Senior GenAI Engineer

18 hours ago

Thrissur, 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 TypeScript 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 (IaC) practices. - Collaborate with DevOps 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 TypeScript, 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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