GenAI Solution Architect AI/ML & GenAI
Industry Professionals · Lahore, Pakistan ·
- Work mode
- Hybrid
- Category
- ML ai
- Experience
- 3+ years
Industry Professionals · Lahore, Pakistan ·
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Senior architect role (12+ yrs) at a technology services firm: designing and leading delivery of generative-AI/ML systems — LLMs, RAG, agentic AI — on hybrid cloud while managing engineering teams of 8-12. Hybrid in Lahore, Karachi, or Islamabad, with possible relocation to Dubai. Stack: Python, LangChain, Kubernetes, AWS/Azure/GCP.
About the Role
We are seeking a GenAI Solution Architect for our client, a leading technology services firm. This hybrid role is open across Lahore, Karachi, Islamabad, and includes potential relocation to Dubai based on business needs.
The ideal candidate brings 12+ years of experience in enterprise software and systems, with a deep specialization in Generative AI (GenAI), AI/ML, and enterprise architecture. Youll lead multidisciplinary engineering teams and architect next-generation AI-powered systems across cloud, on-premises, and hybrid infrastructures.
Experience: 12+ Years
Locations: Lahore / Karachi / Islamabad (Hybrid)
GenAI Leadership (3+ Years)
Hands-on experience with LLMs (LLAMA, Mistral, GPT): fine-tuning, prompt optimization, deployment
Exposure to Agentic AI, Multi-Agent Systems, RAG implementations
Familiarity with LangChain, LangGraph, Vector Databases (e.g., Pinecone, FAISS)
Demonstrated success in delivering at least 3+ production-grade GenAI applications
AI/ML Engineering (4-5 Years)
Solid development background using Python, TensorFlow, PyTorch
Proven experience in ML lifecycle management: training, serving, monitoring
Integration of ML models into scalable enterprise architectures
Enterprise Architecture (8+ Years)
Experience in MERN stack or similar full-stack technology
Strong command over Kubernetes, Docker, and CI/CD pipelines
Deep understanding of REST APIs, GraphQL, microservices, and containerized deployments
Databases: SQL (PostgreSQL/MySQL) and NoSQL (MongoDB/DynamoDB)
Cross-environment deployment expertise: on-premises, cloud, and hybrid
Cloud & Infrastructure
Hands-on with cloud providers: AWS, Azure, or GCP
Familiarity with ML services: AWS SageMaker, Bedrock, Lambda, etc.
Experience designing hybrid cloud-AI architectures
Project & Team Delivery
Led delivery of 7+ enterprise-grade AI/ML solutions
Managed technical teams (812 engineers) across disciplines
Strong communication and stakeholder management skills
Agile/Scrum experience with demonstrable team performance outcomes
Certifications: AWS/Azure/GCP (Solutions Architect, ML Specialty preferred)
Experience designing Agentic AI workflows with user-centric GenAI solutions
Contributions to open-source GenAI libraries or AI research papers
Primary Expertise: GenAI Architecture & Leadership
Secondary Expertise: AI/ML Development & Model Integration
Tertiary Expertise: Enterprise System Design & Scalable Deployment
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