We are looking for a highly skilled and motivated Software Engineer 3 to join our team, focused on building scalable, efficient, and intelligent systems that integrate with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) pipelines, and orchestration frameworks. You will play a critical role in designing and implementing intelligent workflows that combine traditional software engineering principles with cutting-edge AI technologies.

Key Responsibilities

•  Design, develop, and maintain software components that integrate Large Language Models (LLMs) into scalable services and applications

•  Collaborate with senior engineers, product managers, and data scientists to translate business requirements into LLM-powered features and tools

•  Implement and optimize LLM orchestration workflows using frameworks like LangChain, LlamaIndex, or custom-built logic

•  Develop and refine prompt strategies for specific use cases, including experimentation with zero-shot, few-shot, and chain-of-thought prompting

•  Integrate vector databases and RAG (retrieval-augmented generation) pipelines to enable context-aware AI applications

•  Write clean, maintainable, and testable code in Python, following best practices and participating in code reviews and peer programming

•  Contribute to the deployment and scaling of applications using Docker, Kubernetes CI/CD pipelines, and cloud infrastructure (e.g., AWS, GCP, or Azure)

•  Monitor system performance and work with senior engineers to troubleshoot and resolve production issues related to LLM usage and integration

•  Stay current with advancements in LLMs, prompt engineering, and orchestration tools, and help evaluate and recommend new tools or libraries

•  Participate in Agile development ceremonies (sprint planning, standups, retrospectives) and contribute to continuous team improvement

Education and Experience:

•  Bachelor’s degree in computer science, software engineering, or a related technical field

•  4 years of professional software development experience, ideally building scalable APIs, services, or backend systems

Skills:

•  Proficiency in Python and strong coding fundamentals, with experience working in production environments

•  Experience with building and integrating LLM-based systems, including hands-on use of APIs from platforms like Azure OpenAI, AWS Bedrock, or Google Gemini

•  Familiarity with prompt engineering techniques such as zero-shot, few-shot, chain-of-thought prompting, and task-specific prompt templating

•  Understanding of how to orchestrate LLM workflows using frameworks and tools like LangChain, LlamaIndex, or similar orchestration layers

•  Experience working with vector databases (e.g., FAISS, Pinecone, Weaviate) and integrating retrieval-augmented generation (RAG) techniques into applications

•  Exposure to cloud platforms such as AWS, GCP, or Azure, and basic understanding of deploying applications using containers on Kubernetes

•  Experience working with version control (Git) and participating in team-based Agile development workflows (e.g., sprint planning, code reviews, CI/CD)

•  An eagerness to learn and apply new technologies in the rapidly evolving LLM and AI tooling ecosystem

•  Strong communication skills and the ability to collaborate across functions, document clearly, and contribute meaningfully to discussions

•  Experience working with web frameworks (e.g., FastAPI, Flask, Express) or contributing to full-stack applications involving LLMs

Soft Skills:

•  Strong communication skills with the ability to translate complex technical concepts to non-technical audiences.

•  Proven ability to influence cross-functional teams without direct authority.