AI Engineer

Full-time, on-site role for an AI Engineer (LLM & Application Development), based in Bengaluru, Mumbai, NCR or Hyderabad.

Experience Level: 4–8 Years

Role Overview

We are looking for a skilled AI Engineer with a strong foundation in software engineering and production-grade application development. In this role, you will bridge the gap between cutting-edge AI research and practical, scalable software. You will be responsible for designing, building, and deploying AI-powered applications, with a heavy focus on Large Language Models (LLMs), prompt engineering, and robust Python backends.

If you have 4–8 years of experience turning complex AI concepts into reliable, user-facing applications, we want to hear from you.

Key Responsibilities

• AI & LLM Integration: Design, build, and optimize applications leveraging LLMs (OpenAI, Anthropic, open-source models). Implement advanced techniques like RAG (Retrieval-Augmented Generation), agentic workflows, and fine-tuning.

• Backend Application Development: Write clean, maintainable, and scalable Python code to build robust APIs and backend services that support AI features.

• Software Engineering Excellence: Apply rigorous software engineering practices, including CI/CD pipelines, automated testing, version control (Git), and containerization (Docker/Kubernetes).

• Architecture & Scalability: Optimize AI pipelines for latency, cost, and throughput. Ensure seamless data flow between vector databases (e.g., Pinecone, Chroma, Milvus) and core application logic.

• Collaboration: Partner with product managers, data scientists, and front-end engineers to take AI features from prototype to production.

Required Skills & Qualifications

• Experience: 4–8 years of professional software engineering experience, with at least 2 years dedicated to building and deploying AI/LLM-powered applications.

• Core Language: Mastery of Python and its ecosystem (FastAPI, Flask, or Django).

• LLM Tooling: Deep hands-on experience with frameworks like LangChain, LlamaIndex, or AutoGen, and familiarity with vector databases.

• Software Engineering: Strong understanding of data structures, system design, RESTful APIs, and microservices architecture.

• Cloud & DevOps: Experience deploying applications on cloud platforms (AWS, GCP, or Azure) and managing MLOps/LLMOps pipelines.

• Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).

Nice-to-Haves

• Experience with frontend technologies (React, TypeScript) for rapid prototyping.

• Evaluation framework experience (e.g., Ragas, TruLens) to monitor and benchmark LLM outputs.

• Contributions to open-source AI or software projects.