Lead AI Engineer

Overview

Lead the design, development, and deployment of enterprise AI/GenAI solutions, including workflow automation, integrations, and knowledge assistants.

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 AI-powered knowledge assistants, decision support, and workflow automation solutions.
• Ensure code quality, security, reliability, observability, and governance in AI-assisted development.
• Define AI evaluation frameworks to measure quality, accuracy, latency, and system performance.
• Collaborate with business and IT/security/data/HR/finance teams to deliver high-value AI use cases.
• Prototype quickly 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 and data platforms using APIs and event-driven architectures.
• Strong analytical and problem-solving skills to translate ambiguous business problems into scalable AI solutions.

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.