ai engineer

ai engineering lead

software engineer

agentic ai engineer

ai development lead

artificial intelligence engineer

Cortech sols pvt ltd

Job Title: AI EngineerLocation: Gulberg Greens, Islamabad.Experience Required: 2-3 years.Type: Full Time, Onsite Role.Job OverviewWe are seeking a skilled AI Engineer specializing in Large Language Models (LLMs) and Generative AI with 2&ndash;3 years of hands-on experience in building, deploying, and optimizing AI-driven solutions. The role involves working closely with cross-functional teams to develop scalable, production-ready AI applications that deliver real business value.Key Responsibilities* Develop and deploy applications using LLMs (e.g., GPT, Claude, LLaMA, Mistral)* Implement prompt engineering, RAG (Retrieval-Augmented Generation), MCP Servers and embedding-based solutions.* Fine-tune and optimize generative models for domain-specific use cases.* Design end-to-end Generative AI pipelines and workflows* Integrate AI capabilities into existing products via APIs and microservices.* Evaluate model performance, accuracy, latency, and cost efficiency.* Work with vector databases such as Pinecone, FAISS, or Weaviate.* Ensure ethical AI usage, data privacy, and security compliance.Required Qualifications* Bachelor&rsquo;s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.* 2&ndash;3 years of practical experience in AI/ML or applied Generative AI.* Strong proficiency in Python and AI/ML frameworks (PyTorch, TensorFlow, Hugging Face).* Hands-on experience with LLMs, transformers, and generative models.* Strong expertise to work with MCP servers and LangGraph.* Experience with prompt engineering, embeddings, and RAG architectures.* Familiarity with RESTful APIs and cloud platforms (AWS, GCP, Azure)* Solid understanding of software engineering best practices.Preferred Skills* Experience fine-tuning open-source LLMs (LLaMA, Falcon, Mistral, etc.)* Knowledge of LangChain, LIamaIndex, or similar orchestration frameworks.* Experience with Docker, Kubernetes, and CI/CD pipelines.* Understanding of MLOps concepts and model monitoring.* Exposure to multimodal AI (text, image, or audio-based models).Job Types: Full-time, ContractPay: Rs140,000.00 - Rs150,000.00 per monthWork Location: In person

AI Engineer

Datamatics Global Services Ltd

<div>Department: IT Development 
Reports To: AI Engineering Lead<h2 class="jobSectionHeader">
Position Summary</h2>
The AI Engineer is responsible for designing, developing, and deploying AI-powered applications and systems that integrate with Android, iOS, and web platforms. The role involves working on applied machine learning, automation, and intelligent features that enhance customer experience and operational efficiency. The ideal candidate should have strong expertise in mobile development, backend engineering (Python), and web technologies, along with hands-on experience in building, testing, and scaling AI-driven solutions.<h2 class="jobSectionHeader">
Duties &amp; Responsibilities</h2><ul><li>
Design, build, and maintain AI-driven features for mobile (Android/iOS) and web platforms</li><li>
Collaborate with cross-functional teams (mobile, backend, product) to integrate AI capabilities such as recommendation engines, chatbots, fraud detection models, and personalization systems</li><li>
Develop machine learning models, perform data preprocessing, and deploy production-ready models using Python frameworks (TensorFlow, PyTorch, Scikit-learn)</li><li>
Write clean, modular, and scalable code using engineering best practices (SOLID principles, Clean Architecture)</li><li>
Build and manage APIs and microservices for AI functionality using Flask, FastAPI, or Node.js</li><li>
Work closely with UX/UI and product teams to convert insights into intelligent user experiences</li><li>
Conduct model performance optimization, A/B testing, and evaluation for real-world accuracy and reliability</li><li>
Integrate AI systems with cloud infrastructure (AWS, GCP, or Azure) ensuring compliance, governance, and security standards</li><li>
Participate in code reviews, peer-learning sessions, and agile ceremonies such as scrums and sprint reviews</li><li>
Stay updated with emerging AI, ML, GenAI, and automation trends to propose innovative solutions</li><li>
Demonstrate Behaviors &mdash; Be Respectful, Keep Promises, Always Explore, Create Together &mdash; in daily work practices</li></ul><h2 class="jobSectionHeader">
Direct Reports</h2><ul><li>
None</li></ul><h2 class="jobSectionHeader">
Role Relationships</h2><h3 class="jobSectionHeader">
Internal</h3><ul><li>
IT Development</li><li>
Information Security</li><li>
Operations</li><li>
Internal Audit</li></ul><h3 class="jobSectionHeader">
External</h3><ul><li>
Vendors</li></ul><h2 class="jobSectionHeader">
Knowledge &amp; Experience</h2><h3 class="jobSectionHeader">
Education</h3><ul><li>
BS/MS in Computer Science, Artificial Intelligence, Data Science, or a related field</li></ul><h3 class="jobSectionHeader">
Experience</h3><ul><li>
3+ years of software development experience</li><li>
Proven experience in AI/ML projects</li><li>
Hands-on experience with mobile development (Android/iOS), Python engineering, and web technologies</li></ul><h2 class="jobSectionHeader">
Competencies</h2><h3 class="jobSectionHeader">
AI / ML</h3><ul><li>
Flowise, PyTorch, OpenAI APIs, N8N</li><li>
Machine Learning &amp; Applied AI development</li><li>
Data preprocessing, model training, deployment</li></ul><h3 class="jobSectionHeader">
Programming</h3><ul><li>
Python</li><li>
Swift / Kotlin</li><li>
JavaScript / TypeScript</li></ul><h3 class="jobSectionHeader">
Cloud &amp; DevOps</h3><ul><li>
AWS / GCP</li><li>
Docker, CI/CD pipelines</li></ul><h3 class="jobSectionHeader">
Version Control</h3><ul><li>
Git</li></ul><h3 class="jobSectionHeader">
Data Engineering</h3><ul><li>
Pandas, NumPy, SQL</li><li>
ETL processes &amp; data pipelines</li></ul><h3 class="jobSectionHeader">
Mobile &amp; Web Development</h3><ul><li>
Android Studio</li><li>
Xcode</li><li>
React / Next.js</li><li>
Flutter (optional)</li></ul><h3 class="jobSectionHeader">
API &amp; Backend</h3><ul><li>
REST, GraphQL</li><li>
Flask / FastAPI</li><li>
Node.js</li></ul><h3 class="jobSectionHeader">
Security &amp; Compliance</h3><ul><li>
Secure coding standards</li><li>
Data privacy and compliance frameworks</li></ul>
UUnhBo8fyy</div>

AI Engineering Lead

Palladium Pakistan Pvt Ltd

<div><div><div><div>Posted date</div> <div>27th February, 2026</div> <div>Last date to apply</div> <div>5th March, 2026</div>
</div> 
<div><div>Country</div> <div>Pakistan</div> <div>Locations</div> <div>Islamabad</div>
</div> 
<div><div>Category</div> <div>Artificial Intelligence
</div></div> 
<div><div>Type</div> <div>Consultancy</div> <div>Position</div> <div>1</div>
</div> 
<div><div>Experience</div> <div>10 years</div></div></div></div>
 <div>Mid National - AI / Machine Learning Specialist/Developer

E4H FED TA: Embedded Technical Support to the Ministry of National Health Services, Regulation &amp; Coordination (M/o NHSR&amp;C)

Programme Overview

Evidence for Health (E4H) is a Foreign, Commonwealth &amp; Development Office (FCDO)-funded programme aimed at strengthening Pakistan's healthcare system, thereby decreasing the burden of illness and saving lives. E4H provides technical assistance (TA) to the Federal, Khyber Pakhtunkhwa (KP), and Punjab governments, and is being implemented by Palladium along with Oxford Policy Management (OPM).

Through its flexible, embedded, and demand-driven model, E4H supports the government to achieve a resilient health system that is prepared for health emergencies, responsive to the latest evidence, and delivers equitable, quality, and efficient healthcare services. Specifically, E4H delivers TA across three outputs:

Output 1: Strengthened integrated health security, with a focus on preparing and responding to health emergencies, including pandemics.

Output 2: Strengthened evidence-based decision-making to drive health sector performance and accountability.

Output 3: Improved implementation of Universal Health Coverage, with a focus on ending preventable deaths.

Position Summary

The overall goal is to develop a National Digital Health Hub (NDHH) software and implement an integrated, scalable, and interoperable digital health information platform within a six-month timeframe

Specific Objectives

The specific objectives are to:
<div>
<ul><li>Link the remaining two provinces to NDHH through secure, standards-aligned interoperability mechanisms and validated data pipelines;</li></ul>
<ul><li>Operationalise the Practice Hub to deliver AI-enabled advanced analytics and decision support, including explainable insights and scenario-oriented outputs;</li></ul>
<ul><li>Strengthen governance, capacity, and sustainability arrangements so that NDHH is routinely usable and maintainable within Government systems (NHDC/NIH and provincial counterparts).</li></ul>
</div>
Strategic Approach

Phase II will follow the same strategic logic established in Phase 1. The focus will be on connecting/linking existing systems and datasets, support interoperability, ensure secure and ethical use of health data, strengthen capacity for routine use, and build a flexible platform aligned with global standards that can adapt to future health system needs.

Key strategic principles include:
<ul>
<li>Federated interoperability (connect and exchange rather than replace existing provincial systems)</li>
<li>Governance-led implementation (data sharing and decision rights defined up-front)</li>
<li>Incremental rollout with verification (pilot-to-scale with measurable acceptance criteria)</li>
<li>Human-centred adoption (capacity building, usability, and local operational ownership)</li>
</ul>
Scope of Work

As a part of this TA assignment, the consultant(s) will cover the following scope of work:

1 Governance, Coordination, and Data Sharing

Building on Phase 1 governance structures, the consultant(s) will:
<ul>
<li>Strengthen and operationalise national&ndash;provincial coordination mechanisms for NDHH implementation (including provincial inclusion and decision pathways).</li>
<li>Support the completion/update of data sharing instruments (e.g., MoUs/DSA) between M/o NHSR&amp;C, NIH/NHDC and the participating provinces/areas, clarifying roles, responsibilities, and permissible use.</li>
<li>Establish practical governance for AI-enabled decision support (approval workflow for use-cases, safeguards, and change control).</li>
</ul>
2 Provincial Onboarding and Integration (Remaining Two Provinces)
<ul>
<li>Conduct onboarding the two remaining provinces (systems integration, linkage, APIs, metadata alignment, connectivity, and privacy constraints).</li>
<li>Implement and validate secure data exchange pipelines (scheduled ingestion, reconciliation, error handling, and alerting), consistent with the Phase 1 approach to backend integration and validation.</li>
<li>Use and apply existing national metadata packages and indicator mappings to ensure comparability across provinces while retaining provincial context.</li>
<li>Conduct integration testing and provincial UAT with documented sign-off.</li>
</ul>
3 Practice Hub Development (AI-enabled Advanced Analytics)

The consultant(s) will design, develop, test, deploy and operationalise the Practice Hub, including AI models configured and executed in the accordance with NDHH requirements, as a controlled decision-support layer that:
<ul>
<li>Enables authorised users to query integrated datasets and receive interpretable results (trends, comparisons, alerts, &ldquo;&rdquo; what-if&rdquo; scenarios, briefs and short summaries).</li>
<li>Connects with the Knowledge Hub, so results are linked to relevant policies, guidelines, and evidence resources to support learning and consistent decision making..</li>
<li>Implements ethical and safety AI controls to protect privacy, reduce bias, ,explain how results are generated , track system use, and restrict access based on user role.</li>
<li>Uses approved AI services through secure APIs (where approved) to support advanced analysis and summarisation, while protecting sensitive information and tracking data sources.</li>
</ul>
4 Security, Identity, and Access Management
<ul>
<li>Ensure role-based access controls and permissions for new provincial users and for Practice Hub functions (including auditability).</li>
<li>Protect system and data by using encryption, multi-factor authentication, and secure operating practices with national hosting requirements.</li>
</ul>
5 Testing, Quality Assurance, and Deployment
<ul>
<li>Execute a structured test plan: unit, integration, end-to-end, performance/load, security testing, and UAT.</li>
<li>Conduct UAT in the two newly onboarded provinces and ensure the NDHH is ready to for routine use.</li>
<li>Establish monitoring and operational procedures; configure alerts and routine checks (operational sustainability).</li>
</ul>
6 Documentation, Training, Capacity Building, and Handover
<ul>
<li>Produce comprehensive technical documentation (NDHH architecture, APIs, interoperability mechanisms, and end to end data flows), user guides, and training materials and conduct structured training sessions.</li>
<li>Strengthen NIH/NHDC operational capacity through hands-on administration, supervised operations, and progressive handover.</li>
</ul>
Focal points nominated by the Director General (Health) and NIH will be actively engaged in the activity. Staff of HPSIU and the Ministry will also be engaged in the activity.

Sustainability: Capacity Building, Institutionalisation, and/or Transition Planning
Capacity Building: Targeted trainings, on-the-job mentoring, and practical guidance will strengthen NIH/NHDC and provincial capacity to operate, maintain, and routinely use NDHH, including interoperability, analytics, and decision-support functions.

Institutionalisation: NDHH to be embedded within existing government HIS structures through formal governance arrangements, standard operating procedures, data-sharing agreements, and alignment with national data and interoperability standards.

Transition Planning: A phased handover will transfer full operational ownership to NIH/NHDC and provinces, supported by complete documentation, system access transfer, and formal validation of government readiness at the end of Phase II.

Responsibilities

The AI/Machine Learning Specialist/Developer will be responsible for:
<ul>
<li>Inception Report &amp; detailed Workplan including integrated Gantt chart</li>
<li>Provincial onboarding, Governance, Integration and Go-live of the Remaining Two Provinces</li>
<li>Practice Hub V1.0 (AI-enabled advanced analytics)</li>
<li>Security Hardening, Documentation, Capacity Building, and Operational Handover</li>
<li>Final Phase II report</li>
</ul>
Timeline and Days

The level of effort (LOE) for the role is 30 days from May 2026 &ndash; Sep 2026.

Requirement

Technical Expertise
<ul>
<li>Minimum 10 years of experience in machine learning and natural language processing.</li>
<li>Experience with OpenAI, Google AI APIs, and model integration.</li>
<li>Experience applying AI in healthcare/public health data systems</li>
</ul>
Competencies
<ul>
<li>Innovative Thinking</li>
<li>Strong algorithmic and coding skills and data literacy</li></ul></div>

FED TA DigitalHub - Mid STTA AI / Machine Learning Specialist/Developer

NEXT eBIZ

Location: Islamabad, PakistanReimagine Work Through Agentic AIWe are a rapidly growing multinational group with operations across the UK, USA, Malaysia, and the UAE. As we expand our AI capabilities, we are seeking a forward-thinking AI Engineer to design and deliver agentic AI systems that automate workflows, enhance productivity, and scale global business operations.This role sits at the intersection of AI engineering, workflow automation, and business impact. You will architect intelligent, multi-agent systems that operate autonomously across e-commerce, operations, recruitment, logistics, and customer experience.Key Responsibilities<ul><li>Design and implement agentic AI workflows for real-time task execution and decision-making</li><li>Build and orchestrate multi-step automation pipelines using agent frameworks and workflow tools</li><li>Develop multi-agent architectures to support e-commerce growth, sales, recruitment, and logistics</li><li>Integrate AI solutions into internal operations and customer-facing systems</li><li>Build custom GPTs, AI copilots, and autonomous agents aligned with business objectives</li><li>Collaborate with global teams to identify automation opportunities and optimize workflows</li><li>Support non-technical teams with AI onboarding, prompt strategy, and best practices</li><li>Contribute to the AI roadmap with a focus on scalability, reliability, and responsible AI adoption</li></ul>Required Qualifications<ul><li>Hands-on experience with agentic AI frameworks (e.g., AutoGPT, BabyAGI, OpenAgents, CrewAI)</li><li>Strong experience building multi-step workflows using LangChain, automation platforms, or custom scripts</li><li>Proficiency in Python (required); JavaScript or TypeScript is a plus</li><li>Experience integrating AI into e-commerce, customer service, logistics, or internal operations</li><li>Practical experience with LLM APIs (OpenAI, Claude, Gemini, Mistral, etc.)</li><li>Experience designing and implementing RAG (Retrieval-Augmented Generation) systems</li><li>Familiarity with vector databases such as Pinecone, Weaviate, or FAISS</li><li>Ability to deploy, monitor, and optimize autonomous agents in production environments</li></ul>Nice to Have<ul><li>Experience with agent memory, prompt optimization, or RLHF concepts</li><li>Exposure to orchestration tools such as Airflow, Zapier, or Make</li><li>Understanding of AI governance, ethics, and performance monitoring</li></ul>What We Offer<ul><li>Opportunity to work on real-world, production-grade AI systems</li><li>Collaboration with international teams across multiple regions</li><li>High-impact role influencing automation and AI strategy at scale</li><li>Competitive compensation based on experience</li><li>Long-term growth within a fast-scaling global organization</li></ul>Job Type: Full-timeWork Location: In person

AI Workflow / AI Operations Engineer

RocketDevs

<div>
 
 RocketDevs empowers software engineers by bridging talent with global tech opportunities. We connect skilled developers with innovative projects, fostering an inclusive tech community.
 
 
 
 
 
 We are seeking a
 
 AI Engineer
 
 with a strong focus on
 
 AI systems and agent development
 
 to join our team and work on client projects that leverage modern AI capabilities. This is a
 
 full-time, remote position
 
 focused on building intelligent, scalable backend systems and AI-powered agents for global clients.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design, build, and maintain backend systems that power AI-driven applications.
 </li>
 <li>
 Develop and deploy
 
 AI agents
 
 capable of reasoning, planning, tool usage, and multi-step workflows.
 </li>
 <li>
 Integrate Large Language Models (LLMs) and AI APIs (e.g., OpenAI, Anthropic, Hugging Face) into backend services.
 </li>
 <li>
 Build and manage RESTful or GraphQL APIs for AI-powered features.
 </li>
 <li>
 Design data pipelines for storing prompts, embeddings, agent memory, and model outputs.
 </li>
 <li>
 Implement vector search and retrieval systems (e.g., embeddings, RAG pipelines).
 </li>
 <li>
 Optimize AI workflows for performance, cost, and reliability.
 </li>
 <li>
 Handle authentication, authorization, and secure access to AI services.
 </li>
 <li>
 Collaborate in architecture discussions, code reviews, and sprint planning.
 </li>
 <li>
 Explore and implement AI tooling to improve developer productivity and client outcomes.
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 <ul>
 <li>
 Strong software engineering experience with
 
 Python (FastAPI, Flask, Django)
 
 or
 
 Node.js (Express, NestJS)
 
 .
 </li>
 <li>
 Hands-on experience integrating
 
 LLMs or AI APIs
 
 into production systems.
 </li>
 <li>
 Experience building or experimenting with
 
 AI agents
 
 , including:
 </li>
 </ul>
 <ol>
 <li>
 Tool calling / function calling
 </li>
 <li>
 Multi-step reasoning or workflows
 </li>
 <li>
 Agent memory or state management
 </li>
 </ol>
 <ul>
 <li>
 Solid understanding of API design, async processing, and background jobs.
 </li>
 <li>
 Experience with databases such as:
 </li>
 </ul>
 <ol>
 <li>
 SQL (PostgreSQL - PgVector, MySQL)
 </li>
 <li>
 NoSQL (MongoDB)
 </li>
 <li>
 Vector databases (e.g., Pinecone, Weaviate, FAISS, Elasticsearch)
 </li>
 <li>
 Familiarity with Redis or similar caching layers.
 </li>
 </ol>
 <ul>
 <li>
 Experience with Git &amp; GitHub, Docker, and basic CI/CD workflows.
 </li>
 <li>
 Experience with
 
 web scraping and document parsing (HTML, PDFs).
 
 </li>
 <li>
 A
 
 deployed project
 
 (personal or professional) demonstrating an AI-powered backend system or agent is required.
 </li>
 </ul>
 
 
 
 
 
 Nice to Have
 
 
 <ul>
 <li>
 Experience with RAG (Retrieval-Augmented Generation) systems.
 </li>
 <li>
 Familiarity with agent frameworks (e.g., LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen).
 </li>
 <li>
 Experience with embeddings, prompt versioning, and evaluation.
 </li>
 <li>
 Familiarity with
 
 Model Context Protocol (MCP)
 
 or similar standards for connecting AI models to tools, data sources, and environments.
 </li>
 <li>
 Experience building or integrating
 
 automation workflows
 
 for AI systems (e.g., background jobs, task orchestration, event-driven workflows, or tools like Temporal, Airflow, n8n, Zapier).
 </li>
 <li>
 Knowledge of Kubernetes, serverless platforms, or Supabase.
 </li>
 <li>
 Understanding of AI safety, cost optimization, and observability.
 </li>
 <li>
 Familiarity with AI-assisted development tools or platforms.
 </li>
 </ul>
 
 
 
 
 
 Hiring Process
 
 
 
 We ensure a fair and transparent process for every applicant:
 
 
 
 Apply &rarr; Take a Compulsory 30-minute Assessment &rarr; 30-minute Onboarding Interview &rarr; Final interview &amp; selection
 
 
 
 
 
 
 
 Note
 
 
 <ul>
 <li>
 The assessment is mandatory. Please apply only if you&rsquo;re willing to take it.
 </li>
 <li>
 Having a deployed AI-powered backend project (personal or professional) is a must.
 </li>
 </ul>
</div>

AI Engineer (2+ years of Experience)

CreativeTalent

About the Agency: Creative Talent is at the intersection of human creativity and Artificial Intelligence. We build high-velocity video campaigns for top-tier US E-commerce brands. With millions of views across TikTok and Facebook, our work defines what &quot;modern advertising&quot; looks like.The Mission: We aren&rsquo;t looking for a traditional editor; we want a visual storyteller who can masterfully blend Adobe Premiere/After Effects with the latest AI tech (Sora, ElevenLabs, HeyGen) to create thumb-stopping UGC and review-style ads.What You&rsquo;ll Do:<ul><li>Engineer high-converting ads for the US market.</li><li>Integrate AI-generated voiceovers, B-roll, and avatars into seamless video narratives.</li><li>Design dynamic motion graphics and subtitles that drive engagement.</li><li>Rapidly iterate and test ad variations to find &quot;the winner.&quot;</li></ul>What We&rsquo;re Looking For:<ul><li>The Toolkit: Mastery of Premiere Pro and After Effects.</li><li>The Edge: A deep interest or experience in AI platforms (Leonardo, Veo, etc.).</li><li>The Mindset: A portfolio that proves you understand E-commerce pacing and &quot;the hook.&quot;</li></ul>The Package:<ul><li>The Upside: Performance-based commissions for winning ads.</li><li>Perks: Full health insurance, long-term career path, and global brand exposure.</li></ul>Job Type: Full-timePay: Rs100,000.00 - Rs120,000.00 per monthExperience:<ul><li>Video Editing: 2 years (Preferred)</li></ul>Language:<ul><li>English (Preferred)</li></ul>Work Location: In person

AI Video Editor

Mercurial Minds (Pvt) Ltd

Job Description &ndash; AI EngineerCompany: Mercurial Minds (Pvt.) Ltd. Location: Islamabad (On-site) Employment Type: Full-time Experience Required: 2&ndash;4 years (AI / Machine Learning / Applied Data Science)Company OverviewMercurial Minds (Pvt.) Ltd. is a forward-thinking technology and digital innovation company delivering end-to-end software solutions that help businesses transform, scale, and innovate through modern digital technologies. Our expertise spans cloud-native platforms, data-driven systems, AI-powered products, and large-scale digital transformation initiatives across telecom, media-tech, and enterprise environments.At Mercurial Minds, we focus on building intelligent, scalable, and production-ready systems that create measurable business value. We foster a culture of innovation, technical excellence, and continuous learning.Role OverviewWe are seeking an experienced and highly motivated AI Engineer to design, build, and deploy intelligent systems powered by modern AI technologies, including large language models (LLMs), machine learning, and advanced data pipelines.This role involves working on end-to-end AI solutions such as agentic systems, retrieval-augmented generation (RAG), semantic search, question-answering systems, summarization engines, recommendation systems, AI-powered matching platforms, and production-grade analytics solutions.The ideal candidate combines strong AI engineering expertise with applied machine learning knowledge and hands-on experience deploying scalable AI solutions in production environments.Key Responsibilities<ul><li>Design, develop, and optimize end-to-end AI-powered applications</li><li>Build and maintain RAG pipelines using vector databases, embeddings, and document processing workflows</li><li>Implement semantic search, filtering, and ranking systems across large and multi-source datasets</li><li>Fine-tune, evaluate, and deploy open-source LLMs and other machine learning models</li><li>Design scalable data pipelines for ingestion, cleaning, transformation, and storage</li><li>Deploy models and AI services using cloud infrastructure and containerization technologies</li><li>Collaborate with product, backend, and frontend teams to integrate AI capabilities into applications</li><li>Monitor model performance, latency, and operational costs, and continuously optimize system quality</li></ul>Required Skills &amp; Qualifications<ul><li>Bachelor&rsquo;s degree (BS) in Computer Science, Artificial Intelligence, Data Science, or a related field</li><li>Strong proficiency in Python programming and software engineering best practices</li><li>Hands-on experience with agentic and LLM frameworks such as LangChain, LlamaIndex, LangGraph, CrewAI, or similar</li><li>Experience working with vector databases (Pinecone, Weaviate, Milvus, FAISS, Chroma, etc.)</li><li>Solid understanding of NLP, embeddings, transformers, and semantic similarity techniques</li><li>Experience deploying models using Docker and cloud platforms (AWS, Azure, or GCP)</li><li>Familiarity with REST APIs and microservices architectures</li><li>Knowledge of data processing libraries (Pandas, NumPy) and machine learning frameworks (Scikit-learn, PyTorch, or TensorFlow)</li><li>Experience with model evaluation, prompt engineering, and performance optimization</li><li>Understanding of the full ML lifecycle including training, validation, deployment, and monitoring</li></ul>Nice to Have<ul><li>Experience fine-tuning open-source models (LoRA, PEFT, quantization)</li><li>Knowledge of MLOps tools such as MLflow, Weights &amp; Biases, Airflow, or Kubeflow</li><li>Background in data science or advanced analytics</li><li>Familiarity with graph databases or knowledge graphs</li><li>Experience building high-availability production systems</li><li>Master&rsquo;s degree (MS) in Computer Science, Artificial Intelligence, Data Science, or related field</li><li>Strong hands-on project experience in real-world AI applications</li></ul>What We Offer<ul><li>Opportunity to work on real-world, high-impact AI solutions</li><li>Exposure to cutting-edge AI and LLM technologies</li><li>Collaborative and fast-growing engineering environment</li><li>Competitive compensation and career growth opportunities</li></ul>Ideal Candidate ProfileYou are someone who enjoys taking AI ideas from concept to production, understands both theoretical foundations and practical implementation of modern AI systems, and actively stays current with rapidly evolving AI and LLM ecosystems.Job Type: Full-timeAbility to commute/relocate:<ul><li>Islamabad: Reliably commute or planning to relocate before starting work (Preferred)</li></ul>Application Question(s):<ul><li>Do you have hands-on experience building or deploying LLM-based applications (e.g., RAG pipelines, semantic search, or agentic systems) in a production or real-world environment?</li></ul><ul><li> Have you worked with vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus, Chroma) and deployed AI/ML models using cloud platforms or Docker?</li></ul>Location:<ul><li>Islamabad (Required)</li></ul>Work Location: In person

Explore 154+ Artificial intelligence engineer in Islamabad this March. Find roles across top companies and apply now to boost your career.

154 artificial intelligence engineer jobs In Islamabad

AI Engineer

AI Engineering Lead

FED TA DigitalHub - Mid STTA AI / Machine Learning Specialist/Developer

AI Workflow / AI Operations Engineer

AI Engineer (2+ years of Experience)

AI Video Editor

AI Engineer