495 AI Architect jobs in Pakistan

One of our prestigious client is looking for a hands-on AI Architect who bridges software development, data engineering, and advanced AI/ML. You will design and code AI solutions that leverage large language models, embeddings and retrieval‑augmented generation while ensuring robust data pipelines and integration with our software products. This role requires a strong foundation in software engineering and data engineering along with deep expertise in AI/ML.

Key Responsibilities:

1. Cross‑Disciplinary Solution Design

Engage with stakeholders to understand product requirements and architect end‑to‑end solutions incorporating data ingestion, model training, deployment and monitoring.

Design systems that combine traditional software components with AI/ML models and modern data engineering practices.

1. Hands‑On Development

Write and maintain production‑quality code across back‑end services, data pipelines and model inference layers, primarily using Python and at least one other language (e.g. .Net, Java).

Build RESTful or gRPC APIs to expose AI functionality and integrate with front‑end and other microservices.

1. Data Engineering & Pipeline Construction

Develop and manage data pipelines for ingestion, transformation and storage (using tools such as Apache Spark, Kafka, Airflow, SQL/NoSQL databases).

Work with vector databases and embedding stores for retrieval‑augmented systems.

Ensure data quality, schema management and robust ETL processes that support model training and inference.

1. Advanced AI/ML & LLM Expertise

Train, fine‑tune and deploy machine‑learning and deep‑learning models, including large language models (LLMs) and transformer architectures (e.g., GPT, Llama, Mistral).

Implement embedding techniques (e.g., sentence and document embeddings), retrieval‑augmented generation (RAG) pipelines and hybrid search (vector + keyword).

Build customised pipelines using frameworks like LangChain, LLamaIndex or similar to integrate models with diverse data sources.

1. System Optimisation & Scalability

Optimise model performance (latency, throughput and accuracy) for production workloads, using techniques such as model quantisation, batching and caching.

Scale services using containerisation (Docker) and orchestration (Kubernetes) on cloud platforms (AWS, Azure, GCP).

1. Collaboration & Mentorship

Collaborate with software engineers, data scientists and DevOps teams to deliver cohesive solutions.

Mentor junior engineers and share best practices in software development, data engineering and AI/ML.

1. Monitoring & Maintenance

Implement observability for data pipelines and AI services (logging, metrics, model drift detection).

Continuously monitor and iterate models and pipelines based on feedback and new data.

Required Skills & Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Engineering, Artificial Intelligence or related field.
• Experience: Minimum 6–8 years in software development and data engineering, with at least 3 years of hands‑on AI/ML experience.
• Proficiency in Python and deep familiarity with AI/ML frameworks (e.g., PyTorch, TensorFlow, Scikit‑learn) and LLM libraries (e.g., Hugging Face Transformers, LangChain).
• Hands‑on experience building and deploying large language models, embeddings, RAG pipelines and vector‑database‑powered applications.
• Strong knowledge of data engineering tools (Spark, Kafka, Airflow), relational and NoSQL databases, and proficiency in SQL.
• Experience designing and operating microservices, APIs and containerised applications on cloud platforms.
• Solid understanding of MLOps best practices (CI/CD for ML, model versioning, automated testing, monitoring).
• Strong problem‑solving and communication skills; ability to translate business requirements into technical designs.

Preferred Qualifications:

• Experience with GPU orchestration (NVIDIA Triton, KServe) for model serving.
• Knowledge of privacy‑preserving techniques and responsible AI practices.
• Exposure to reinforcement learning or recommendation systems.

What We Offer:

The chance to work on cutting‑edge AI projects integrating software, data and advanced models.

A collaborative environment where hands‑on coding and architectural leadership go hand in hand.

Support for ongoing learning and professional development in AI/ML and data engineering.

Health Insurance

Gadget Allowance

Job Title
: GEN AI Architect

Location
: Onsite, Lahore

Need to have exp
. :Atleast 2 project on Gen AI

Job Summary
:

We are seeking a highly skilled GEN AI Architect with extensive experience in designing and deploying AI powered agents and architectures. The ideal candidate will have a strong background in large language models (LLMs) and a proven track record of implementing scalable AI solutions that align with business objectives. This role requires a blend of technical expertise, strategic thinking, and excellent communication skills to collaborate effectively with cross functional teams.

Responsibilities
:

• Define & Design AI Architectures: Establish scalable, modular, and efficient architectures for AI agents, LLM based applications, and generative AI models.
• Hands on AI Development: Implement and optimize generative AI models using frameworks such as OpenAI, LangChain, and RAG.
• AI Integration & Deployment: Work with cloud AI platforms (Azure, Google Cloud Platform) to implement best practices for MLOps, model serving, and continuous improvement.
• Enterprise AI Strategy: Align AI driven solutions with business objectives, ensuring scalability, security, and cost effectiveness.
• Cross functional Collaboration: Engage with product teams, data scientists, and engineering teams to ensure seamless integration of AI powered solutions into business workflows.
• AI Governance & Ethics: Establish responsible AI practices, ensuring compliance with data privacy, model bias mitigation, and security best practices.
• Evaluation & Optimization: Continuously assess AI agent performance and optimize for improved outcomes.

Mandatory Skills
:

• Hands on experience in designing and deploying AI powered agents and multi agent architectures.
• Expertise in Large Language Models (LLMs) such as GPT, BERT, and Llama.
• Proficiency in AI frameworks like TensorFlow, PyTorch, and Hugging Face.
• Strong knowledge of retrieval augmented generation (RAG) and vector databases (e.g., Vector DBs).
• Experience with cloud AI services (Azure Cognitive Services) and containerized deployment using Docker and Kubernetes.
• Strong background in API driven development, API and Microservices, and event driven architectures.
• Experience with MLOps, CI/CD Pipeline, and monitoring AI models in production.
• Excellent problem solving, analytical thinking, and effective communication skills.
• Preferred Skills:
• Experience with AI orchestration/agents frameworks, including AG2, CrewAI, and AutoGPT.
• Familiarity with multi modal AI models (text, image, video, audio) and AI personalization techniques.
• Knowledge of Responsible AI principles, including bias mitigation and explainability.
• Advanced academic background (PhD/Master's) in AI, ML, Data Science, or a related field.

Qualifications
:

The ideal candidate will possess a strong technical foundation in AI architecture and development, with a focus on delivering innovative solutions that drive business value. A commitment to responsible AI practices and a passion for continuous learning in the rapidly evolving AI landscape are essential.

AI Architect – Software & Data Engineering, LLM/RAG Specialist

• Location: Hybrid (3 days onsite / 2 days remote -Karachi or Islamabad)
• Type: Full‑time

About the Role

We are looking for a hands-on AI Architect who bridges software

development, data engineering, and advanced AI/ML. You will design and code AI solutions that leverage large language models, embeddings and retrieval‑augmented generation while ensuring robust data pipelines and integration with our software products. This role requires a strong foundation in software engineering and data engineering along with deep expertise in AI/ML.

Key Responsibilities

1. Cross‑Disciplinary Solution Design

○ Engage with stakeholders to understand product requirements and architect

end‑to‑end solutions incorporating data ingestion, model training, deployment

and monitoring.

○ Design systems that combine traditional software components with AI/ML models

and modern data engineering practices.

1. Hands‑On Development

○ Write and maintain production‑quality code across back‑end services, data

pipelines and model inference layers, primarily using Python and at least one

other language (e.g. .Net, Java).

○ Build RESTful or gRPC APIs to expose AI functionality and integrate with

front‑end and other microservices.

1. Data Engineering & Pipeline Construction

○ Develop and manage data pipelines for ingestion, transformation and storage

(using tools such as Apache Spark, Kafka, Airflow, SQL/NoSQL databases).

○ Work with vector databases and embedding stores for retrieval‑augmented

systems.

○ Ensure data quality, schema management and robust ETL processes that

support model training and inference.

1. Advanced AI/ML & LLM Expertise

○ Train, fine‑tune and deploy machine‑learning and deep‑learning models,

including large language models (LLMs) and transformer architectures (e.g.,

GPT, Llama, Mistral).

○ Implement embedding techniques (e.g., sentence and document embeddings),

retrieval‑augmented generation (RAG) pipelines and hybrid search (vector +

keyword).

○ Build customised pipelines using frameworks like LangChain, LLamaIndex or

similar to integrate models with diverse data sources.

1. System Optimisation & Scalability

○ Optimise model performance (latency, throughput and accuracy) for production

workloads, using techniques such as model quantisation, batching and caching.

○ Scale services using containerisation (Docker) and orchestration (Kubernetes) on

cloud platforms (AWS, Azure, GCP).

1. Collaboration & Mentorship

○ Collaborate with software engineers, data scientists and DevOps teams to deliver

cohesive solutions.

○ Mentor junior engineers and share best practices in software development, data

engineering and AI/ML.

1. Monitoring & Maintenance

○ Implement observability for data pipelines and AI services (logging, metrics,

model drift detection).

○ Continuously monitor and iterate models and pipelines based on feedback and

new data.

Required Skills & Qualifications

● Bachelor's or Master's degree in Computer Science, Data Engineering, Artificial

Intelligence or related field.

● Experience: Minimum 6–8 years in software development and data engineering, with at

least 3 years of hands‑on AI/ML experience.

● Proficiency in Python and deep familiarity with AI/ML frameworks (e.g., PyTorch,

TensorFlow, Scikit‑learn) and LLM libraries (e.g., Hugging Face Transformers,

LangChain).

● Hands‑on experience building and deploying large language models, embeddings, RAG

pipelines and vector‑database‑powered applications.

● Strong knowledge of data engineering tools (Spark, Kafka, Airflow), relational and

NoSQL databases, and proficiency in SQL.

● Experience designing and operating microservices, APIs and containerised applications

on cloud platforms.

● Solid understanding of MLOps best practices (CI/CD for ML, model versioning,

automated testing, monitoring).

● Strong problem‑solving and communication skills; ability to translate business

requirements into technical designs.

Preferred Qualifications

● Experience with GPU orchestration (NVIDIA Triton, KServe) for model serving.

● Knowledge of privacy‑preserving techniques and responsible AI practices.

● Exposure to reinforcement learning or recommendation systems.

What We Offer

● The chance to work on cutting‑edge AI projects integrating software, data and advanced

models.

● A collaborative environment where hands‑on coding and architectural leadership go

hand in hand.

● Support for ongoing learning and professional development in AI/ML and data

engineering.

● Health Insurance

● Gadget Allowance

Job Type: Full-time

Pay: Rs300, Rs350,000.00 per month

Work Location: In person

We're Hiring: Senior AI Infrastructure Engineer (Immediate Joiner)

At
Blue Clay Health
, we're building technology that transforms how healthcare works in the U.S. Our mission is to create intelligent, scalable platforms that improve outcomes for both patients and providers.

We're looking for a
Senior AI Infrastructure Engineer
to design, deploy, and operate the secure AI backbone that powers our platform. This role spans GPU infrastructure, LLM serving, retrieval systems, and HIPAA-grade cloud security. You'll work with leading open-weight models (e.g., Llama 3, Mixtral, MedGemma) and build the systems that make them safe, reliable, and production-ready. This is a critical early role with room to shape both system architecture and team direction.

What You'll Do

• Design and deploy GPU-powered AI inference infrastructure on
  Google Cloud.
• Manage secure model storage, orchestration, and private networking in a regulated environment.
• Build and optimize the retrieval and search stack that combines keyword and semantic search with smart reranking.
• Integrate and operate both general-purpose AI models (e.g., Llama, Mixtral) and specialist clinical models (e.g., MedGemma).
• Develop event-driven services that power system safeguards, provenance tracking, and issue resolution.
• Ensure full HIPAA compliance through encryption, access controls, logging, and secure compute environments.
• Implement scalable monitoring and autoscaling for high-throughput workloads using standard observability tools.
• Collaborate closely with application engineers to deliver RAG, automated reports, and clinician-facing safety features.

Tech Stack

• Cloud & Infra:
  GCP (GKE private clusters, A3/H100 GPUs, VPC-SC, CMEK, Pub/Sub, Secret Manager)
• Inference:
  vLLM, TensorRT-LLM, NVIDIA Triton
• Models:
  Llama 3, Mixtral, MedGemma, RoBERTa/DeBERTa-based classifiers, SapBERT, bge-m3 embeddings, cross-encoders
• Datastores:
  OpenSearch (BM25), pgvector/Weaviate (dense), AlloyDB/CloudSQL
• Pipelines:
  Kubernetes microservices, event-driven with Pub/Sub
• Monitoring:
  Prometheus, Grafana, GCP Cloud Logging/Monitoring

What We're Looking For

• Experience deploying 70B+ open-weight LLMs (Llama 2/3, Mixtral) on multi-GPU clusters.
• Deep comfort with GCP infrastructure:
  GKE, GPU node pools, VPC-SC, CMEK, private-only networking.
• Hands-on with retrieval pipelines: embeddings, hybrid search, cross-encoder rerankers, vector DB tuning.
• Ability to orchestrate multiple models and services into a coherent, production pipeline.
• Practical understanding of HIPAA / PHI-safe architectures and how to implement them on GCP.
• Strong in Kubernetes/containerization, monitoring GPU workloads, and cost-managing high-performance compute.
• Bonus: prior healthcare or regulated-data experience, safeguard systems, or MedGemma deployments.
• Pragmatic, resilient, and motivated to build infrastructure that matters.

Why Join Blue Clay Health?

• Build mission-critical AI that improves patient outcomes.
• Collaborate with top AI, data, and health experts.
• Immediate onboarding and flexible remote setup.

Compensation

• Competitive compensation aligned with experience and impact.

How to Apply

If you're excited to build secure, production-grade AI infrastructure from the ground up—and want your work to matter—we'd love to hear from you.

Job Title: AI Architect – Software & Data Engineering, LLM/RAG Specialist

Location: Hybrid (3 days onsite / 2 days remote -Karachi or Islamabad)

Type: Full‑time

About the Role

We are looking for a hands-on AI Architect who bridges software development, data engineering, and advanced AI/ML. You will design and code AI solutions that leverage large language models, embeddings and retrieval‑augmented generation while ensuring robust data pipelines and integration with our software products. This role requires a strong foundation in software engineering and data engineering along with deep expertise in AI/ML.

Key Responsibilities

1. Cross‑Disciplinary Solution Design

○ Engage with stakeholders to understand product requirements and architect

end‑to‑end solutions incorporating data ingestion, model training, deployment

and monitoring.

○ Design systems that combine traditional software components with AI/ML models

and modern data engineering practices.

1. Hands‑On Development

○ Write and maintain production‑quality code across back‑end services, data

pipelines and model inference layers, primarily using Python and at least one

other language (e.g. .Net, Java).

○ Build RESTful or gRPC APIs to expose AI functionality and integrate with

front‑end and other microservices.

1. Data Engineering & Pipeline Construction

○ Develop and manage data pipelines for ingestion, transformation and storage

(using tools such as Apache Spark, Kafka, Airflow, SQL/NoSQL databases).

○ Work with vector databases and embedding stores for retrieval‑augmented

systems.

○ Ensure data quality, schema management and robust ETL processes that

support model training and inference.

1. Advanced AI/ML & LLM Expertise

○ Train, fine‑tune and deploy machine‑learning and deep‑learning models,

including large language models (LLMs) and transformer architectures (e.g.,

GPT, Llama, Mistral).

○ Implement embedding techniques (e.g., sentence and document embeddings),

retrieval‑augmented generation (RAG) pipelines and hybrid search (vector +

keyword).

○ Build customised pipelines using frameworks like LangChain, LLamaIndex or

similar to integrate models with diverse data sources.

1. System Optimisation & Scalability

○ Optimise model performance (latency, throughput and accuracy) for production

workloads, using techniques such as model quantisation, batching and caching.

○ Scale services using containerisation (Docker) and orchestration (Kubernetes) on

cloud platforms (AWS, Azure, GCP).

1. Collaboration & Mentorship

○ Collaborate with software engineers, data scientists and DevOps teams to deliver

cohesive solutions.

○ Mentor junior engineers and share best practices in software development, data

engineering and AI/ML.

1. Monitoring & Maintenance

○ Implement observability for data pipelines and AI services (logging, metrics,

model drift detection).

○ Continuously monitor and iterate models and pipelines based on feedback and

new data.

Required Skills & Qualifications

● Bachelor's or Master's degree in Computer Science, Data Engineering, Artificial

Intelligence or related field.

● Experience: Minimum 6–8 years in software development and data engineering, with at

least 3 years of hands‑on AI/ML experience.

● Proficiency in Python and deep familiarity with AI/ML frameworks (e.g., PyTorch,

TensorFlow, Scikit‑learn) and LLM libraries (e.g., Hugging Face Transformers,

LangChain).

● Hands‑on experience building and deploying large language models, embeddings, RAG

pipelines and vector‑database‑powered applications.

● Strong knowledge of data engineering tools (Spark, Kafka, Airflow), relational and

NoSQL databases, and proficiency in SQL.

● Experience designing and operating microservices, APIs and containerised applications

on cloud platforms.

● Solid understanding of MLOps best practices (CI/CD for ML, model versioning,

automated testing, monitoring).

● Strong problem‑solving and communication skills; ability to translate business

requirements into technical designs.

Preferred Qualifications

● Experience with GPU orchestration (NVIDIA Triton, KServe) for model serving.

● Knowledge of privacy‑preserving techniques and responsible AI practices.

● Exposure to reinforcement learning or recommendation systems.

What We Offer

● The chance to work on cutting‑edge AI projects integrating software, data and advanced

models.

● A collaborative environment where hands‑on coding and architectural leadership go

hand in hand.

● Support for ongoing learning and professional development in AI/ML and data

engineering.

● Health Insurance

● Gadget Allowance

Job Type: Full-time

Pay: Rs300, Rs350,000.00 per month

Work Location: In person

Key Responsibilities

• 1. Cross Disciplinary Solution Design
• Engage with stakeholders to understand product requirements and architect endtoend solutions incorporating data ingestion, model training, deployment and monitoring.
• Design systems that combine traditional software components with AI/ML models and modern data engineering practices.
• 2. HandsOn Development
• Write and maintain production-quality code across backend services, data pipelines and model inference layers, primarily using Python and at least one other language (e.g., .Net, Java).
• Build RESTful or gRPC APIs to expose AI functionality and integrate with the frontend and other microservices.
• 3. Data Engineering & Pipeline Construction
• Develop and manage data pipelines for ingestion, transformation and storage (using tools such as Apache Spark, Kafka, Airflow, SQL/NoSQL
  databases).
• Work with vector databases and embedding stores for retrieval-augmented systems.
• Ensure data quality, schema management and robust ETL processes that support model training and inference.
• 4. Advanced AI/ML & LLM Expertise
• Train, finetune and deploy machinelearning and deeplearning models, including large language models (LLMs) and transformer architectures (e.g., GPT, Llama, Mistral).
• Implement embedding techniques (e.g., sentence and document embeddings), retrievalaugmented generation (RAG) pipelines and hybrid search (vector + keyword).
• Build customised pipelines using frameworks like LangChain, LLamaIndex or similar to integrate models with diverse data sources.
• 5. System Optimisation & Scalability
• Optimise model performance (latency, throughput and accuracy) for production workloads, using techniques such as model quantisation, batching and caching.
• Scale services using containerisation (Docker) and orchestration (Kubernetes) on cloud platforms (AWS, Azure, GCP).
• 6. Collaboration & Mentorship
• Collaborate with software engineers, data scientists and DevOps teams to deliver cohesive solutions.
• Mentor junior engineers and share best practices in software development, data engineering and AI/ML.
• 7. Monitoring & Maintenance
• Implement observability for data pipelines and AI services (logging, metrics, model drift detection).
• Continuously monitor and iterate models and pipelines based on feedback and new data.
• Requirements & Qualifications
• Bachelors or Masters degree in Computer Science, Data Engineering, Artificial Intelligence or related field.
• Experience: Minimum 6 to 8 years in software development and data engineering, with at least 3 years of handson AI/ML experience.
• Proficiency in Python and deep familiarity with AI/ML frameworks (e.g., PyTorch, TensorFlow, Scikitlearn) and LLM libraries (e.g., Hugging Face Transformers, LangChain).
• Handson experience building and deploying large language models, embeddings, RAG pipelines and vectordatabasepowered applications.
• Strong knowle dge of data engineering tools (Spark, Kafka, Airflow), relational and NoSQL databases, and proficiency inSQL.
• Experience designing and operating microservices, APIs and containerised applications on cloud platforms.
• Solid understanding of MLOps best practices (CI/CD for ML, model versioning, automated testing, monitoring).
• Strong problem solving and communication skills; ability to translate business requirements into technical designs.

Experience :

5 + years

Work Timings:

(Monday to Friday: 11:00
AM - 7:30 PM)

Work Mode:

Onsite Karachi

Work Days :

Monday- Friday

Overview

Translation Empire PK is hiring an AI Solutions Architect to lead the end-to-end design and implementation of AI-powered systems. You will work closely with technical and business teams to ensure that AI strategies align with organizational goals and are successfully deployed at scale.

• Design scalable, reliable AI architectures and solutions.
• Define system requirements, interfaces, and integration plans.
• Provide technical leadership across AI projects.
• Guide data and ML engineering best practices.
• Review code and system designs for compliance and performance.

• Master’s degree in Computer Science, AI, or related discipline.
• 5+ years of experience in AI system design and architecture.
• Expertise in cloud-native AI solutions (AWS/GCP/Azure).
• Deep understanding of MLOps and deployment strategies.
• Excellent communication and stakeholder management skills.

Certification: Cloud or AI-related certifications are preferred.

Work mode: Work from Office.

Location: DHA 1 Sector F Rwp.

Salary: Market Competitive.

Job Description
Translation Empire PK is hiring an AI Solutions Architect to lead the end-to-end design and implementation of AI-powered systems. You will work closely with technical and business teams to ensure that AI strategies align with organizational goals and are successfully deployed at scale.

Key Responsibilities:

• Design scalable, reliable AI architectures and solutions.
• Define system requirements, interfaces, and integration plans.
• Provide technical leadership across AI projects.
• Guide data and ML engineering best practices.
• Review code and system designs for compliance and performance.

Qualification and Experience:

• Master’s degree in Computer Science, AI, or related discipline.
• 5+ years of experience in AI system design and architecture.
• Expertise in cloud-native AI solutions (AWS/GCP/Azure).
• Deep understanding of MLOps and deployment strategies.
• Excellent communication and stakeholder management skills.

Certification:
Cloud or AI-related certifications are preferred.

Work mode:
Work from Office.

Location:
DHA 1 Sector F Rwp.

Salary:
Market Competitive.

• Design scalable, reliable AI architectures and solutions
• Define system requirements, interfaces, and integration plans
• Provide technical leadership across AI projects
• Guide data and ML engineering best practices
• Review code and system designs for compliance and performance
  
  

• Master's degree in Computer Science, AI, or related discipline
• 5+ years of experience in AI system design and architecture
• Expertise in cloud-native AI solutions (AWS/GCP/Azure)
• Deep understanding of MLOps and deployment strategies
• Excellent communication and stakeholder management skills