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Strong brand, metro location, mid-level generalist AI role increases applicant competition.
Generative AI engineering skills transfer across industries despite advisory context.
Explicit 5+ years and multiple mandatory GenAI, cloud, and engineering skills increase filtering strictness.
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Design, develop, and deploy AI-powered applications and production-ready solutions using LLMs, RAG architectures, AI agents, and multi-agent systems.
Build backend services, APIs, integrations, and user interfaces for AI solutions and optimize them for quality, performance, scalability, and cost efficiency.
Collaborate with architects, engineers, and business stakeholders to deliver scalable AI solutions and contribute to reusable frameworks and engineering best practices.
Work Experience Required: 5+ years in relevant AI software engineering roles.
Mandatory skills include expertise in Generative AI (LLMs, prompt engineering, RAG architectures, embeddings, vector databases), hands-on experience with GenAI frameworks (e.g., LangChain, LangGraph), and proficiency with leading AI platforms (e.g., Azure OpenAI, Google Vertex AI).
Strong proficiency in Python and API development frameworks such as FastAPI or Flask; experience with frontend technologies like React, Next.js, or Streamlit.
Education Qualification: Master of Business Administration (MBA) explicitly required.
Experienced in full-stack AI application development incorporating cloud-native and containerized environments (Azure, AWS, GCP, Docker).
Technical operator comfortable integrating AI services with enterprise systems and implementing AI governance and evaluation best practices.
Able to deliver scalable, optimized AI solutions through cross-functional collaboration with architects, engineers, and business teams in a consulting context.