AI Engineer

@ Ravian AI

About Ravian AI

Ravian AI is building device-native AI systems that can think, decide, and act on behalf of users. Our platform goes beyond web-based agents, enabling true end-to-end automation directly on devices. We work with enterprises and consumers to unlock productivity and decision intelligence at scale.

The Role

As an AI Engineer at Ravian AI, you will design and build production-grade, multi-agent AI systems and the backends that power them. You will work with FastAPI services, WebSocket event streams, orchestration logic (Autogen/LangGraph), and device execution layers to deliver autonomous, safe, and repeatable solutions.

Responsibilities

• Design & build backends with high-performance APIs and reliable WebSocket streams.
• Implement multi-agent workflows using Autogen, LangGraph or similar frameworks.
• Productionize AI with idempotent workflows, validation and performance metrics.
• Implement observability with tracing, logging, and safety guardrails.
• Optimize performance with latency reduction, cost control, and fallback designs.
• Collaborate with product, design, and customers to define SLAs and progress prototypes to production.
• Maintain high quality through crisp testing, CI/CD automation, and clear documentation.

Must-Have Qualifications

• 3–5 years in software/AI engineering in production environments.
• Strong backend skills with FastAPI (or similar), WebSockets, async Python, and cloud services.
• Experience with multi-agent systems using Autogen, LangGraph, or equivalent frameworks.
• Proven record in building and shipping AI projects/products used by real users.
• Solid understanding of LLM tooling including prompting, tool-use, and safety implementations.
• Familiarity with data models, queues, caches, relational/NoSQL databases, and containerization.

Nice-to-Have

• Experience with device control including browser automation and OS-level tasks.
• Knowledge of retrieval systems, vector stores, and evaluation frameworks.
• Experience with observability tools like OpenTelemetry, Prometheus, Grafana, or ELK stacks.
• Prior publications, open source contributions, or notable GitHub repositories.

Tech Stack

Python, FastAPI, WebSockets, Autogen, LangGraph, Celery/Queues, SQL/NoSQL, Docker, AWS (Lambda/ECS/S3), OpenTelemetry, CI/CD

How We Hire

• Intro call (30 mins): Discussion on what you’ve shipped.
• Technical deep dive (60–90 mins): System walkthrough and design reasoning.
• Practical exercise: Build or critique a multi-agent flow within 2-3 days.
• Founder discussion: Product sense, speed, and ownership conversation.
• References & offer discussions.

Application Instructions

Send an email to Lokesh@ravian.ai and Surya@ravian.ai with the subject line: "Application — AI Engineer — Your Name". Include a cover letter (1 page max) detailing a production AI system you built, your role, the scale and business impact, details of your multi-agent systems, why device-native agents excite you, your resume (PDF with GitHub/Portfolio links), top GitHub repositories, any published papers or blog posts, and your salary expectations. Also, clarify your identification as a Data Scientist or ML Engineer with production multi-agent systems experience.

Compensation

₹8–12 LPA based on experience and fit, with potential performance-based upside.

Key skills/competency

• FastAPI
• WebSockets
• Python
• Multi-agent Systems
• Autogen
• LangGraph
• Cloud (AWS/Azure/GCP)
• CI/CD
• Observability
• Production AI