Full Stack Software Engineer I

Quick Facts

• Role: Full Stack Software Engineer I

Description

A motivated, hands-on Full Stack Software Engineer is needed to build scalable, enterprise-grade applications that combine Python backend development with Generative AI and Agentic AI. Responsibilities include designing RESTful APIs, working with relational and NoSQL databases, and implementing LLM-based solutions such as RAG pipelines, vector search, and agentic workflows. The role emphasizes testing, debugging, documentation, and secure coding practices.

Responsibilities

• Design, develop, test, and maintain Python applications and backend services

• Build and integrate RESTful APIs using FastAPI or Flask

• Write clean, modular, reusable, maintainable code; implement unit tests, logging, and error handling

• Develop SQL queries, manage schemas, and perform basic query optimization for relational databases

• Implement data ingestion, retrieval, and integration workflows for NoSQL databases

• Build GenAI applications using LLMs, including RAG pipelines and vector database-based retrieval

• Handle document ingestion, chunking, embeddings, semantic search, and retrieval workflows

• Integrate LLM APIs and perform prompt engineering

• Develop agentic AI agents and workflows with tool calling and external system integration

• Use LangChain, LangGraph, or similar frameworks for agent orchestration and workflow automation

• Evaluate agent performance, reliability, and response quality

• Use Git for version control and collaborate via code reviews in Agile teams

• Write technical documentation and support application troubleshooting

• Follow secure coding practices and data privacy requirements

Requirements

• Bachelor’s degree in Computer Science/Software Engineering/Information Technology or related field, or equivalent practical experience

• 1–3 years of enterprise software development experience using Python

• Strong Python fundamentals (OOP, data structures) and API development

• Hands-on experience with at least one relational database and one NoSQL database

• Working knowledge of SQL, database design, and data retrieval

• Practical experience integrating LLMs into Python applications

• Understanding of embeddings, vector databases, semantic search, and RAG architectures

• Familiarity with frontier and open-source LLMs

• Basic understanding of agentic AI concepts (tool calling, workflow orchestration)

• Experience using Git and common development tools

• Knowledge of Docker and CI/CD pipelines and deployment practices

• Strong problem-solving, debugging, and communication skills

• Employment eligibility to work in the United States (no visa sponsorship)

Benefits

• Opportunity to work with modern AI technologies and contribute to enterprise-grade software applications