Role
Join our AI team to architect Agentic AI systems that power autonomous drone fleets. You’ll design multi-agent frameworks where AI “does, not just suggests,” enabling drones to perceive, reason, and act independently. This role is for builders who ship code, not theories—ideal for hands-on engineers with portfolios of AI projects, regardless of formal degrees. You’ll work on:
- Multi-agent coordination: Architect frameworks where AI agents communicate, decompose tasks, and solve problems collectively.
- Decision automation: Build systems that process diverse inputs (text, sensor data, images) to trigger real-world actions.
- Scalable AI: Optimize performance for cloud deployments where latency, cost, and reliability are critical.
Key Responsibilities
Design Agentic AI Systems
- Develop frameworks for agent-to-agent communication, dynamic task assignment, and context-aware decision-making using tools like LangGraph, AutoGen, or OpenAI Swarm.
- Implement RAG pipelines and memory management to ground agents in domain-specific knowledge (e.g., technical manuals, historical logs).
Build Versatile AI Capabilities
- Work with Vision-Language Models (VLMs) to analyze aerial/sensor imagery alongside text-based reasoning for tasks like anomaly detection.
- Create agents that autonomously execute Python functions (e.g., data analysis, API calls) based on contextual triggers.
Optimize for Real-World Impact
- Deploy scalable AI workflows on AWS/GCP, balancing GPU utilization and latency for time-sensitive applications.
- Implement observability tools (e.g., LangSmith) to monitor agent behavior, debug failures, and improve system reliability.
Human-in-the-Loop Intelligence
- Design oversight mechanisms for AI agents, balancing autonomy with safety (e.g., bias testing, fallback protocols).
- Optimize agent observability with tools like LangSmith for debugging and performance monitoring.
Required Skills And Qualifications
We care about your engineering mindset, not your industry pedigree.
Proven AI Development Experience
- Portfolio of projects demonstrating multi-agent systems, RAG implementations, or decision automation (GitHub/Kaggle links required).
- Proficiency in Python and AI/ML frameworks (PyTorch, TensorFlow, Hugging Face).
Technical Breadth
- Experience with cloud platforms (AWS, GCP) and vector databases (Pinecone, Milvus).
- Familiarity with agentic frameworks (LangChain, CrewAI) and LLM orchestration.
Problem-Solver Mindset
- Ability to ship production-ready code that balances innovation with scalability.
Culture Fit
- Thrive in ambiguity, embrace failure as a learning tool, and challenge KPIs to chase goals.
What We Offer
- Build Without Boundaries: Shape your role and work on moonshot projects (no rigid job descriptions!).
- Fail Fast, Learn Faster: Experiment freely in a zero-bureaucracy environment.
- Own End-to-End Solutions: From designing agent protocols to optimizing cloud costs, you’ll see your code drive real-world outcomes.
- Collaborative Team Energy: Work in Pune with a team that whiteboards, iterates, and ships together. Daily hackathons > endless meetings.
- Growth Fuel: Access to cutting-edge tools, conferences, and a team of AI/robotics nerds.
Show us your code, not your resume.
Apply With
- A GitHub/GitLab link to your most ambitious AI project
- A 1-paragraph pitch for an agentic system that could automate a complex workflow (e.g., "An AI team that troubleshoots server outages")