Principal AI Engineer

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟱𝟱𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟭𝟬𝟬𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟱𝟱-𝟭𝟬𝟬 𝗟𝗣𝗔)

Experience: 10+ yrs

Location: Bengaluru

Job Type: Full-time

We are seeking a highly experienced Senior / Principal AI Engineer to design, build, and scale enterprise-grade AI infrastructure, agentic systems, and backend platforms that power production AI applications. This role is ideal for engineers who combine deep expertise in AI, backend engineering, and cloud infrastructure with a passion for building secure, reliable, and scalable AI solutions.

As a Senior / Principal AI Engineer, you will work across AI agents, LLM-powered applications, model routing, inference services, and production infrastructure while contributing to both AI application development and backend platform engineering. You will collaborate closely with product, engineering, and platform teams to transform AI prototypes into production-ready systems with strong observability, governance, and operational excellence.

Requirements

Key Responsibilities

• Design, develop, and maintain scalable AI infrastructure supporting enterprise-grade agentic applications.
• Build intelligent AI workflows involving Retrieval-Augmented Generation (RAG), tool calling, memory, planning, and multi-agent collaboration.
• Develop backend APIs, services, and asynchronous processing systems using Python and Rust.
• Design and implement model routing, inference pipelines, AI gateways, and secure integrations with enterprise systems.
• Build reusable frameworks for agent lifecycle management, workflow orchestration, evaluation, and deployment.
• Develop scalable event-driven architectures for long-running AI and backend workloads.
• Integrate LLMs, vector databases, hosted model providers, and enterprise data sources into production environments.
• Design and optimize MLOps workflows including model deployment, versioning, monitoring, rollback, and continuous evaluation.
• Implement CI/CD pipelines, containerized deployments, Kubernetes orchestration, infrastructure automation, and cloud-native operational practices.
• Monitor production systems using logs, metrics, distributed tracing, and observability tools while continuously improving reliability, security, scalability, and cost efficiency.
• Collaborate with cross-functional engineering teams to define architecture, establish engineering standards, and mentor developers on AI platform best practices.

What Makes You a Great Fit

• 10+ years of experience in software engineering, AI platform engineering, backend development, or distributed systems.
• Strong hands-on expertise in Python and exposure to Rust for building production-grade backend and AI services.
• Proven experience designing and deploying LLM-powered applications, AI agents, or agentic workflows in production.
• Strong understanding of Retrieval-Augmented Generation (RAG), embeddings, vector databases, tool orchestration, and model inference.
• Experience building scalable backend services, REST APIs, asynchronous systems, and distributed architectures.
• Hands-on expertise with Docker, Kubernetes, CI/CD pipelines, cloud infrastructure, and modern DevOps practices.
• Experience working with PostgreSQL, Redis, messaging systems, object storage, and cloud-native infrastructure.
• Strong understanding of AI observability, model evaluation, prompt management, monitoring, and operational best practices.
• Familiarity with AI infrastructure technologies such as model gateways, inference platforms, agent orchestration frameworks, or developer tooling.
• Excellent problem-solving, architectural decision-making, communication, and technical leadership skills with the ability to independently own complex engineering initiatives from design through production.