Gen-AI Engineer

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About the Role

Responsibilities

• Assist in designing, developing, and deploying end-to-end, production-grade LLM-powered applications along with the team members.
• Help build and maintain stateful, multi-step AI applications and agentic workflows using modern frameworks such as LangChain and LangGraph.
• Contribute to the implementation of Retrieval-Augmented Generation (RAG) pipelines to ground LLMs in external data.
• Participate in the lifecycle of data ingestion, chunking, embedding, and indexing for vector databases to support robust RAG systems.
• Help evaluate and optimize the performance and output quality of LLM applications, focusing on metrics like relevance, factuality, and safety.
• Collaborate with cross functional teams and other engineers to understand requirements and carryout the development.
• Proactively learn and apply the latest advancements in LLM technology, including agentic frameworks and advanced RAG techniques.
• Follow and contribute to best practices and development standards for building scalable, reliable, and maintainable LLM-powered applications.
• Write clean, maintainable, and well-documented code, adhering to team-wide coding standards and best practices for production-level software.
• Assist in diagnosing and resolving technical issues related to our LLM-powered applications and infrastructure.

Qualifications

• Bachelor's or Masters degree in computer science, Engineering, or a related field (or equivalent practical experience).
• 3-4 years of hands-on LLM and GenAI software development experience, with an interest or experience in building LLM-powered applications.
• Strong proficiency in Python and a good understanding of building scalable software.
• Atleast 2 years of Experience with prompt engineering, including techniques for crafting and testing prompts to elicit desired behaviors from various LLMs.
• Familiarity with implementing LLM patterns like Retrieval-Augmented Generation (RAG) and an understanding of the underlying components.
• Demonstrated ability to learn quickly, work collaboratively, and deliver high-quality code.
• Good analytical and problem-solving skills with an eagerness to tackle complex technical challenges.
• Strong communication skills.

Preferred Qualifications

• Hands-on experience with LLM application frameworks (e.g., LangChain, LangGraph, LlamaIndex).
• Practical experience with vector databases (e.g., Pinecone, Weaviate, Chroma, FAISS) and embedding models.
• A portfolio of completed software projects (including personal or academic) that demonstrates your technical skills and coding practices.
• Familiarity with deploying applications on a major cloud platform (AWS, Azure, or GCP).
• Experience with version control systems (e.g., Git) and CI/CD concepts.