266 Generative AI Engineer jobs in Pakistan

We are seeking a Generative AI Engineer to lead the design, development, and deployment of agentic, multi-step AI systems. You will build robust, scalable pipelines powered by LLMs, multi-agent architectures, MCP interoperability, advanced data processing, and best-in-class engineering practices. The ideal candidate excels in Python development, systems design, and delivering solutions through the full software lifecycle.

Architect and implement multi-agent workflows using LangChain, LangGraph, AutoGen, CrewAI, Google ADK, CAMEL, Swarm, and OpenAI Agents SDK to orchestrate task decomposition, memory, tool use, and agent coordination.

Engineer workflows that use MCP for context-sharing and standardized communication among agents and with external systems (SQL, file systems, tools).

Agent Framework Development

Design abstracted agent frameworks supporting planning, reasoning, retries, orchestration, and observability.

Develop ETL pipelines for ingestion, transformation, storage, and embedding generation using Airflow, Prefect, Spark, Hadoop, and vector databases (FAISS, Pinecone, Weaviate).

LLM Fine‑Tuning & RAG Architecture

Fine‑tune GPT, LLaMA, Claude, Mistral models with efficient methods; build retrieval‑augmented systems using vector DBs and knowledge graphs.

Integrate text, image, audio, OCR, and structured data (via CLIP, Whisper, TTS/STT); expose capabilities through REST/GraphQL APIs and microservices.

Follow core Python engineering practices—OOP, async, unit testing, packaging. Containerize with Docker and deploy on Kubernetes or serverless infra.

Ethics, Security & Performance Optimization

Integrate bias detection, explainability, privacy safeguards (prompt injection mitigation), and optimize performance and cost.

Education:

BSc or MSc in Computer Science, Engineering, Data Science, or equivalent.

Technical Skills:

Python: Advanced proficiency in OOP, async programming, packaging, testing.

LLM Frameworks: Hugging Face Transformers, PyTorch, TensorFlow.

Agent Frameworks: Experience with LangChain, LangGraph, AutoGen, CrewAI, ADK.

Protocols: Deep understanding of MCP, A2A, and agent interoperability.

Cloud & Containerization: Experience with AWS, GCP, Azure, Docker, Kubernetes.

RAG Systems: Expertise in FAISS, Pinecone, ChromaDB, Weaviate, and knowledge graphs.

Software Quality & Architecture: Strong foundations in system design, scalability, security, and CI/CD best practices.

Deep familiarity with prompt engineering, decision chaining, and tool integrations.

Background in reinforcement learning, planning, or control-loop architectures.

Soft Skills:

Excellent communication and collaboration across multidisciplinary teams.

Analytical mindset with strong debugging and iterative development approach.

Agile-oriented: rapid experimentation, evaluation, and adaptation.

Join to apply for the Senior Generative AI Engineer role at Ähdus Technology GmbH

Join to apply for the Senior Generative AI Engineer role at Ähdus Technology GmbH

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Job Title: Senior Generative AI Engineer

Location: Bahria Town, Phase 7, Rawalpindi

Employment Type: Full-Time

About the Role:

We are looking for a Senior Generative AI Engineer to lead the design and development of cutting-edge generative AI systems that produce human-like content such as text, images, code, and audio. You will play a key role in building and deploying large-scale models (e.g., LLMs, diffusion models), optimizing performance, and integrating them into real-world applications.

Key Responsibilities:

• Design and implement generative AI models (e.g., GPT, Stable Diffusion, VAEs, GANs) for various use cases.
• Fine-tune and optimize large language models (LLMs) using techniques like LoRA, PEFT, or RLHF.
• Collaborate with product and research teams to turn ideas into working AI-powered features.
• Develop scalable training and inference pipelines using modern ML infrastructure.
• Analyze model outputs for quality, bias, and safety, and implement necessary safeguards.
• Stay up to date with the latest research in generative AI and apply state-of-the-art techniques.
• Lead and mentor junior engineers and contribute to architectural decisions.
  
  
  

• Master’s or PhD in Computer Science, Machine Learning, AI, or related field.
• 4+ years of hands-on experience in machine learning, with at least 2 years in generative models.
• Deep understanding of transformer architectures, diffusion models, embeddings, and prompt engineering.
• Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow.
• Experience with model deployment, optimization (e.g., quantization, distillation), and cloud AI tools.
• Familiarity with data curation, synthetic data generation, and ethical considerations in generative AI.
• Excellent communication skills and ability to work cross-functionally.
  
  
  

• Experience with OpenAI, Hugging Face, or similar platforms.
• Contributions to generative AI research or open-source projects.
• Experience with multimodal models (text+image, text+audio, etc.).

• Seniority level Not Applicable

• Employment type Full-time

• Job function Engineering and Information Technology
• Industries IT Services and IT Consulting

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• Design, train, and validate machine learning models
• Process and clean large datasets for training
• Automate model pipelines and deployment
• Monitor and retrain models for performance enhancement
• Collaborate on research and development initiatives
  
  

• Bachelor's or Master's in Computer Science, ML, or similar
• 3+ years of experience in ML engineering
• Experience with Python, TensorFlow, and scikit-learn
• Familiarity with Docker, Kubernetes, and cloud services
  
  

We build cutting edge Cloud-based solutions used by over 15,000 companies worldwide, primarily in the US, Australia, and Canada. Our goal is to be the leading SaaS provider for enterprises. Our clients include NASA, 3M, Disney, Amazon, and more.

We're seeking Deep Learning Engineers to enhance our products through AI/ML for recommendations, pattern recognition, and creating smarter systems to boost efficiency.

Requirements:

• Implement machine learning algorithms effectively
• Strong understanding of statistics and deep learning fundamentals
• Solid engineering background with the ability to develop production-ready services
• Proficiency in an object-oriented programming language
• Experience in building efficient, optimized systems, including parallel processing with GPUs for fast response times
• At least 2-3 years of proven experience in deep learning or machine learning

Responsibilities:

• Develop pipelines capable of handling large-scale deep learning data
• Conduct experiments for hypothesis testing
• Continuous optimization of models and systems

• Design, train, and validate machine learning models
• Process and clean large datasets for training
• Automate model pipelines and deployment
• Monitor and retrain models for performance enhancement
• Collaborate on research and development initiatives
  
  

• Bachelor's or Master's in Computer Science, ML, or similar
• 3+ years of experience in ML engineering
• Experience with Python, TensorFlow, and scikit-learn
• Familiarity with Docker, Kubernetes, and cloud services
  
  

Job Description

Build autonomous AI-driven agents for tasks such as reasoning, decision-making, automation, and contextual understanding.

Customize and deploy GPT, LLaMA, Claude, Mistral, and other foundation models to solve industry-specific challenges.

Design scalable, production-ready AI workflows using Python, LangChain, LlamaIndex, OpenAI functions, and AutoGPT.

Enhance AI agents with retrieval-augmented generation (RAG), vector databases (FAISS, Pinecone, Weaviate, ChromaDB), and knowledge graphs.

Work with text, images, audio, and structured data to create multimodal AI applications.

Implement reinforcement learning, agentic workflows, and action-planning techniques to enhance AI autonomy.

Optimize and deploy models on cloud platforms (AWS, Azure, GCP) and ensure efficiency in a microservices-based architecture.

Leverage few-shot learning, prompt chaining, and tool-use APIs to improve AI reasoning capabilities.

Develop responsible AI solutions by addressing bias, explainability, and security concerns.

Proven experience developing GenAI-powered applications and AI agents.

Strong proficiency in Python and AI/ML frameworks (TensorFlow, PyTorch, Hugging Face, LangChain, LlamaIndex, OpenAI API).

Hands-on expertise in LLM fine-tuning, model adaptation, and prompt engineering.

Familiarity with vector databases (FAISS, Pinecone, Weaviate, ChromaDB) and knowledge retrieval techniques.

Experience integrating AI with APIs, automation frameworks, and microservices.

Working knowledge of cloud-based AI deployment (AWS, Azure, GCP).

Understanding of NLP, reinforcement learning, and multi-agent architectures.

Strong problem-solving skills, ability to work independently, and in a collaborative team environment.

Excellent communication skills with a passion for AI-driven innovation.