Artificial Intelligence Engineer

About us

Arvya Tech is a service-first AI & SaaS startup delivering production-grade AI solutions for multiple clients across industries. Our work focuses on building scalable, secure, and high-performance AI-powered applications rather than research prototypes.

We are looking for a hands-on AI Engineer who can take ownership of end-to-end AI feature delivery, from design and implementation to deployment, monitoring, and optimization, while managing multiple projects in parallel.

What you’ll own

• Design, build, and operate LLM-based features using Retrieval-Augmented Generation (RAG), vector databases, and embeddings.
• Develop and maintain AI-powered SaaS applications using Python.
• Deploy, manage, and monitor production-grade AI services on Microsoft Azure.
• Implement CI/CD pipelines for AI and backend services.
• Ensure high availability, low latency, and traffic handling for concurrent users.
• Monitor applications using logging, metrics, and alerts; troubleshoot production issues.
• Optimize performance and cost using caching, batching, async processing, and efficient architecture.
• Manage multiple client projects simultaneously with strong ownership.
• Collaborate with frontend, backend, DevOps, and product teams.
• Mentor junior engineers and contribute to technical reviews and delivery planning.

Must-have qualifications

• 2–3 years of professional experience building and deploying production software.
• Strong proficiency in Python (FastAPI/Flask, async programming).
• Hands-on experience with LLMs and RAG systems (embeddings, vector stores, retrieval, prompt engineering).
• Experience deploying and managing production applications.
• Solid Azure experience (Azure App Service, Azure ML, Azure OpenAI, AKS or similar).
• Experience with Docker and basic Kubernetes concepts.
• Familiarity with CI/CD pipelines, monitoring, and incident handling.
• Experience designing systems for scale, traffic management, and performance.
• Ability to multitask and manage multiple deliverables in a service-based environment.
• Strong communication skills and experience working with clients or cross-functional teams.

Nice-to-have

• Experience with LangChain, LlamaIndex, or similar LLM orchestration tools.
• Familiarity with vector databases (FAISS, Pinecone, Weaviate, etc.).
• Exposure to SaaS multi-tenant architectures.
• Experience with Redis, PostgreSQL, MongoDB.
• Basic knowledge of MLOps practices (model versioning, monitoring, retraining workflows).

What we offer

• Competitive compensation based on experience.
• Hybrid working model.
• Opportunity to work on real-world AI systems used by paying clients.
• Ownership of projects from design to production.
• Fast growth path toward Senior AI Engineer / Tech Lead roles.
• Startup environment with high impact and learning velocity.

How to apply

Send your resume and a brief note describing a production AI or SaaS project you worked on (architecture overview or repo link encouraged).

Email: [email protected]

Subject line format: 1114 – AI Engineer