Sr. AI Engineer

• Build responsive, modern web interfaces using Next.js and React.js, including server-side rendering, static generation, and micro front-end architecture. Translate AI-driven data and insights into intuitive user experiences and interactive dashboards.

• Design, develop, and maintain microservices using Python and Fast API for AI and ML workflows, ensuring scalability, security, and enterprise-grade reliability.

• Integrate LLM capabilities (OpenAI, Anthropic, Google) directly into full-stack features, enabling conversational interfaces, intelligent search, and AI-assisted workflows.

• Build and optimize data ingestion pipelines for structured and unstructured data sources to power AI models and analytics.

• Create secure, high-performance RESTful APIs that bridge front-end experiences with backend AI/ML services and internal LLM access layers.

• Implement Retrieval-Augmented Generation workflows and manage vector databases (Milvus) to power intelligent, context-aware applications.

• Deploy and manage full-stack services in AWS EKS Kubernetes clusters, ensuring scalability, resilience, and uptime.

• Deploy and manage full-stack services in AWS EKS Kubernetes clusters, ensuring scalability, resilience, and uptime.

• Partner closely with ML engineers, data scientists, UX designers, and business stakeholders to deliver cohesive, AI-powered product experiences.

This job might be for you if you:

• Possess a Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.

• 5+ years of relevant experience in building AI-powered UI components using Next.js/React.js such as chat interfaces, semantic search, and real-time AI output streaming.

• Advanced proficiency in Python (Fast API) for backend microservice development.

• Strong proficiency in Next.js and React.js for building dynamic, responsive front-end interfaces, including SSR, SSG, and micro front-end architectures.

• Deep understanding of RESTful API design, microservices architecture, and full-stack integration patterns.

• Experience with Kubernetes, AWS EKS, and containerized full-stack deployments.

• Hands-on experience with LLM integration (OpenAI, Anthropic, Google) and prompt engineering.

• Familiarity with vector databases (Milvus) and RAG-based architectures.

• Solid understanding of SQL and data pipeline engineering for AI workflows.

• Jenkins, Bitbucket, Atlassian suite (Jira, Confluence).

• Familiarity with image processing workflows and SQL data integration.

• Knowledge of pharmaceutical industry standards and compliance practices.

• Experience with Next.js App Router, state management libraries (Redux, Zustand), and modern front-end tooling.

  • Background in UX/design principles for enterprise AI product interfaces.