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Niche GenAI skills (LLMs, RAG, LangChain) reduce applicant density despite mid-level experience.
High; role depends on specialized GenAI expertise, limiting cross-industry transferability.
Explicit years plus mandatory GenAI stack and engineering experience enforce strict shortlisting.
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Design, develop, and deploy Generative AI applications leveraging LLMs, RAG, and orchestration frameworks.
Build reusable prompt-based solutions, AI workflows, and integrate vector databases for enterprise knowledge retrieval.
Develop scalable APIs and microservices to expose AI capabilities, ensuring performance and reliability.
Bachelor's degree in Computer Science, Data Science, AI, Engineering, or related field.
3–6 years software development experience with 1–2 years in Generative AI solutions.
Proficiency in Python, experience with LangChain or similar orchestration frameworks, and building APIs/microservices.
Hands-on experience with LLMs, prompt engineering, embeddings, vector databases, and RAG architectures.
Experienced in end-to-end AI application lifecycle from prototyping to production deployment with scalable solutions.
Skilled at translating business requirements into reusable AI components and integrating AI workflows into enterprise environments.
Familiar with AI testing strategies, synthetic data, and maintaining AI solution quality, reliability, and performance.