python,Java,RAG， Prompt engineering,AI/LLM
Role Overview
As an AI Application Engineer, you’ll be responsible fintegrating, fine-tuning, operationalizing large language models other AI components production-grade software systems. This role focuses on post-training workflows—such as fine-tuning, prompt engineering, retrieval-augmented generation (RAG), vectdatabase integration, model deployment—rather than foundational model development.
You’ll work closely with backend engineers, product teams, data teams to build intelligent apps that are fast, accurate, consistent production-ready.
Key Responsibilities
- Integrate LLMs other AI components web backend applications.
- Fine-tune open models using techniques like LoRA, QLoRA, supervised fine-tuning.
- Build RAG pipelines using vectdatabases.
- Design optimize prompts fvarious tasks (prompt chaining, templating, few-shot setups).
- Package deploy models finference
- Evaluate monitAI model performance in live environments.
- Ensure scalable, secure, compliant use of AI systems in production.
- Stay informed on LLM tooling ecosystems (LangChain, LlamaIndex, OpenAI APIs, Hugging Face, Spring AI etc.)
Required Qualifications
- Bachelor’s Master’s in Computer Science, Engineering, a related field.
- 2+ years of experience building AI-augmented applications services.
- Proficient in Python familiar with frameworks like LangChain, Transformers, Hugging Face datasets.
- Understanding of vectembeddings experience with vectsearch tools.
- Strong grasp of model deployment workflows (e.g., Docker, REST APIs, cloud services like AWS/Microsoft Azure).
- Familiarity with prompt engineering strategies LLM behavituning.
- Experience integrating with APIs from OpenAI, Anthropic, open-source models like Mistral LLaMA.
Preferred Qualifications
- Experience fine-tuning models using PEFT methods (LoRA/QLoRA).
- Familiarity with LLMOps, observability, model evaluation
- Exposure to security, privacy, responsible AI practices.
- Priexperience building chatbots, copilots, document analyzers, other AI apps.
- Contributions to open-source AI tools GenAI workflows.
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