Principal AI-ML Engineer

Principal AI-ML Engineer

Role Overview

We are looking for an AI/ML Architect with strong hands-on experience in Python-based ML systems and Generative AI solutions. This role focuses on designing and deploying production-grade AI systems, with a strong emphasis on LLMs, RAG pipelines, and MLOps practices.

The ideal candidate will have 1415 years of overall experience, including at least 10 years of relevant experience in AI/ML and Generative AI.

You will work closely with engineering and product teams to build scalable, secure, and high-performance 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

• 1015 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 & 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, Bengaluru (exception: remote if the candidate is extremely good).Some travel will be needed in this position