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 .
- Robust 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

📌 Principal AI-ML Engineer (Hyderabad)
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