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Mid-level AI role with in-demand skills and moderate employer brand, yielding medium competition.
Strong generative-AI, LLM, and vector-database specialization creates high background fit sensitivity.
Multiple mandatory years plus specific LLM, RAG, vector DB, cloud, and deployment requirements drive high strictness.
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Lead design, development, and maintenance of AI-powered applications including LLMs, generative AI, and Retrieval-Augmented Generation (RAG) solutions.
Architect and implement scalable, secure, and maintainable cloud-native AI software systems with APIs and microservices.
Evaluate and optimize AI models and infrastructure, driving best practices and mentoring engineering teams on complex AI initiatives.
Bachelor's degree in Computer Science, Software Engineering, or related field, or equivalent experience.
5+ years of professional software engineering experience with at least 2 years focused on AI, machine learning, or generative AI applications.
Proficiency in Python, TypeScript, Java, or C#; experience with cloud platforms like AWS, Azure, or GCP; hands-on experience with LLMs and AI platforms (e.g., OpenAI, Anthropic).
Experience implementing RAG solutions, vector databases, semantic search, RESTful APIs, microservices, and CI/CD or DevOps practices.
Experienced software engineer skilled in AI application development and integration of advanced AI technologies and frameworks such as LangChain or Semantic Kernel.
Strong operational expertise in deploying and managing AI workloads on cloud-native infrastructure with a focus on performance, security, and reliability.
Able to provide technical leadership and mentorship while collaborating effectively with product and platform teams in regulated or high-compliance environments.