AI Architect

Client company introduction:

It is a leading software engineering company delivering innovative, AI-powered platforms for global clients.

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 problemsolving and communication skills; ability to translate business requirements into technical designs. 

Experience :

5 + years

Work Timings:

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

Work Mode:

Onsite Karachi

Work Days :

Monday- Friday

About HR Ways:

Apply at jobs@hrways.co (not com)

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