𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟯𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟮𝟮𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟯-𝟮𝟮 𝗟𝗣𝗔)

Experience: 4+ yrs

Location: Hyderabad

Job Type: Full-time

We are looking for an experienced AI Engineer to design and develop innovative AI/ML and Generative AI Proofs of Concept (POCs) across a range of business applications. The role focuses on rapidly translating business problems into working AI-driven solutions and evaluating the feasibility, effectiveness, and scalability of emerging AI technologies.

The ideal candidate will have strong hands-on experience in Machine Learning, NLP, Generative AI, Large Language Models (LLMs), Python, RAG architectures, embeddings, and vector databases. You should be comfortable experimenting with new technologies, building prototypes quickly, and collaborating with business and technical stakeholders.

Requirements

Key Responsibilities

• Design and develop AI/ML and Generative AI Proofs of Concept (POCs) to validate new business use cases.
• Translate business problem statements into practical and scalable AI-driven solutions.
• Build LLM-powered applications using models such as GPT, Llama, Mistral, Claude, and other foundation models.
• Develop AI applications using frameworks such as LangChain, LlamaIndex, and Semantic Kernel.
• Rapidly evaluate technical feasibility across Machine Learning, NLP, Generative AI, and LLM use cases.
• Design and implement RAG architectures using embeddings, vector databases, retrieval pipelines, and prompt engineering techniques.
• Develop APIs, microservices, data pipelines, and integrations required to operationalise AI solutions.
• Conduct experiments involving model fine-tuning, embeddings, vector search, prompt optimisation, and model evaluation.
• Explore and prototype emerging AI capabilities, including transformers, agentic workflows, multimodal models, and advanced RAG techniques.
• Leverage cloud AI services across Azure, AWS, and GCP, with exposure to Azure OpenAI being an advantage.
• Apply lightweight MLOps practices covering model and code versioning, evaluation, monitoring, and experimentation.
• Analyse POC results and assess solution performance, feasibility, scalability, and potential business value.
• Present POC outcomes, technical findings, insights, and recommendations to business and senior leadership.
• Collaborate with data scientists, software engineers, product teams, and business stakeholders throughout the development lifecycle.
• Stay current with the latest developments in Generative AI, LLMs, AI agents, NLP, and machine learning technologies.

What Makes You a Great Fit

• 4+ years of experience in AI Engineering, Machine Learning, Data Science, NLP, or a closely related field.
• Strong hands-on expertise in Machine Learning, NLP, and Generative AI.
• Proven experience building AI/ML prototypes and rapid Proofs of Concept.
• Strong practical experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, or equivalent models.
• Proficiency with LangChain, LlamaIndex, Semantic Kernel, or similar LLM application frameworks.
• Strong programming skills in Python and experience developing APIs and AI-enabled services.
• Solid understanding of embeddings, vector databases, semantic search, prompt engineering, and RAG architectures.
• Experience with cloud platforms such as Azure, AWS, or GCP; Azure OpenAI experience is preferred.
• Understanding of LLM evaluation, fine-tuning, retrieval optimisation, and model experimentation.
• Exposure to agentic AI, transformers, multimodal AI, and emerging Generative AI architectures.
• Familiarity with API development, microservices, data pipelines, and software engineering practices.
• Understanding of lightweight MLOps, model versioning, monitoring, and evaluation.
• Strong analytical and problem-solving abilities with a practical, experimentation-driven mindset.
• Excellent communication skills and the ability to explain complex AI concepts to technical and non-technical stakeholders.
• Ability to work effectively in Agile, collaborative, and fast-paced environments.
• Curiosity and enthusiasm for experimenting with emerging AI technologies and turning new ideas into working solutions.