Sr. AI Engineer

About Us

We’re a fast-growing product company integrating cutting-edge AI capabilities into our core offering to stay competitive and deliver exceptional value to customers. Our AI work spans task-specific ML models, large language model (LLM) integration, and agentic systems that orchestrate multiple tools to produce end-user results.

We run a Python-based backend (FastAPI + Gunicorn + Nginx) with heavy background job processing using Celery. We’re looking for a senior-level AI Engineer who is equally strong in backend engineering and applied AI — capable of building production-grade systems that are fast, reliable, and maintainable.
What You’ll Do

- Design, develop, and deploy production-grade AI-powered backend systems.

- Integrate LLMs and traditional ML models into performant, scalable architectures.

- Integrate and optimize vector databases for retrieval-augmented generation (RAG) pipelines and other traditional ML queries.

- Write clean, well-structured, and testable Python code following best practices.

- Capable of thinking about performance and ensuring optimal decision making to reduce latency.

- Build hybrid architectures that balance LLM calls with traditional ML.

- Debug complex, cross-layer issues spanning backend, AI inference, and UI integration.

- Conduct thorough dev testing before QA handoff to ensure production reliability.

- Collaborate with product, backend, and frontend engineers to deliver cohesive solutions.

Must-Have Skills & Experience

- 3–5+ years professional backend engineering experience in Python, FastAPI or Flask, and background processing.

- Proven record of deploying Python applications to production (not just scripts or academic work).

- Strong grasp of software design patterns

- Strong understanding of backend performance, parallel processing in background jobs and multi-threading

- Proficiency in performance tuning specially for heavy AI models

- Applied machine learning experience — training, evaluating, and maintaining small task-specific models.

- Familiarity with LLM integration, prompt engineering, and context window optimization.

- Proven ability to debug AI behavior, identify root causes, and make targeted fixes.

- Strong testing discipline for both backend and AI components.

- Experience with background processing with Celery or other major libraries

- Experience with monitoring APIs and background processing

- Experience with ensuring visibility and error reporting.

- Nice to have: experience with Docker, understanding of CI/D, deployment automation and Kubernetes

Who Will Succeed in This Role

- Independent problem solver — you can debug without constant supervision.

- Production mindset — you understand that reliability, scalability, and maintainability matter as much as accuracy.

- System thinker — you see backend, AI, and UI as a connected whole.

Why Join Us

- Direct impact on the company’s competitive edge.

- Small, fast-moving team with high autonomy.

- Work on practical, real-world AI applications — not just research.

- Opportunity to shape our AI architecture and best practices from the ground up.

If you’re a backend-first AI engineer who thrives in shipping production-ready systems and knows how to make AI practical, fast, and reliable — we’d love to talk.

Originally posted on Himalayas