Native Software Engineer Analyst

About the Role

Launch your software engineering career at the intersection of Python, full-stack development, and Generative AI. This is a full-time onsite role designed for recent graduates and emerging engineers. You will build modern software solutions while learning how artificial intelligence is changing application design, development, testing, and delivery.

Key Responsibilities

• Build and enhance modern applications using Python, APIs, databases, and user-facing technologies.
• Develop backend services and integrations using frameworks such as FastAPI, Flask, or Django.
• Use AI coding assistants and LLM-powered development tools to support coding, testing, debugging, research, and documentation.
• Explore and contribute to solutions using Generative AI, large language models (LLMs), prompt engineering, RAG, embeddings, vector search, knowledge retrieval, and AI agents.
• Gain hands-on experience with emerging agentic technologies such as LangGraph and Model Context Protocol (MCP).
• Partner closely with engineering, product, and business stakeholders to translate business challenges into practical technology solutions.
• Work within a collaborative "2-in-a-box" model, where engineering and business partners jointly shape solutions, priorities, and outcomes.
• Participate in solution design, demonstrations, planning sessions, code reviews, and technical discussions.
• Write tests, troubleshoot applications, document your work, and contribute to reliable deployment practices.
• Review and validate AI-generated code and content.
• Follow established practices for secure coding, data privacy, application reliability, logging, and responsible AI development.
• Learn from feedback, ask questions, take ownership, and continuously expand your technical capabilities.

Requirements & Tech Stack

• A genuine interest in becoming an AI-native software engineer and learning how Generative AI can improve the software development lifecycle.
• Foundational programming knowledge, particularly with Python, developed through coursework, internships, academic work, or personal projects.
• Understanding of core software engineering concepts such as data structures, algorithms, object-oriented programming, testing, debugging, and version control.
• Familiarity with APIs, HTTP, JSON, databases, and web application fundamentals.
• Curiosity about LLMs, AI agents, prompt engineering, RAG, AI-assisted coding, or Generative AI applications.
• A willingness to experiment with new technologies while thoughtfully reviewing and validating results.
• Strong problem-solving skills and an eagerness to tackle unfamiliar technical challenges.
• The ability to collaborate with both technical and non-technical partners.
• A growth mindset with the confidence to ask questions, receive feedback, take initiative, and learn quickly.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, Data Science, or a related technical field.
• 0 years of professional experience required.
• Hands-on exposure to Python through coursework, internships, academic projects, hackathons, open-source contributions, or personal development projects.
• Foundational understanding of software development and web application concepts.

Exposure to one or more of the following is a plus

• Backend: Python, FastAPI, Flask, Django
• Frontend: JavaScript, TypeScript, React, Angular, HTML, CSS
• AI/GenAI: LLMs, prompt engineering, RAG, embeddings, vector databases, semantic search, knowledge retrieval
• Agentic AI: AI agents, LangGraph, agent orchestration, MCP
• Development: Git, GitHub, unit testing, CI/CD, Docker
• Cloud: Azure, AWS, or Google Cloud
• Hackathons, research, technical clubs, open-source communities, or independent coding projects.

You do not need experience with every technology listed.