Gen AI Engineer

Role Overview

We are looking for an experienced AI/ML Engineer with strong expertise in Generative AI, Machine Learning, NLP, and Google Cloud Platform (GCP). The candidate will be responsible for designing, developing, deploying, and optimizing AI/ML solutions, including GenAI and Agentic AI applications, to solve complex business problems.

Key Responsibilities

• Design, build, deploy, and optimize ML pipelines using Google Cloud services.
• Develop and implement AI/ML models for predictive analytics, NLP, OCR, and Generative AI use cases.
• Build RAG-based and Agentic AI solutions using LangChain, LangGraph, and LlamaIndex.
• Integrate AI/ML solutions into existing applications in batch and real-time environments.
• Develop scalable data pipelines and optimize SQL, Hive, PySpark, and dataframe-based processing.
• Collaborate with cross-functional teams and maintain detailed technical documentation.
• Support model governance, monitoring, CI/CD implementation, and production deployment.

Required Skills

Programming & Core Python

• Python, OOPs Concepts, Functions & Modules
• Iterators, Generators, Decorators
• Exception Handling, Typing, Dataclasses
• Data Structures & Algorithms
• Design Patterns

Machine Learning

• NumPy, Pandas, Scikit-learn
• XGBoost, LightGBM
• TensorFlow, PyTorch
• MLflow, Matplotlib

NLP & OCR

• spaCy, NLTK, Gensim
• Transformers, Sentence Transformers
• pytesseract, EasyOCR

Generative AI & Agentic AI

• LangChain, LangGraph, LlamaIndex
• FAISS, Pinecone
• OpenAI, Anthropic, Gemini APIs
• Multi-Agent Systems and RAG Architectures

Data & Cloud

• SQL, Hive, PySpark
• Google Cloud Platform (GCP)
• GitHub, CI/CD Pipelines
• NoSQL (Good to Have)
• Big Data Technologies (Good to Have)

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Information Systems, or related field.
• Hands-on experience in building and deploying AI/ML and Generative AI solutions.
• Strong understanding of machine learning algorithms, software architecture, and model deployment.
• Excellent communication and stakeholder management skills.
• Experience with AI/ML governance in regulated industries is an added advantage.