LLM Developer

Actowiz Solutions LLP; Ahmedabad District; On-site; INR 600,000 - 1,200,000; Full time

Job summary

Actowiz Solutions LLP is seeking an LLM Engineer to design, develop, and deploy AI-powered applications. You will work with OpenAI, Google Gemini, Anthropic, and open-source models, build RAG pipelines, implement embeddings and semantic search, and craft prompts for reliable production-grade AI features. Strong Python skills and Github proficiency are essential for this hands-on role.

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.

Responsibilities

• Design, develop, and integrate LLM-powered features into applications.
• Work with LLM APIs and platforms like OpenAI, Gemini, and Anthropic.
• Build and optimize RAG pipelines for knowledge-based AI apps.
• Implement embeddings, vector databases, and semantic search.
• Design, test, and refine prompts for accuracy 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 or retrieval issues.
• Optimize performance, latency, scalability, and cost.

Skills

Python

LLM platforms

Prompt engineering

RAG

Embeddings

REST APIs

Git

Debugging

Independent work

Tools

LangChain

LlamaIndex

LangGraph

Pinecone

Qdrant

Weaviate

Chroma

pgvector

PostgreSQL

MongoDB

Docker

AWS

Azure

GCP

Job description

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.
• 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.