We are looking for a hands-on AI Engineer who has built and shipped real-world applications using Generative AI, Large Language Models, and Django. This role is not about experiments or notebooks; it's about owning production-grade AI systems end to end. You will work on designing, building, and scaling AI-driven features that directly impact users, integrating LLMs deeply into backend systems, workflows, and products.
Responsibilities
- Design and buildproduction-ready GenAI featuresusing LLMs (OpenAI, Anthropic, open-source models, etc. )
- Architect and implementbackend services in Djangofor AI-powered workflows.
- Develop prompting strategies, structured outputs, and guardrails for reliability.
- Build and maintainend-to-end AI systems(API logic, persistence UI integration).
- Optimise for latency, cost, and accuracy in LLM-based systems.
- Implementretrieval-augmented generation (RAG), embeddings, and vector search.
- Handleevaluation, monitoring, and iterationof AI outputs.
- Collaborate with product and frontend teams to ship usable AI features.
- Write clean, testable, and maintainable code.
Requirements
- 3+ years of professional experienceas a software or AI engineer.
- Strong hands-on experience withGenerative AI and LLMs.
- Proven experience buildingcomplete projectsusing: LLM APIs, Prompt engineering, and Structured JSON outputs.
- Strong backend experience with Python & Django.
- Experience integrating LLMs intoreal products, not just demos.
- Solid understanding of: REST APIs, Databases (Postgres preferred), Async/background processing.
- Comfortable working in fast-moving product environments.
- Experience with RAG pipelines, vector databases (Pinecone, FAISS, Weaviate, etc. )
- Experience withtool calling/function calling.
- Familiarity withLangChain / LlamaIndex(or similar frameworks).
- Experience handlingprompt versioning and evaluation.
- Frontend exposure.
- Startup or SaaS experience.
This job was posted by Hr Xtenav from XTEN-AV.
