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.

  • Masters Degree in related field

  • 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.

  • Benefits Package, with time off and Holiday pay

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.

Summary

Build and deploy production-grade AI-powered backend systems, integrating LLMs, traditional ML models, and vector databases for RAG. Requires 3+ years of Python backend engineering experience, a Master's degree in a related field, and proven production deployment experience.

Responsibilities

Design, develop, and deploy production-grade AI-powered backend systems; integrate LLMs and ML models; optimize vector databases for RAG; write clean testable Python code; debug cross-layer issues; collaborate with product, backend, and frontend engineers

Qualifications

3-5+ years professional backend engineering experience in Python, FastAPI or Flask, and background processing; Master's degree in related field; proven record deploying Python applications to production

Education requirements

Master's degree in related field

Experience requirements

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

Benefits

Benefits Package with time off and Holiday pay