AI Engineering Lead

Sage It; Hyderabad, Chennai District, Bengaluru; Presencial; INR 4 000 000 - 7 000 000; Tempo integral

Resumo da oferta

Sage It seeks a hands-on AI Engineering Lead to architect, build, and scale production-grade AI systems with a focus on Agentic AI, Cloud & MLOps. You will lead end-to-end AI applications, not just model development, across Hyderabad, Bengaluru, and Chennai.

You will design LLM-based agents, RAG pipelines, and orchestration frameworks, deploy via CI/CD, Docker/Kubernetes, and ensure observability and reliability in cloud environments.

Qualificações

• 8–12+ years of hands-on experience in AI/ML systems.
• Proven track record delivering AI-powered applications.
• Strong Python expertise.

Responsabilidades

• Architect end-to-end AI/Agentic AI solutions.
• Design and build LLM-based agents and orchestration frameworks.
• Develop RAG pipelines, LLM integrations, tool-calling, memory, and reasoning workflows.
• Build scalable AI-powered applications and reusable AI frameworks.
• Define and implement MLOps / LLMOps best practices.
• Manage the complete AI lifecycle from development to production.

Conhecimentos

AI/ML systems

Agentic AI

Python

LLMs

Multi-agent systems

Cloud platforms (AWS/Azure/GCP)

MLOps / LLMOps

Docker

Kubernetes

CI/CD

Distributed systems

Ferramentas

LangChain

LangGraph

Vector databases

PyTorch

TensorFlow

APIs

Microservices

Descrição da oferta de emprego

Hiring: AI Engineering Lead - Agentic AI, Cloud & MLOps (Hands on)

Location: Hyderabad/ Bangalore / Chennai

We are looking for a hands-on AI Engineering Lead to architect, build, deploy, and scale production-grade AI systems with a strong focus on Agentic AI, Cloud, MLOps, and modern application engineering.

We are looking for builders who can design, build, and ship AI-powered applications end-to-endnot just model developers.

Key Responsibilities

• Architect and deliver end-to-end AI and Agentic AI solutions.
• Design and build LLM-based agents, multi-agent systems, and orchestration frameworks.
• Develop RAG pipelines, LLM integrations, tool-calling, memory, and reasoning workflows.
• Build scalable AI-powered applications and reusable AI frameworks.
• Define and implement MLOps / LLMOps best practices.
• Manage the complete AI lifecycle from development to staging and production.
• Own deployment, scalability, reliability, monitoring, and performance.
• Build CI/CD pipelines for AI/ML systems.
• Deploy production solutions using Docker, Kubernetes, APIs, and microservices.
• Design scalable, distributed, API-driven, and event-driven architectures.
• Challenge technical assumptions, identify risks, and improve solution designs.
• Mentor engineers and drive technical excellence.

Required Experience & Skills

• 8- 12+ years of experience across application engineering and AI/ML systems.
• Proven experience building and delivering AI-powered applications.
• Strong hands-on experience with Agentic AI, AI Agents, RAG, and LLMs.
• Experience with multi-agent systems and orchestration frameworks.
• Strong hands-on Python experience.
• Experience with AI/ML frameworks such as PyTorch, TensorFlow, or equivalent.
• Production experience with at least one cloud platform:
  • AWS
  • Azure
  • GCP
• Strong experience with MLOps / LLMOps.
• Experience with model/prompt versioning, evaluation, monitoring, and observability.
• Strong CI/CD experience.
• Hands-on experience with Docker, Kubernetes, APIs, and Microservices.
• Strong understanding of distributed systems, system design, and event-driven architecture.

Preferred Skills

• LangChain / LangGraph or equivalent agent orchestration frameworks.
• Vector databases.
• Large-scale data systems.
• AI security and Responsible AI.
• Client-facing or IT consulting experience.