data engineer

it support engineer

civil structural engineer

engineering manager

admin head ( engineer)

ai engineer

Skylinx Technologies

AI Engineer &ndash; Lahore (On-Site)We are hiring an in-house AI Engineer to join our Lahore-based engineering team. This role focuses on building and deploying AI-driven features for our custom platform, including data intelligence, competitive alerts, and user-facing AI interfaces. You will work closely with backend and product teams and have direct ownership of AI integrations and deployments.Key Responsibilities<ul><li>Work with existing machine learning models and large language models (LLMs).</li><li>Deploy and manage AI/ML models on private cloud or self-hosted infrastructure.</li><li>Integrate third-party AI tools and APIs (e.g., Groq, OpenAI, Hugging Face, vector databases).</li><li>Build data pipelines by connecting AI models with relational and NoSQL databases.</li><li>Design and implement competitive alerts, insights, and notifications from structured and unstructured data.</li><li>Develop APIs and basic interfaces to expose AI capabilities within the platform.</li><li>Optimize inference performance, cost, and scalability.</li><li>Ensure data security and privacy in AI workflows.</li><li>Collaborate closely with in-house backend, frontend, and product teams.</li></ul>Required Skills &amp; Qualifications<ul><li>2+ years of professional experience in AI/ML engineering or applied AI development.</li><li>Strong proficiency in Python.</li><li>Hands-on experience with machine learning models, LLMs, or inference pipelines.</li><li>Experience deploying models on private cloud, VPS, or on-prem infrastructure.</li><li>Familiarity with third-party AI platforms and tools (e.g., Groq, OpenAI, Anthropic).</li><li>Experience working with databases (MySQL, PostgreSQL, MongoDB, etc.).</li><li>Ability to build and consume REST APIs.</li><li>Basic experience with interfaces or dashboards for AI-powered features.</li><li>Strong problem-solving skills and ability to work in an on-site team environment.</li></ul>Nice to Have<ul><li>Experience with RAG (Retrieval-Augmented Generation) systems.</li><li>Knowledge of alerting systems, recommendation engines, or analytics dashboards.</li><li>Familiarity with Docker, Kubernetes, or MLOps workflows.</li><li>Experience in SaaS or data-driven platforms.</li><li>Frontend exposure (React, Vue, or similar).</li></ul>What We Offer<ul><li>On-site role in Lahore with a collaborative engineering team.</li><li>Opportunity to build production-grade AI systems.</li><li>Competitive salary</li><li>Long-term growth and learning opportunities.</li><li>Direct impact on core product features.</li></ul>How to ApplyPlease share:<ul><li>Your updated resume</li><li>GitHub or project links (if available)</li><li>Short summary of AI or ML projects you&rsquo;ve worked on</li></ul>Work Location: In person

AI Engineer (In-House)

Hustech

hustech.ai builds production-ready AI systems for real businesses. We work with international clients across automation, NLP, Computer Vision, LLM applications, and custom AI products. Our focus is delivery, reliability, and real business outcomes.Role OverviewWe are hiring an experienced Applied AI Engineer who can take ownership of client projects from start to finish.This is not a research-only role and not for fresh graduates. We need someone who can understand client requirements, design the right solution, build the system, deploy it, and support delivery.You should be comfortable handling different AI project types such as ML, Deep Learning, NLP, Computer Vision, LLM apps, RAG systems, and AI agents.What You&rsquo;ll Do<ul><li>Join client calls and convert requirements into technical solutions</li><li>Design end-to-end AI system architecture</li><li>Build and train ML / DL models</li><li>Develop NLP, CV, LLM, RAG, and agent-based systems</li><li>Build APIs and backend services using Python / FastAPI</li><li>Deploy solutions using Docker and cloud platforms</li><li>Integrate AI systems into client products and workflows</li><li>Optimize performance, accuracy, and scalability</li><li>Debug issues and deliver production-ready systems</li><li>Communicate progress clearly with international clients</li></ul>Required Experience<ul><li>3+ years professional industry experience (real client work, not coursework)</li><li>Proven experience delivering end-to-end AI projects</li><li>Strong Python skills</li><li>Hands-on experience in several of these areas: ML, DL, NLP, CV, LLMs, RAG, Agents etc</li><li>Experience with PyTorch or TensorFlow</li><li>Experience with APIs, FastAPI, Docker, deployment</li><li>Strong problem-solving and system design skills</li><li>Good spoken and written English</li><li>Comfortable speaking with international clients</li></ul>Preferred Skills<ul><li>AWS, GCP, or Azure</li><li>Vector databases (Qdrant, Pinecone, Weaviate)</li><li>OpenCV, Hugging Face, Scikit-learn</li><li>Automation tools and workflow systems</li></ul>Who Should ApplyApply only if you have already built and delivered real AI systems for companies or clients and can work independently with ownership.EducationBachelor&rsquo;s or Master&rsquo;s in Computer Science, AI, Machine Learning, or related field.Job Type: Full-timeExperience:<ul><li>AI Engineer: 3 years (Required)</li></ul>Language:<ul><li>English (Required)</li></ul>Work Location: In person

AI/ML Engineer

Hazen Technologies Inc.

<div>Company Overview:
Hazen Technologies is a leading technology and BPO company having offices in USA and Pakistan. Today we stand as a premier driver of innovation, offering transformative IT solutions, managed services (back-office support), and creative &amp; digital marketing services tailored for a range of industries. Our core focus is on providing seamless solutions that add real value for our customers.
Job Location: Gulberg Lahore Pakistan.
Job Conditions: Onsite, full time, 02:00 pm to 11:00 pm PKT
Report to: Chief Software Architect
Responsible for designing, developing, and implementing cutting-edge AI and machine learning solutions. Passionate and skilled to join our growing technology team. The ideal candidate will have hands-on experience building AI-powered solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) architectures, and modern machine learning techniques.
Key Responsibilities: 
<ul><li>
Design and implement AI-powered applications using Large Language Models (LLMs).</li>
<li>Develop and maintain Retrieval-Augmented Generation (RAG) pipelines for document search, knowledge retrieval, and conversational AI.</li>
<li>Work with LLM APIs and integrate them into production-grade applications.</li>
<li>Build and manage embedding pipelines and vector search solutions.</li>
<li>Apply machine learning principles for model evaluation, optimization, and performance improvement.</li>
<li>Collaborate with backend and frontend teams to integrate AI features into products.</li>
<li>Monitor and improve AI system performance, scalability, and reliability.</li>
<li>Stay updated with the latest advancements in Generative AI, LLM frameworks, and machine learning technologies.</li></ul>
Key Requirements:<ul>
<li>BS/MS in Computer Science, Artificial Intelligence, Data Science, or a related field.</li>
<li>Strong programming skills in Python.</li>
<li>Hands-on experience working with LLMs and their APIs.</li>
<li>Experience building or working with RAG-based architectures.</li>
<li>Understanding of machine learning fundamentals and model evaluation techniques.</li>
<li>Experience with embeddings, vector databases, and semantic search.</li>
<li>Familiarity with frameworks such as LangChain, LlamaIndex, or similar LLM orchestration tools.</li></ul>
Preferred / Nice to Have<ul>
<li>Experience with Azure AI services and Azure OpenAI.</li>
<li>Familiarity with vector databases such as Qdrant, Pinecone, or Weaviate.</li>
<li>Experience deploying ML/AI solutions in cloud environments (Azure preferred).</li>
<li>Knowledge of MLOps, model monitoring, and scalable AI system design.</li>
<li>Experience working with REST APIs and backend integration.</li></ul>
At Hazen Technologies, we value diversity and inclusivity in the workplace. We are committed to providing equal employment opportunities to all individuals, regardless of race, gender, age, sexual orientation, religion, or disability.
Join our team and be a part of shaping the future of AI and machine learning at Hazen Technologies. Apply now! and make sure to fill out the form.</div>

Senior AI/ML Engineer

UserWise Services

<div>About UserWise
We&rsquo;re building a high-speed, AI-assisted game production team focused on developing and scaling mobile games globally.
This is not a traditional game team. We operate with ownership, clarity, and execution speed &mdash; leveraging AI-driven workflows to move faster than most studios.
We work across a global team, building production-ready games and scaling them through LiveOps. Our focus is simple: increase the number of high-quality bets and turn them into scalable products.
Our team is already working across established franchises such as Fruit Ninja and Wordscapes, contributing to both development and growth initiatives.
Why Join
You&rsquo;ll be part of a team applying AI to real production environments &mdash; not research, but building systems that directly impact how games are created and scaled. 
Requirements 

What You&rsquo;ll Do
You will build systems and tools that accelerate game development across design, engineering, art, and QA.<ul><li>
Create AI-assisted workflows and tools that enable faster content creation (levels, assets, systems) directly within Unity Engine.</li><li>
Automate repetitive processes across production pipelines</li><li>
Work closely with designers, artists, QA, and engineers to improve workflows</li><li>
Integrate AI Capabilities: Connect our development environment with external AI/LLM models and APIs e.g. Claude Code MCP servers, Cursor Skills, to automate repetitive production pipelines.</li><li>
Rapidly prototype and deploy solutions that increase team velocity</li><li>
Continuously improve how games are built, tested, and scaled</li></ul>
What You Bring<ul><li>
Strong engineering background 4+ years of experience in game development</li><li>
Fluency in C# and deep familiarity with Unity Engine</li><li>
Experience working with AI/LLM-based tools or systems</li><li>
You are a builder &mdash; you ship tools and solutions, not just ideas</li><li>
You focus on practical impact, not theoretical research</li><li>
You can work across disciplines (design, art, QA, product)</li><li>
You are comfortable moving fast and iterating quickly</li><li>
You take ownership and solve problems end-to-end</li><li>
You care about improving speed, scalability, and efficiency</li></ul>
Environment<ul><li>
High ownership &mdash; you build systems that impact the entire team</li><li>
High speed &mdash; rapid iteration and deployment of tools</li><li>
AI-first workflows &mdash; real application of AI in production</li><li>
Global team &mdash; collaborate across multiple disciplines and regions</li><li>
Low bureaucracy &mdash; minimal process, maximum execution</li></ul> 
Benefits 
<ul><li>
Market competitive, tax-free USD salaries</li><li>
Private Health Insurance</li><li>
Paid Time Off</li><li>
Performance Bonus</li><li>
Annual Performance Reviews</li></ul></div>

AI Engineer - Game Development (Production Acceleration & Tooling)

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)

My Digital People

AI Engineer &ndash; Generative, Agentic AI &amp; AutomationWe&rsquo;re looking for a hands-on AI Engineer (2&ndash;3 years experience) who can design, build, and scale AI-powered automations and agentic systems. This role focuses on practical implementation &mdash; from intelligent workflows and voice agents to deploying open-source models on cloud infrastructure.You&rsquo;ll work on end-to-end automation systems that streamline business processes using AI.Key ResponsibilitiesAI Automation &amp; Workflows (Core Focus)<ul><li>Design and build end-to-end AI automations for business processes</li><li>Create intelligent workflows using n8n, Make, Zapier, Flowise, and custom Python</li><li>Automate tasks such as lead handling, customer support, data processing, and reporting</li><li>Connect multiple systems (CRMs, databases, APIs) into seamless automated pipelines</li><li>Build event-driven and trigger-based automation systems</li></ul>Agentic AI Systems<ul><li>Develop agentic workflows using LangChain, LangGraph, or similar tools</li><li>Architect multi-agent systems with task delegation and decision-making</li><li>Enable agents to interact with tools, APIs, and real-world data</li></ul>AI Systems &amp; Integrations<ul><li>Build AI applications across chat, voice, image, and video</li><li>Integrate AI with external tools using APIs, MCP, and webhooks</li><li>Orchestrate multiple AI providers (OpenAI, Anthropic, Google, open-source)</li></ul>Voice AI<ul><li>Develop and deploy voice agents using Vapi, ElevenLabs, or similar platforms</li><li>Design real-time conversational experiences</li></ul>RAG &amp; Knowledge Systems<ul><li>Build and maintain knowledge bases and RAG pipelines</li><li>Handle document ingestion, chunking, and embedding workflows</li></ul>Deployment &amp; Infrastructure<ul><li>Deploy and manage open-source models on cloud platforms (AWS, Azure, GCP)</li><li>Work with Docker and basic Kubernetes</li><li>Ensure scalability, monitoring, and cost control</li></ul>Prompt Engineering &amp; System Design<ul><li>Design robust prompts and multi-turn AI systems</li><li>Optimize context handling and response accuracy</li></ul>Evaluation &amp; Optimization<ul><li>Build evaluation frameworks (LLM-as-judge, human review)</li><li>Implement logging and observability (LangSmith, Helicone, or similar tools)</li><li>Optimize performance and cost through caching and model routing</li></ul>Security &amp; Reliability<ul><li>Implement AI guardrails (prompt injection protection, PII handling)</li><li>Ensure safe, reliable, and production-ready deployments</li></ul>Required Skills &amp; Experience<ul><li>2&ndash;3 years of experience in AI/ML, automation engineering, or AI-driven development</li><li>Strong Python skills</li><li>Hands-on experience with automation tools (n8n, Make, Zapier, or similar)</li><li>Experience building AI automations or workflow systems</li><li>Familiarity with LangChain, LangGraph, or similar frameworks</li><li>Strong understanding of APIs, webhooks, and system integrations</li><li>Experience with cloud platforms (AWS, Azure, or GCP)</li><li>Knowledge of prompt engineering and AI system design</li><li>Understanding of AI system evaluation, logging, and debugging</li></ul>Nice to Have<ul><li>Experience with vector databases (Pinecone, FAISS, Weaviate, Qdrant)</li><li>Familiarity with AI development tools (Cursor, Claude Code)</li><li>Experience with voice/telephony or real-time systems</li><li>Exposure to fine-tuning techniques (LoRA, QLoRA)</li><li>Experience with business process automation (BPA) systems</li></ul>EducationBachelor&rsquo;s degree in Computer Science, Engineering, Data Science, or equivalent practical experience.Job Type: Full-timeWork Location: In person

Automation Engineer (n8n & Zapier)+Model Training

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>

Azure AI (Agentic) Specialist - Team Lead

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