Lead AI Engineer

Overview

Lead AI Engineer to design, build, and deploy enterprise-grade AI/GenAI applications—automating business processes and improving decision-making.

What you'll do

• Design, develop, and deploy AI/GenAI applications, RAG pipelines, and intelligent workflow automation.
• Build backend services, APIs, integrations, and orchestration frameworks using LLMs and model APIs.
• Develop knowledge assistants, workflow automation, and decision support solutions.
• Ensure code quality, security, reliability, observability, and governance.
• Define evaluation frameworks to measure AI quality, accuracy, latency, and system performance.
• Collaborate with business and functional teams to deliver high-value AI use cases.
• Prototype and scale solutions into secure, production-ready deployments.

What you'll need

• 7–12+ years of experience in software engineering, AI/ML, or GenAI application development.
• Proven experience building and deploying production-grade AI/GenAI solutions.
• Strong expertise in Python, backend development, APIs, system integration, and workflow orchestration.
• Hands-on experience with RAG, LLMs, prompt engineering, tool/agent calling, AI evaluation, and observability.
• Experience integrating enterprise applications, data platforms, and services using APIs and event-driven architectures.
• Analytical and systems thinking skills to translate ambiguous business problems into scalable AI solutions.
• BE/B.Tech/MCA, preferably in Computer Science, Information Technology, or a related field.

Nice to have

• Experience with vector databases, embeddings, semantic search, and advanced RAG architectures.
• Knowledge of SQL, data engineering, and data pipelines.
• Exposure to intelligent agents, automation platforms, and AI governance frameworks.
• Experience building reusable AI frameworks, accelerators, or enterprise AI platforms.