| Must-Have** | - The AI Engineer will be responsible for designing and developing innovative Proof of Concepts (POCs) using advanced AI/ML and Generative AI technologies across various business applications. The role involves working closely with business stakeholders and cross-functional teams to translate problem statements into scalable AI-driven solutions. The candidate is expected to have strong hands-on experience in machine learning, LLMs, and rapid prototyping, along with the ability to evaluate feasibility and deliver working prototypes.
- • Strong hands-on experience in Machine Learning, NLP, and Generative AI
• Experience working with LLMs (GPT, Llama, Mistral, Claude, etc.)
• Proficiency in frameworks such as LangChain, LlamaIndex, or Semantic Kernel
• Experience in building AI/ML prototypes and rapid experimentation
• Strong programming skills in Python and API development
• Understanding of embeddings, vector databases, and RAG architectures
• Knowledge of cloud platforms (Azure/AWS/GCP), preferably Azure OpenAI
• Strong analytical, problem-solving, and communication skills
• Ability to work in Agile and collaborative environments
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Key responsibilities: | - • Design and develop AI/ML Proof of Concepts (POCs) to validate new business use cases
• Build and deploy LLM-based applications using modern frameworks and custom pipelines
• Rapidly evaluate feasibility across ML, NLP, and Generative AI domains
• Develop APIs, microservices, and pipelines to integrate AI solutions
• Conduct experiments on model fine-tuning, embeddings, and vector search optimization
• Stay updated with the latest advancements in AI (transformers, RAG, agentic workflows, multimodal models)
• Collaborate with business stakeholders to convert requirements into technical solutions
• Present POC outcomes, insights, and recommendations to leadership
• Apply lightweight MLOps practices such as versioning, monitoring, and evaluation
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