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Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and deploy scalable Generative AI and RAG applications including full pipeline components and integration with voice AI and conversational systems.
Build and maintain robust Python backend services, APIs, and agentic AI workflow automation, integrating with databases, enterprise systems, and customer data sources.
Take AI/ML solutions from proof-of-concept to production, focusing on scalability, reliability, latency, monitoring, and working directly with customers to troubleshoot and tailor deployments across cloud and on-premises environments.
Minimum Requirements
3+ years of experience in Software Engineering, AI/ML Engineering, Data Science, or GenAI with strong hands-on development.
Proficiency in Python backend development including FastAPI/Flask and microservices, with experience deploying AI applications using Docker.
Hands-on experience building and deploying RAG-based applications and LLM solutions including vector databases, embeddings, prompt engineering, and workflow automation frameworks like LangChain or LlamaIndex.
Experience with Voice AI technologies including ASR, TTS, telephony, plus integration with SQL/NoSQL databases and REST APIs.
Ideal Candidate Profile
Experienced in both AI/ML model integration and backend engineering delivering production-grade Generative AI and RAG solutions.
Comfortable working directly with customers to translate requirements, troubleshoot issues, and operationalize AI applications in diverse environments including cloud and on-premises.
Skilled in building scalable, maintainable backend services and agentic AI workflows leveraging state-of-the-art frameworks and tools in fast-paced, customer-facing settings.