AI Engineer

Role Overview We are seeking a highly skilled developer with 3-5 years of deep, hands-on experience in Artificial Intelligence and Machine Learning to design and build advanced assets for our Agentic AI solutions. The ideal candidate will demonstrate exceptional knowledge in AI/ML algorithms and frameworks, a serious track record in deploying models at scale, and strong expertise working with Large Language Models (LLMs).

Key Responsibilities

• Design, implement, and optimize complex AI/ML assets and models for agentic AI solutions.
  
• Lead research and prototyping efforts in ML and AI algorithm development, with a focus on advancing the core intelligence of agentic AI systems.
  
• Develop, fine-tune, and experiment with Gen AI LLMs, working with state-of-the-art architectures and leveraging the latest research in natural language processing and generative AI.
  
• Apply advanced techniques such as transfer learning, reinforcement learning, and retrieval-augmented generation (RAG).
  
• Collaborate closely with product, engineering, and research teams to benchmark performance, drive technical innovation, and set the direction for AI/ML initiatives.
  
• Understand requirements on domain specific use cases and implement AI/ML solutions
  

Required Skills & Qualifications

• 3-5 years strong professional experience as an AI/ML engineer, data scientist, or research scientist.
  
• Strong knowledge on Agent to Agent communication and development of Agentic AI frameworks
  
• Experience with vector search/vector databases, knowledge graphs, and data pipelines for RAG-based systems.
  
• Expert-level Python programming skills and fluency in libraries and toolkits such as NumPy, Pandas, scikit-learn, PyTorch, TensorFlow, Hugging Face, etc.
  
• In-depth knowledge of classical and advanced machine learning algorithms, deep learning, neural network architectures, and their real-world applications.
  
• Demonstrable experience building and fine-tuning LLMs (such as GPT, Llama, Mistral, etc.) and integrating them into robust solutions.
  
• Strong background in state-of-the-art ML methodologies: prompt engineering, embeddings, transformers, self-supervised and unsupervised learning, RLHF, etc.
  
• Experience with production-level deployment of AI/ML models, cloud-based ML infrastructure (AWS/GCP/Azure/IBM Cloud), containerization (Docker), and scalable MLOps practices.
  
• Developing Solutions Aligned with AI Governance and Ethical AI Standards
  

Nice to Have

• Familiarity with agentic AI frameworks or multi-agent systems.
  
• Publications, patents, or open-source contributions in AI/ML.
  
• Strong analytical and communication skills.
  
• UIUX Knowledge and framework
  
• RDBMS and NoSQL database knowledge
  
• Knowledge on AIML model finetune
  

Mandatory skills

Python
Machine Learning (ML) Deep Learning (DL) Natural Language Processing (NLP) Generative AIAgentic AI

multi Agent frame works

Crew AI Approaches

Generative AI