Manage database migrations across development, staging, and production environments.
Build and maintain data sync processes between the data warehouse and production databases.
Implement asynchronous and background job processing using message queues such as RabbitMQ or Redis.
Administer and optimize PostgreSQL and MySQL databases, covering schema design, indexing, and query tuning.
AI & Intelligent Applications
Build Retrieval-Augmented Generation (RAG) based AI agents for enterprise knowledge and policy search.
Develop Model Context Protocol (MCP) based tools and integrations that give AI assistants access to production data and insights.
Quality, Security & Reliability
Write clean, modular, reusable, and well-tested code following best practices.
Monitor, debug, and resolve complex issues across backend services, data pipelines, and AI systems.
Ensure compliance with security best practices, data privacy requirements, and secure coding standards.
Optimize system performance, reliability, and scalability.
Collaboration
Work with product managers, developers, pipeline/TD teams, DevOps, and business stakeholders.
Document architecture, data flows, and technical decisions.
REQUIRED SKILLS
5+ years of experience in backend development, including at least 1–2 years in a lead or senior role.
Strong proficiency in Node.js and TypeScript with hands-on experience in NestJS.
Solid experience in data modeling, API design, and relational databases (PostgreSQL, MySQL).
Experience with Change Data Capture, ETL/ELT pipelines, and data synchronization between systems.
Working knowledge of data warehousing concepts and syncing data between OLTP and analytical systems.
Familiarity with AI agent development and tool-calling, including Model Context Protocol (MCP).
Experience integrating with third-party APIs, including Google Workspace APIs (Sheets, Drive).
Working knowledge of RabbitMQ and Redis for messaging and job queues, and of event-driven, message-based architectures.
Proficiency with Git and version control workflows.
Strong problem-solving, communication, and mentoring skills.
PREFERED SKILLS
Hands-on experience building LLM-powered applications: RAG pipelines, embeddings, vector databases (e.g., pgvector, Pinecone, Qdrant, Weaviate), and frameworks like LangChain or LlamaIndex.
Frontend development experience (React or similar) for building internal tools and applications.
Experience with streaming/CDC tools such as Debezium or Kafka.
Familiarity with Docker, CI/CD pipelines, and Linux/shell scripting.
Understanding of microservices architecture.
Experience with monitoring and logging tools (Prometheus, Grafana, ELK Stack).
Familiarity with cloud platforms (AWS, GCP, or Azure).
Experience with testing frameworks such as Jest.
Exposure to VFX, animation, or media production pipelines is a strong plus.
Willingness to learn and switch between technologies as needed and to swap between multiple projects simultaneously.
