Principal AI/ML Architect

Principal AI-ML Architect

Role 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)