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ai architect

Datamatics Technologies

<div>
 Job Title: AI Architect
 
 
 Level:
 
 Senior / Principal
 
 
 Employment Type:
 
 Full-time
 
 
 Experience
 
 : 6+ Years
 
 
 Location
 
 : Islamabad (Onsite)
 
 Role Overview
 
 We are seeking a
 
 high-level AI Architect
 
 to serve as a
 
 Senior Solution Architect
 
 for our real-time automation and intelligence ecosystem. This role is both
 
 strategic and hands-on at the architectural level
 
 , acting as a technical mentor and trusted advisor to engineering teams.
 
 
 You will be responsible for defining and evolving the
 
 enterprise architecture
 
 that underpins real-time data processing, automation, and AI/ML workflows. The role requires a visionary mindset, strong problem-solving capability, and the ability to design scalable, future-ready systems that support complex, high-throughput AI use cases.
 
 Key Responsibilities
 
 
 Solution Mentorship &amp; Technical Leadership
 
 
 <ul>
 <li>
 
 Act as a technical authority and mentor for engineering teams
 
 </li>
 <li>
 
 Guide best practices for real-time data streaming, event-driven architectures, and low-latency processing
 
 </li>
 <li>
 
 Review designs and implementations to ensure architectural consistency and technical excellence
 
 </li>
 </ul>
 
 
 Architecture &amp; Gap Analysis
 
 
 <ul>
 <li>
 
 Analyze existing platforms to identify architectural gaps, performance bottlenecks, and scalability risks
 
 </li>
 <li>
 
 Design and propose robust, enterprise-grade architectural improvements
 
 </li>
 <li>
 
 Define target-state architectures aligned with long-term business and AI strategy
 
 </li>
 </ul>
 
 
 System Orchestration &amp; Integration
 
 
 <ul>
 <li>
 
 Design and oversee the integration of distributed systems, messaging platforms, and data pipelines
 
 </li>
 <li>
 
 Ensure seamless, reliable data flow across heterogeneous enterprise systems
 
 </li>
 <li>
 
 Define standards for system interoperability, resilience, and observability
 
 </li>
 </ul>
 
 
 AI/ML Infrastructure &amp; Enablement
 
 
 <ul>
 <li>
 
 Architect the data and compute foundations required for AI/ML workloads, including agentic workflows and real-time analytics
 
 </li>
 <li>
 
 Enable large-scale automation, intelligent decisioning, and near-real-time inference
 
 </li>
 <li>
 
 Ensure architectures support model lifecycle management, scalability, and performance
 
 </li>
 </ul>
 
 
 Technical Governance &amp; Quality
 
 
 <ul>
 <li>
 
 Ensure architectural designs align with industry standards, security requirements, and scalability goals
 
 </li>
 <li>
 
 Provide high-level design documentation, reference architectures, and technical blueprints
 
 </li>
 <li>
 
 Support roadmap definition and continuous architectural evolution
 
 </li>
 </ul>
 Technical Requirements
 <ul>
 <li>
 
 
 Expert-level experience with distributed systems
 
 , including:
 
 <ul>
 <li>
 
 Real-time stream processing
 
 </li>
 <li>
 
 Distributed storage platforms
 
 </li>
 <li>
 
 Low-latency analytical databases
 
 </li>
 </ul>
 </li>
 <li>
 
 Proven experience designing
 
 enterprise-scale, high-throughput data architectures
 
 
 </li>
 <li>
 
 Strong background in
 
 event-driven and real-time processing ecosystems
 
 
 </li>
 <li>
 
 Experience supporting
 
 AI/ML platforms
 
 , data fabrics, and automation frameworks
 
 </li>
 <li>
 
 Demonstrated ability to translate complex technical challenges into scalable architectural solutions
 
 </li>
 </ul>
 Leadership &amp; Soft Skills
 <ul>
 <li>
 
 Strong
 
 mentorship and coaching experience
 
 with senior engineering teams
 
 </li>
 <li>
 
 Ability to influence architectural direction across multiple teams and stakeholders
 
 </li>
 <li>
 
 Excellent communication skills, capable of articulating complex designs to both technical and non-technical audiences
 
 </li>
 <li>
 
 Strategic mindset with a focus on long-term platform evolution
 
 </li>
 </ul>
 Nice to Have
 <ul>
 <li>
 
 Experience with cloud-native and hybrid architectures
 
 </li>
 <li>
 
 Exposure to MLOps, DataOps, or platform engineering practices
 
 </li>
 <li>
 
 Experience in regulated or large enterprise environments
 
 </li>
 </ul>
 Why Join
 <ul>
 <li>
 
 Shape the
 
 architectural foundation of advanced AI and automation platforms
 
 
 </li>
 <li>
 
 Influence enterprise-scale technical decisions with long-term impact
 
 </li>
 <li>
 
 Work in a senior, high-visibility role with strong ownership and autonomy
 
 </li>
 </ul>
</div>

AI Architect

92Techno

We are seeking an experienced AI/GenAI Solution Architect to lead the design and delivery of enterprise-grade AI solutions.Responsibilities<ul><li>Engage with clients early to understand AI/GenAI/ML use cases and business requirements</li><li>Design proposed AI architectures and delivery approaches for opportunities</li><li>Provide effort estimates, assumptions, and implementation roadmaps for AI components</li><li>Lead end-to-end AI/GenAI solution architectures including data, models, integration, and deployment</li><li>Own scoped AI work packages delivered by the AI CoE within larger delivery projects</li><li>Ensure AI solutions are production-grade, secure, scalable, and maintainable</li><li>Collaborate with delivery teams for integration, handover, and deployment support</li><li>Establish reusable reference architectures, patterns, and best practices</li><li>Lead AI-enabled development initiatives across delivery teams</li><li>Standardize AI tools and workflows across the software development lifecycle (requirements, design, coding, testing, documentation)</li><li>Maintain awareness of emerging AI tools, models, and industry trends</li><li>Support internal incubation efforts and AI technology radar initiatives</li><li>Guide and mentor junior AI engineer and data analysts, providing technical direction, support, and feedback to elevate team expertise.</li></ul>Required Qualifications<ul><li>8+ years of experience in solution architecture, AI/ML engineering, or related roles</li><li>Strong understanding of AI/ML concepts, GenAI architectures, and modern model ecosystems</li><li>Experience designing AI solutions for enterprise clients, including integration into business applications</li><li>Hands-on familiarity with GenAI patterns such as RAG, agents, embeddings, and prompt engineering</li><li>Strong communication and stakeholder management skills, especially in client-facing settings</li><li>Ability to work across pre-sales, delivery, and engineering teams</li></ul>Preferred Skills<ul><li>Experience with cloud AI platforms (Azure AI, AWS SageMaker, GCP Vertex AI)</li><li>Familiarity with MLOps practices, evaluation frameworks, and deployment pipelines</li><li>Exposure to enterprise security, compliance, and responsible AI governance</li><li>Prior experience in consulting or client delivery environments</li></ul>Job Type: Full-timePay: Rs500,000.00 - Rs600,000.00 per monthWork Location: In person

AI Solution Architect

Systems Limited

<div>
 
 
 About the Role
 
 
 
 We are looking for an AI Security Architect to design and establish the Enterprise AI Security Reference Architecture. This role will ensure that all GenAI and Agentic AI platforms are secure, compliant, and aligned with enterprise governance standards across the AI lifecycle.
 
 
 
 
 
 
 Responsibilities:
 
 
 <ul>
 <li>
 Define and publish the Enterprise AI Security Reference Architecture as the standard for secure AI design
 </li>
 <li>
 Identify trust boundaries, threat surfaces, and control points across the AI ecosystem
 </li>
 <li>
 Design security controls for AI models, RAG pipelines, agent frameworks, vector databases, and LLM APIs
 </li>
 <li>
 Align AI security architecture with ISO/IEC 42001 and identify gaps with remediation plans
 </li>
 <li>
 Design Agent Identity &amp; Access Management (IAM) frameworks for secure agent operations
 </li>
 <li>
 Establish secure lifecycle management for AI agents including provisioning, monitoring, and decommissioning
 </li>
 <li>
 Develop AI risk classification models and mitigation strategies
 </li>
 <li>
 Define security standards for LLM integrations, prompt management, and AI services
 </li>
 <li>
 Conduct architectural security reviews for AI solutions and platforms
 </li>
 <li>
 Collaborate with engineering and infrastructure teams to ensure secure deployments
 </li>
 </ul>
 
 
 
 
 
 Qualifications:
 
 
 <ul>
 <li>
 10+ years of experience in Cybersecurity Architecture or Enterprise Security
 </li>
 <li>
 Strong experience with GenAI platforms, LLM architecture, RAG pipelines, and agentic AI security
 </li>
 <li>
 Hands-on experience with Azure OpenAI, AWS Bedrock, vector databases, and API security
 </li>
 <li>
 Knowledge of OWASP Top 10 for LLM applications and AI-specific threat vectors
 </li>
 <li>
 Experience in designing security for cloud-native AI platforms
 </li>
 <li>
 Strong understanding of identity management, cryptography, and data protection
 </li>
 <li>
 Experience working in regulated industries such as financial services, healthcare, or legal
 </li>
 <li>
 Strong problem-solving, stakeholder management, and communication skills
 </li>
 </ul>
 
 Location: Khi/ Lhr/ Isb
 
</div>

AI Security Architect

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>
f6KdxkjExk</div>

Data Architect

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>

Shahzada Group of Industries

We are seeking an experienced AI Infrastructure &amp; Automation Engineer to join our team. In this role, you will be the bridge between high-level AI application logic and the underlying hardware that powers it. You will own the responsibility of scaling our AI operations, ensuring our LLM workflows run efficiently on centralized GPU infrastructure, and automating our backend systems. If you have a passion for building robust AI pipelines and optimizing server performance, we want to hear from you.Key Responsibilities<ul><li>Infrastructure Management: Architect, deploy, and maintain centralized GPU server clusters to ensure high availability and performance for LLM training and inference.</li><li>LLM Integration: Develop and maintain backend logic to integrate Large Language Models (LLMs) into production-grade applications.</li><li>Automation: Build end-to-end automation workflows that reduce manual operational tasks, utilizing tools like N8N, Make, or custom Python scripts.</li><li>System Optimization: Monitor and tune server resources to maximize GPU utilization and minimize inference latency.</li><li>Pipeline Development: Create and manage data pipelines for ingestion, preprocessing, and model fine-tuning.</li><li>Scalability: Troubleshoot hardware/software bottlenecks and scale our infrastructure as our AI service demand grows.</li></ul>Required Qualifications<ul><li>Deep Technical Expertise: 3+ years of experience in AI/ML infrastructure, systems engineering, or a similar technical role.</li><li>GPU &amp; Server Knowledge: Hands-on experience with managing GPU-accelerated servers (e.g., NVIDIA stack, CUDA, and containerization with Docker/Kubernetes).</li><li>LLM Proficiency: Practical experience with deploying and fine-tuning LLMs (e.g., Llama, OpenAI API, Mistral) in production environments.</li><li>Programming: Strong proficiency in Python and experience with MLOps frameworks.</li><li>System Integration: Proven ability to connect APIs, webhooks, and databases to build cohesive, automated business workflows.</li><li>Problem-Solving: A &quot;builder&quot; mindset with the ability to identify infrastructure bottlenecks and implement solutions proactively.</li></ul>Job Type: Full-timePay: Rs80,000.00 - Rs120,000.00 per monthWork Location: In person

Lead AI Automation Engineer (LLM & GPU Infrastructure)

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286 ai architect jobs In Lahore

AI Architect

AI Solution Architect

AI Security Architect

Data Architect

Azure AI (Agentic) Specialist - Team Lead

Azure AI (Agentic) Specialist - Team Lead

Lead AI Automation Engineer (LLM & GPU Infrastructure)