Senior AI Engineer

• Architect, design, and develop production-grade LLM applications including copilots, chatbots, and autonomous AI agents.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines using structured and unstructured enterprise data sources.
• Develop agentic workflows with tool calling, function execution, and multi-step reasoning capabilities.
• Design and maintain backend services and APIs supporting AI inference, orchestration, and system integration.
• Implement LLMOps/GenAIOps practices including evaluation frameworks, monitoring systems, CI/CD pipelines, and model/version management.
• Optimize AI systems for performance, ensuring the right balance of latency, cost efficiency, scalability, and reliability.
• Apply Responsible AI principles and security-by-design practices across all AI system implementations.
• Collaborate with cross-functional teams including product, engineering, and security to shape AI architecture and strategy.
• Mentor engineering peers and contribute to establishing best practices in generative AI system design.

Requirements:

• 10+ years of professional software engineering experience with strong backend development expertise.
• Advanced proficiency in Python, with experience in frameworks such as FastAPI, Django, and modern backend systems.
• Hands-on expertise in LLM engineering, including prompt engineering, RAG architectures, and APIs such as OpenAI or Amazon Bedrock.
• Strong experience with Elasticsearch, including vector search, hybrid search (BM25 + embeddings), and semantic retrieval techniques.
• Proficiency with vector databases such as Pinecone, Qdrant, or ChromaDB and embedding-based retrieval systems.
• Proven experience building production-grade generative AI systems, including Copilot-style or agent-based applications.
• Strong understanding of distributed systems, microservices, event-driven architecture, and scalable backend design.
• Experience with cloud platforms (AWS/GCP), containerization (Docker, Kubernetes), and CI/CD pipelines.
• Familiarity with LLMOps and MLOps practices in production environments.
• Strong communication skills and ability to collaborate with technical and non-technical stakeholders.
• Experience operating AI systems at scale and exposure to enterprise-grade reliability requirements is highly desirable.

Benefits:

• Opportunity to work on cutting-edge generative AI systems deployed at enterprise scale.
• Remote-first flexibility within India-based work arrangements.
• Exposure to advanced AI architecture, LLMOps practices, and modern distributed systems.
• High-impact role with ownership over end-to-end AI system design and delivery.
• Collaborative environment working with cross-functional AI, product, and platform teams.
• Career growth in a fast-evolving AI engineering landscape with strong technical challenges.
• Inclusive and innovation-driven culture focused on continuous learning and experimentation.