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Medium — Tier-1 brand and mid-level (3–5 yrs) amplify competition despite niche GenAI specialization.
Medium — core LLM and Python skills are transferable, but enterprise integrations and compliance increase domain specificity.
High — explicit 3–5 years plus mandatory GenAI, LLM, LangChain, vector DB, and DevOps skills.
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Develop and maintain enterprise applications using Python with FastAPI, Flask, SQL, and Generative AI technologies.
Design scalable, secure system architectures incorporating LLM integrations, RAG frameworks, vector databases, and Agentic AI solutions.
Lead code reviews, mentor developers, ensure coding standards, and collaborate with stakeholders to deliver AI-powered solutions on time within SLAs.
3 to 5 years of professional Python development experience with expertise in FastAPI, Flask, SQL, and MSSQL databases.
Hands-on experience building Generative AI applications using LLMs (OpenAI, Gemini, Anthropic), Prompt Engineering, RAG, Embeddings, LangChain, and Vector Databases.
Experience with DevOps and containerization tools including GitLab CI/CD, Kubernetes, Docker, and cloud platforms like AWS.
Work Experience Required: 3 to 5 years in relevant Python and Generative AI development roles.
Experienced in developing advanced AI applications such as conversational analytics, text-to-SQL systems, and AI-driven compliance automation, indicating strong domain expertise.
Capable of architecting secure, scalable AI systems integrating multiple advanced technologies like Agentic AI and vector databases, reflecting strategic and technical depth.
Proven leadership ability in code review and mentoring, suggesting a senior role with cross-team coordination and stakeholder collaboration.