Role Overview

As a Mid-Level AI Engineer focused on Large Language Model (LLM) development, you will play a critical role in building, optimizing, and scaling intelligent AI systems that leverage the latest in LLM research and orchestration frameworks. You will collaborate with cross-functional teams to create production-ready AI tools and interfaces that power modern enterprise use cases.

Key Responsibilities

Develop and optimize LLM-based applications using orchestration frameworks like LangChain, CrewAI, or similar.
Implement context management protocols to improve model memory retention, token handling, and performance efficiency.
Design and deploy interactive interfaces for LLM applications using tools like OpenWebUI.
Prepare and manage structured datasets for model training, fine-tuning, and inference workflows.
Integrate vector databases (e.g., FAISS, Pinecone) and implement retrieval-augmented generation (RAG) pipelines.
Collaborate with AI engineers, data scientists, and product teams to refine prompt engineering and multi-agent workflows.
Stay updated with advancements in LLM architectures, AI tooling, and open-source ecosystems.
Contribute to the development of scalable, secure, and ethical AI systems aligned with enterprise standards.

Must-Have Skills & Qualifications

4–6 years of experience in AI/ML engineering, preferably with a strong focus on Natural Language Processing (NLP) or LLMs.
Proficiency in Python, with hands-on experience in LangChain, CrewAI, and Hugging Face Transformers.
Practical knowledge of OpenWebUI or similar tools for deploying LLM interfaces.
Deep understanding of token limits, context length, memory optimization, and embedding techniques.
Experience in data preparation – cleaning, labeling, structuring, and formatting for training or inference.
Familiarity with vector databases (e.g., FAISS, Pinecone) and embedding models.
Ability to collaborate in agile teams and adapt to fast-paced development environments.

Find Your Dream Job

Filters

Latest Job Opportunities