Location : Role is remote, however you must be based within a City location in India
Our client who provides world’s leading Agent and Agentic solution platform designed for teams looking to streamline operational efficiency and scale productivity without needing to add headcount is currently hiring for an AI Engineer.
What You'll Do
AI / ML Engineering
- Build and deploy production-grade AI / ML features using LLM APIs (OpenAI, Anthropic, etc.) and agent orchestration frameworks
- Design, implement, and optimize RAG pipelines including embedding strategies, vector search, and retrieval patterns
- Develop multi-agent systems with tool use, memory management, and planning capabilities using frameworks like Mastra, LangChain, or LlamaIndex
- Engineer and iterate on prompts to optimize LLM performance, accuracy, and cost-efficiency
Backend Development
Build and deploy high-quality features using TypeScript (70%) and Python (30%) for AI / ML workloadsDesign and maintain relational databases (Azure SQL) and vector databases, ensuring optimal performance and data integrityDevelop and integrate clean, scalable APIs to support AI-powered features and 3rd-party servicesCollaboration & Ownership
Collaborate with product team to deliver AI / ML capabilities that solve real user problemsTake full ownership of feataures from concept to production deploymentContribute to engineering best practices and participate in code reviews with a constructive mindsetRequired :
5+ years of backend development experience in a commercial setting2+ years of production experience building and deploying LLM-based applicationsStrong understanding of RAG concepts : embeddings, vector search, retrieval strategies, and chunking approachesHands-on experience with an agent orchestration framework (Mastra, LangChain, LlamaIndex, or similar)Experience building multi-agent systems with tool use, memory, and planning capabilitiesProficiency in TypeScript (primary) and Python, ideally with knowledge of NodeJSSolid experience with relational databases and familiarity with vector databasesExperience working in cloud environments (preferably Azure, with exposure to Kubernetes, Docker, etc.)Comfortable with version control and collaboration tools like GitHubA hands-on "doer" who executes efficiently and takes pride in shipping quality codeExcellent communication skills and fluency in English