Senior genai engineer

1 day ago

Nashik, India Mitra AI Full time

Key Responsibilities: AI System Design & Development: Architect, develop, and deploy large-scale Generative AI, LLM-based systems, including intelligent agents and automation workflows. LLM Integration & Optimization: Integrate and optimize large language models for reasoning, summarization, and structured content generation. Apply prompt design, fine-tuning, and evaluation strategies to ensure reliable and domain-aware outputs. Knowledge & Retrieval Systems: Design and implement retrieval-augmented and context-aware AI pipelines, combining embeddings, semantic search, and hybrid retrieval methods. Backend Engineering: Build robust, scalable backend services and APIs using Type Script and Python, including real-time communication and data streaming capabilities. Ensure high performance, fault tolerance, and clean integration between AI components and backend systems. Data Pipelines & Processing: Develop and manage pipelines to extract, process, and transform unstructured data (code, documents, text) into AI-ready formats. Infrastructure & Deployment: Design and maintain cloud-native, containerized, and event-driven architectures with Infrastructure-as-Code (Ia C) practices. Collaborate with Dev Ops teams to implement CI/CD, observability, and environment automation. Model Evaluation & Monitoring: Establish model evaluation metrics, continuous validation workflows, and performance dashboards to ensure production reliability and drift detection. Leadership & Mentorship: Lead design discussions, perform technical reviews, and mentor AI engineers. Collaborate cross-functionally with product and platform teams to translate AI capabilities into production-grade solutions. Required Skills Strong proficiency in Python and Type Script , with a solid background in backend or API development. Proven experience in LLM-based application design , Generative AI workflows , or AI agent systems . Understanding of retrieval-augmented generation (RAG) and semantic/embedding-based search principles. Experience building scalable cloud-native services , including event-driven or asynchronous architectures. Familiarity with infrastructure automation , container orchestration , and CI/CD pipelines . Exposure to MLOps principles — model lifecycle management, evaluation, and continuous improvement. Strong problem-solving, analytical, and architectural reasoning skills. Excellent communication, collaboration, and mentoring abilities. Preferred Qualifications & Experiences: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or related disciplines . 3+ years of professional experience in AI/ML software engineering , including 2+ years in Generative AI or LLM-based systems . Previous experience leading small engineering teams or driving architectural decisions is highly preferred.

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