Principal AIML Architect

Must Have Skills
Core

• 10–15 years of experience in software engineering .
• Strong programming skills in Python (mandatory).
• Experience in building production-grade ML systems (not just notebooks).

AI/ML & GenAI

• Hands-on experience with:
• Data Analysis and curation
• Feature engineering
• Statistical model training, evaluation, and hyperparameter tuning
• LLMs / GenAI applications
• RAG pipeline design
• Prompt engineering & model tuning
• Experience with frameworks like Tensorflow, PyTorch, Sci-kit, LangChain

LlamaIndex, or similar.

• Understanding of embeddings, vector search, and retrieval systems.
• Exposure to custom model fine-tuning (good to have, not mandatory).

MLOps & Deployment

• Experience with:
• Model deployment (API-based or batch)
• CI/CD pipelines for ML
• Monitoring and logging
• Familiarity with tools like MLflow, Kubeflow, or similar (any one is fine).

Cloud & Scalability

• Experience with at least one cloud: AWS / Azure / GCP.
• Understanding of scalable system design and APIs.

Data & Systems

• Working knowledge of databases (SQL/NoSQL).
• Experience with vector databases (Milvus, Pinecone, Weaviate, FAISS, etc.).

Good to Have (Optional)

• Experience in AIOps or AI for observability/use-case automation.
• Background in data engineering or analytics pipelines.
• Exposure to Kubernetes/Docker.

Experience in telecom or high-scale product environments.