About the Role

Alpha Intellisense is looking for talented AI Engineers to join our AI & Data Intelligence team. We are seeking engineers who can build practical, production-ready AI solutions—not just experiment with models. You will work on AI products and client solutions involving Generative AI, Large Language Models (LLMs), AI agents, machine learning, NLP, intelligent automation, RAG systems, computer vision, and API-based AI integrations. As an AI Engineer, you will be involved across the development lifecycle: understanding business requirements, designing AI architectures, selecting appropriate models and technologies, developing and testing solutions, integrating AI into web and enterprise applications, and deploying reliable systems to production. You may work on projects including AI-powered SaaS platforms, intelligent business automation, conversational AI, customer-support agents, knowledge-base assistants, recommendation systems, document processing, predictive solutions, and custom AI applications for international clients. We are particularly interested in candidates who understand how to turn AI capabilities into real-world business solutions that are reliable, scalable, secure, and commercially useful.

What We're Looking For

Strong proficiency in Python and experience developing production-level applications.

Practical experience with Generative AI and Large Language Models (LLMs).

Experience working with LLM APIs such as OpenAI, Anthropic, Gemini, or similar platforms.

Experience building AI agents, RAG pipelines, embeddings, vector search, and knowledge-based AI systems.

Understanding of machine learning, deep learning, NLP, and model evaluation fundamentals.

Experience with frameworks/tools such as PyTorch, TensorFlow, Hugging Face, LangChain, LangGraph, or LlamaIndex is preferred.

Experience integrating AI solutions with REST APIs, databases, web applications, and third-party platforms.

Understanding of prompt engineering, structured outputs, tool/function calling, context management, and LLM evaluation.

Experience with vector databases such as Pinecone, Weaviate, Qdrant, Chroma, pgvector, or equivalent technologies.

Familiarity with Git, Docker, cloud deployment, CI/CD, and production AI environments.

Ability to design AI systems with consideration for accuracy, latency, scalability, security, hallucination reduction, and cost optimization.

Strong analytical, problem-solving, debugging, and communication skills.

Ability to independently research emerging AI technologies and rapidly prototype solutions.

Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related discipline preferred.

Strong portfolio, GitHub projects, deployed AI applications, or demonstrable commercial AI experience will be highly valued.

AI Engineer – Generative AI, LLMs & Machine Learning

About the Role

What We're Looking For

Ready to Apply?