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.
Read the full description and apply on the company’s own careers page.
