Job Title

Principal AI-ML ArchitectRole Overview We are looking for an AI/ML Architect with strong hands-on experience in Python-based ML systems and GenAI solutions. This role focuses on designing and deploying production-grade AI systems, especially leveraging LLMs, RAG pipelines, and MLOps practices. You will work closely with engineering and product teams to build scalable, secure, and efficient AI-powered applications.Key Responsibilities ❖ AI/ML System Design ● Design and implement end-to-end ML pipelines (data ingestion → training → evaluation → deployment). ● Architect LLM-based solutions using advanced prompting strategies, RAG (Retrieval-Augmented Generation) and agentic workflows. ● Define scalable patterns for ML/ GenAI application development. ❖ Model Development & Optimization ● Work on data analysis, quality benchmarking, lineage detection and curation, ingestion into vector stores ● Work on statistical model training, evaluation, hyper-parameter tuning, feature engineering ● Work on fine-tuning of LLMs for specific tasks and prompt optimization (no expectation to build models from scratch at large scale). ● Evaluate and select appropriate models (open weights or closed weights). ● Collaborate with data teams for feature engineering and dataset readiness. ❖ MLOps & Deployment ● Implement MLOps best practices: ○ Model versioning ○ Experiment tracking ○ Monitoring & retraining pipelines ○ Prompt versioning ○ Drift detection ○ Token costs ● Handle model deployment in production environments (APIs, batch, streaming). ● Ensure performance, scalability, and reliability of AI systems. ❖ Platform & Integration ● Integrate AI solutions with existing microservices and backend systems. ● Work with vector databases, caching, and APIs for GenAI use cases. ● Ensure security and governance in AI deployments. ❖ Collaboration ● Partner with product managers and engineers to translate business problems into AI solutions. ● Mentor engineers on AI/ML and GenAI best practices.Must Have Skills ❖ Core ● 10–15 years of experience in software engineering / ML systems. ● 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 & hyper parameter 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.Location Hyderabad / Bangalore (Work from office / Hybrid)