We are seeking a Senior AI & Generative AI Specialist to architect, build, and scale production-grade AI and GenAI solutions. The role demands deep hands-on expertise, strong system architecture skills, and the ability to lead cross-functional teams delivering result oriented & compliant AI systems.

Design and architect enterprise-scale AI and Generative AI systems, including LLM-based applications, RAG pipelines, fine-tuned models, and multimodal AI systems.

Lead development of AI platforms and frameworks enabling reusable, scalable AI services (AI-as-a-Service).

Define model selection strategies, fine-tuning approaches, and inference optimization.

Develop and deploy advanced ML/DL models across: Computer Vision (segmentation, detection, classification); NLP (BERT, GPT, Transformers); Generative AI (Diffusion models, GANs, multimodal systems); Time-series forecasting, predictive analytics, anomaly detection.

Drive model optimization, hyperparameter tuning, and performance benchmarking.

Ensure model explainability, fairness, bias detection, and mitigation.

Build GenAI applications & Agents including: Intelligent document processing; Automated report generation; Smart ticketing and customer escalation systems; Knowledge assistants using RAG + vector databases.

Implement prompt engineering, evaluation frameworks, and guardrails.

Optimize inference cost, latency, and scalability in cloud environments.

Establish MLOps best practices: CI/CD for ML; Model versioning and monitoring; Automated retraining pipelines.

Deploy AI services using Docker, Kubernetes, MLflow, FastAPI, Flask.

Ensure high availability, low latency, and cloud cost optimization.

Architect AI workloads on Azure, Databricks, Spark.

Build scalable data pipelines for large-scale training and inference.

Leverage distributed computing for large datasets and real-time inference.

Consult and mentor AI engineering and data science teams.

Collaborate with the AI working group & international stakeholder community.

Translate business and domain problems into AI solutions with measurable impact.

Drive innovation initiatives, patents, and hackathon-level experimentation.