Principal Engineer

Responsibilities:

• Design and build highly scalable, secure, and resilient backend systems using Java and/or Node.js .
• Architect microservices and distributed systems capable of handling high-traffic and low-latency workloads.
• Build and integrate AI/LLM-powered features into backend applications.
• Develop RAG-based applications, AI agents, and intelligent automation workflows.
• Integrate OpenAI, Anthropic, Gemini, or other LLM APIs into enterprise products.
• Work with vector databases and embedding pipelines to build semantic search and knowledge retrieval systems.
• Collaborate with Product, AI/ML, and Engineering teams to translate business requirements into scalable technical solutions.
• Drive engineering best practices, code quality, performance optimisation, and security.
• Mentor engineers through design reviews, code reviews, and technical guidance.
• Lead architecture discussions and contribute to long-term technical strategy.

Requirements:

• 8-12 years of backend development experience.
• Strong hands-on experience with Java (Spring Boot) and/or Node.js .
• Expertise in designing REST APIs, Microservices, and Event-Driven Architecture.
• Strong understanding of Distributed Systems, System Design, Concurrency, and Scalability.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Hands-on experience with Docker, Kubernetes, and CI/CD pipelines.
• Experience with SQL and NoSQL databases (PostgreSQL, MySQL, MongoDB, Redis, etc. ).
• Strong understanding of Kafka/RabbitMQ or other messaging systems.

AI/GenAI Experience (Mandatory):

• Hands-on experience building AI-enabled products or integrating AI into production applications.
• Experience working with LLMs such as OpenAI GPT, Claude, Gemini, Llama, or similar models.
• Strong understanding of RAG (Retrieval-Augmented Generation) architecture.
• Experience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks.
• Experience with Vector Databases such as Pinecone, PGVector, Milvus, ChromaDB, Weaviate, or Qdrant.
• Experience in Prompt Engineering, Embeddings, Semantic Search, AI Agents, and AI workflow orchestration.
• Knowledge of AI evaluation, guardrails, and prompt optimisation is a plus.

Good to Have:

• Experience with Agentic AI frameworks such as CrewAI, AutoGen, ADK, or similar.
• Experience in FinTech, SaaS, or large-scale product companies.
• Exposure to ML pipelines and MLOps.
• Experience leading engineering teams or mentoring senior developers.