Artificial Intelligence Engineer

Company Overview :

Pinnacle FutureBuild values inclusive growth in an agile, diverse environment. With 30+ years of global experience, 3,400+ experts completed 15,000+ projects across 43+ countries for 5,000+ clients. Join us for rapid advancement, cutting-edge training, and impactful global projects. Embrace E.A.R.T.H. values, celebrate uniqueness, and drive swift career growth with Pinnaclites!

Position : AI Engineer

Location : India / Hybrid

Employment Type : Full-Time

Experience : 4- 8 Years

About the Role :

We are seeking a talented and innovative AI Engineer to design, develop, and deploy Artificial Intelligence and Machine Learning solutions that solve complex business problems. The ideal candidate will have strong expertise in Machine Learning, Generative AI, Large Language Models (LLMs), and data-driven application development. As an AI Engineer, you will collaborate with cross-functional teams to build intelligent systems, optimize AI models, and integrate AI capabilities into enterprise applications.

Key Responsibilities :

• Design, develop, and deploy AI/ML models for business and operational use cases.

• Build and optimize Generative AI solutions using Large Language Models (LLMs).

• Develop Retrieval-Augmented Generation (RAG) pipelines and AI-powered applications.

• Fine-tune and evaluate machine learning and deep learning models.

• Create data preprocessing, feature engineering, and model training workflows.

• Integrate AI models with web applications, APIs, and enterprise systems.

• Implement model monitoring, performance tracking, and continuous improvement processes.

• Collaborate with Data Engineers, Software Engineers, and Business Stakeholders to deliver AI solutions.

• Conduct experiments, evaluate model performance, and document findings.

• Stay updated with emerging AI technologies, frameworks, and industry best practices.

Required Skills & Qualifications :1. Technical Skills :

• Strong proficiency in Python.

• Experience with Machine Learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.

• Hands-on experience with Large Language Models (GPT, Claude, Llama, Mistral, etc.).

• Experience in Prompt Engineering and RAG architectures.

• Knowledge of Vector Databases such as Pinecone, ChromaDB, Weaviate, or FAISS.