person

Senior Python Developer

Datamatics Global Services Ltd

<div><h2 class="jobSectionHeader">Job Title: Data Architect</h2>
Experience: 9+ Years 
Industry: Banking / Financial Services 
Location:Pakistan 
Employment Type: Full-Time<h2 class="jobSectionHeader">
Job Summary</h2>
We are seeking an experienced Data Architect with a strong background in AI/ML and Big Data architectures to design, implement, and govern enterprise-wide data solutions. The ideal candidate will play a critical role in enabling data-driven decision-making, advanced analytics, and AI capabilities within a banking environment while ensuring compliance with regulatory and security standards.<h2 class="jobSectionHeader">
Key Responsibilities</h2><ul><li>
Design and implement enterprise data architecture across traditional systems, Big Data platforms, and cloud ecosystems.</li><li>
Architect scalable data lakes, data warehouses, and lakehouse solutions supporting structured and unstructured data.</li><li>
Define and manage data models, metadata frameworks, and data integration patterns for enterprise-wide use.</li><li>
Build and optimize data pipelines for batch and real-time processing using technologies like Hadoop, Spark, and Kafka.</li><li>
Enable AI/ML use cases by designing data platforms compatible with Python-based frameworks such as TensorFlow, PyTorch, and MLflow.</li><li>
Lead cloud data architecture initiatives across AWS, Azure, and GCP, ensuring high availability, scalability, and cost efficiency.</li><li>
Implement and enforce data governance, data quality, and data security frameworks using tools such as Collibra, Alation, and Apache Atlas.</li><li>
Collaborate with cross-functional teams including data engineers, data scientists, business analysts, and IT teams.</li><li>
Design and oversee ETL/ELT processes using tools like Informatica, Talend, and dbt.</li><li>
Utilize orchestration frameworks such as Apache Airflow to automate and monitor workflows.</li><li>
Ensure compliance with banking regulations, data privacy laws, and security standards.</li><li>
Evaluate and recommend emerging technologies to enhance the organization&rsquo;s data capabilities.</li></ul><h2 class="jobSectionHeader">
Required Skills &amp; Qualifications</h2><ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Information Systems, Data Science, or related field.</li><li>
9+ years of experience in data architecture, data engineering, or related roles, preferably in the banking or financial services industry.</li><li>
Strong expertise in Big Data technologies: Hadoop, Spark, Kafka.</li><li>
Hands-on experience with cloud platforms: AWS, Microsoft Azure, or Google Cloud Platform.</li><li>
Proficiency in data modeling (conceptual, logical, physical) and database design.</li><li>
Experience with data warehousing and lakehouse architectures (Snowflake, Databricks).</li><li>
Strong understanding of AI/ML data pipelines and frameworks (Python, TensorFlow, PyTorch).</li><li>
Expertise in ETL/ELT tools and data pipeline orchestration.</li><li>
Knowledge of data governance, metadata management, and data quality frameworks.</li><li>
Familiarity with banking data domains (risk, compliance, fraud, customer analytics).</li><li>
Excellent problem-solving, communication, and stakeholder management skills.</li></ul><h2 class="jobSectionHeader">
Preferred Qualifications</h2><ul><li>
Certifications in Cloud Platforms (AWS/Azure/GCP) or Data Architecture.</li><li>
Experience with real-time streaming architectures.</li><li>
Knowledge of regulatory frameworks such as Basel III, GDPR, or local banking compliance standards.</li><li>
Exposure to Data Mesh or Data Fabric architectures.</li><li>
Experience with API-based data integration and microservices architecture.</li></ul><h2 class="jobSectionHeader">
Key Competencies</h2><ul><li>
Strategic Thinking</li><li>
Data Governance &amp; Compliance</li><li>
Solution Architecture</li><li>
Stakeholder Management</li><li>
Innovation &amp; Continuous Improvement</li></ul>
Vxk31DGthf</div>

Data Architect

Explore 1473+ Azure ai agentic specialist team lead in Karachi this April. Find roles across top companies and apply now to boost your career.

1473 azure ai agentic specialist team lead jobs In Karachi

Azure AI (Agentic) Specialist - Team Lead

Azure AI (Agentic) Specialist - Team Lead

Senior AI Engineer

AI Architect

AI Applications Engineer

Senior Python Developer

Data Architect