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Popular mid-level ML/AI developer title and 3–6 year band increases applicant competition.
LLM and prompt-engineering expertise is transferable across industries but requires specialized AI experience.
Explicit 3–6 years plus many mandatory LLM, Python, and vector DB skills tighten filtering criteria.
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Develop and maintain AI-powered applications using Python focusing on Generative AI, Prompt Engineering, and LLM integrations.
Collaborate with cross-functional teams to build scalable AI solutions enhancing business processes and customer experiences.
Handle full development lifecycle including requirement analysis, prompt design, API integration, deployment, and optimization of AI-driven applications.
3 to 6 years of professional experience in Python development.
Proficiency with Python frameworks such as FastAPI, Flask, Django, and API development.
Hands-on experience with Large Language Models (LLMs), prompt engineering, and AI platforms like OpenAI, Azure OpenAI, Anthropic Claude, or Gemini.
Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.
Experienced in building AI assistants, chatbots, conversational AI, or enterprise automation leveraging NLP, embeddings, semantic search, and RAG architectures.
Skilled in working with AI frameworks like LangChain, LlamaIndex, Hugging Face and vector databases such as Pinecone, Weaviate, Chroma, or FAISS.
Familiarity with cloud platforms (Azure, AWS, or Google Cloud), CI/CD pipelines, Docker, Git, and software development best practices.