Design, build, and deploy sophisticated agentic AI systems. Collaborate with cross-functional teams and champion best practices in Python. Oversee the full AI lifecycle from prompt engineering to deployment.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
Title: Senior AI Engineer - Agentic AI (Remote - PAN India)
Location: Remote, India
🚀 Ready to build the future of autonomous AI?
We are seeking an elite Senior AI Engineer with deep experience in agentic AI to join our 100% remote, innovation-driven team.
This is a high-impact role for a true specialist. You won't just be working with AI; you'll be architecting the very systems that allow it to operate autonomously. If you are an expert in Python and have hands-on experience with frameworks like LangGraph, we want to hear from you.
As a key member of our team, you will be the driving force behind designing, building, and deploying sophisticated, multi-agent systems that solve complex, real-world challenges.
What You'll Be Doing:
- Architecting and building complex, scalable agentic AI systems from the ground up.
- Engineering and maintaining robust, intelligent workflows using LangGraph and related tools.
- Collaborating with cross-functional teams to integrate these autonomous agents into our core applications.
- Championing best practices by writing clean, efficient, and highly testable Python code.
- Overseeing the full AI lifecycle, from advanced prompt engineering and agent design to deployment and continuous monitoring.
What We're Looking For (Required):
- 7+ years of relevant professional experience.
- Expert-level proficiency in Python and its AI/data ecosystem.
- Proven, hands-on experience designing and building agentic AI architectures and autonomous agents.
- Direct, practical experience with LangGraph or similar orchestration frameworks (e.g., AutoGen, CrewAI).
- Deep understanding of LLMs and the principles of multi-agent systems.
- Excellent problem-solving skills and the discipline to thrive in a fully remote (PAN India) environment.
⭐ How to Stand Out (Bonus Points):
- You have practical experience with traditional ML or deep learning (training/fine-tuning models).
- You have experience with ML-Ops and deploying models at scale (AWS, GCP, Azure).
- You are an active contributor to open-source AI projects.
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