LLM Developer

Job Description: LLM Engineer

Experience: 1–2 Years

Employment Type: Full-time

Location: Ahmedabad, Gujarat

About the Role

We are looking for a motivated and hands-on LLM Engineer with 1–2 years of experience in software development, AI/ML, or Generative AI. In this role, you will help design, develop, and deploy AI-powered applications using Large Language Models (LLMs).

The ideal candidate should have practical experience with LLM APIs, Python, Retrieval-Augmented Generation (RAG), prompt engineering, embeddings, and AI application development. You should enjoy experimenting with emerging AI technologies and have the ability to transform prototypes into reliable, scalable, and production-ready solutions.

Key Responsibilities

• Design, develop, and integrate LLM-powered features into existing and new applications.
• Work with LLM APIs and platforms such as OpenAI, Google Gemini, Anthropic, and open-source models.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines for knowledge-based AI applications.
• Implement embeddings, vector databases, semantic search, and document retrieval systems.
• Design, test, and refine prompts to improve response accuracy, consistency, and relevance.
• Implement function calling, structured outputs, and AI-driven workflows.
• Develop REST APIs and backend services using Python.
• Evaluate LLM outputs and troubleshoot hallucinations, retrieval issues, and inconsistent responses.
• Optimize AI applications for performance, latency, scalability, and cost efficiency.
• Collaborate with engineering and product teams to integrate AI capabilities into production systems.
• Stay up to date with the latest LLM models, frameworks, tools, and Generative AI developments.

Required Skills and Qualifications

• 1–2 years of experience in software development, AI/ML, or Generative AI.
• Strong programming skills in Python.
• Hands-on experience with at least one LLM platform, such as OpenAI, Google Gemini, Anthropic, or open-source LLMs.
• Good understanding of prompt engineering and LLM application development.
• Practical knowledge of RAG architecture and retrieval pipelines.
• Familiarity with embeddings, vector databases, and semantic search.
• Basic understanding of REST APIs and backend development.
• Working knowledge of Git and GitHub.
• Strong analytical, problem-solving, and debugging skills.
• Ability to learn new technologies quickly and work independently on small AI projects.Good to Have
• Experience with LLM frameworks such as LangChain, LlamaIndex, or LangGraph.
• Familiarity with vector databases such as Pinecone, Qdrant, Weaviate, Chroma, or pgvector.
• Experience developing APIs using FastAPI or Flask.
• Basic knowledge of databases such as PostgreSQL or MongoDB.
• Familiarity with Docker and application containerization.
• Exposure to deploying applications on AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Understanding of LLM evaluation, monitoring, and observability.
• Experience with AI agents, tool calling, and multi-step AI workflows.
• Familiarity with testing, debugging, and improving production-grade AI applications.

What We’re Looking For

We are looking for someone who:

• Has hands-on experience building LLM or Generative AI projects beyond academic coursework and tutorials.
• Can independently take a small AI feature from an initial idea to a functional prototype.
• Understands the differences between a basic chatbot and a reliable, production-ready LLM application.
• Is comfortable experimenting with different models, prompts, retrieval strategies, and AI frameworks.
• Can identify and troubleshoot hallucinations, poor retrieval quality, and inconsistent model outputs.
• Understands the importance of accuracy, reliability, latency, and cost when developing AI-powered products.
• Is curious, proactive, and eager to learn in the rapidly evolving field of Generative AI.