Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Specialized LLM skills reduce applicant pool despite popular AI title and mid-level experience.
AI/ML skills transfer well across industries, though enterprise integration favors candidates with domain experience.
Explicit 5+ years plus mandatory LLM, Python, Azure and productionization experience enforces high shortlisting strictness.
Design and build AI-native solutions and intelligent automation pipelines using Large Language Models for tasks like reasoning, document generation, and task automation.
Develop autonomous AI workflows integrating AI agents with tools, APIs, and external systems to solve complex business problems using prompt engineering and planning techniques.
Modernize legacy enterprise applications into scalable, secure, and production-ready AI applications while collaborating with product teams and stakeholders to drive AI adoption and digital transformation.
Bachelor's degree in Computer Science, Artificial Intelligence, IT, Data Science, Engineering, or related field.
5+ years of experience in AI Engineering, Software Engineering, Machine Learning, or Generative AI.
Strong hands-on experience with LLMs, prompt engineering, RAG, embeddings, vector databases, and AI agent frameworks like LangChain or Semantic Kernel.
Proficiency in Python, REST APIs, cloud platforms (preferably Azure), and integrating AI services with enterprise applications.
Experienced in designing and deploying enterprise-grade AI solutions involving LLMs and AI agents within cloud-based environments.
Skilled in modern AI technologies such as Azure OpenAI, Microsoft/GitHub Copilot, LangChain, Semantic Kernel, and vector databases.
Comfortable working in collaborative Agile teams with a focus on production-ready, scalable AI automation and responsible AI governance.