AI-Native Software Engineer Analyst, Full-Stack Python
About The Position
This full-time, onsite role is designed for recent graduates and emerging engineers interested in Python, full-stack development, and Generative AI. No prior professional experience is required. The engineer will work with experienced engineers, product partners, and business stakeholders to solve business problems and build modern software solutions, gaining hands-on exposure to Python, APIs, LLMs, prompt and context engineering, RAG, AI agents, LangGraph, and Model Context Protocol (MCP). The role is based at a designated work location five days per week; no relocation is offered. The engineer will develop and enhance applications and backend services, explore Generative AI solutions, and use AI coding assistants in development activities. They will collaborate with engineering, product, and business partners in a shared solution-shaping model, participate in design and planning, and contribute to testing, troubleshooting, documentation, code review, and reliable deployment practices. The position emphasizes validating AI-generated outputs and following secure coding, privacy, reliability, logging, and responsible AI practices. It offers an early-career opportunity to build full-stack engineering fundamentals while learning practical Generative AI and agentic AI techniques.
Requirements
- Bachelor's degree in Computer Science, Software Engineering, Information Technology, Data Science, or a related technical field; candidates nearing completion of their degree are encouraged to apply.
- 0 years of professional experience required.
- Foundational programming knowledge, particularly in Python, developed through coursework, internships, academic work, or personal projects.
- Hands-on exposure to Python through coursework, internships, academic projects, hackathons, open-source contributions, or personal development 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.
- Foundational understanding of software development and web application concepts.
- Genuine interest in becoming an AI-native software engineer and learning how Generative AI can improve the software development lifecycle.
- Curiosity about LLMs, AI agents, prompt engineering, RAG, AI-assisted coding, or Generative AI applications.
- Willingness to experiment with new technologies while thoughtfully reviewing and validating results.
- Strong problem-solving skills and eagerness to tackle unfamiliar technical challenges.
- Ability to collaborate with technical and non-technical partners.
- Growth mindset, with confidence to ask questions, receive feedback, take initiative, and learn quickly.
Nice To Haves
- Exposure to backend technologies such as Python, FastAPI, Flask, or Django.
- Exposure to frontend technologies such as JavaScript, TypeScript, React, Angular, HTML, or CSS.
- Exposure to AI/Generative AI technologies such as LLMs, prompt engineering, RAG, embeddings, vector databases, semantic search, or knowledge retrieval.
- Exposure to agentic AI technologies such as AI agents, LangGraph, agent orchestration, or MCP.
- Exposure to development tools and practices such as Git, GitHub, unit testing, CI/CD, or Docker.
- Exposure to Azure, AWS, or Google Cloud.
- Participation in hackathons, research, technical clubs, open-source communities, or independent coding projects.
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 for coding, testing, debugging, research, and documentation.
- Explore and contribute to solutions involving Generative AI, LLMs, prompt engineering, RAG, embeddings, vector search, knowledge retrieval, and AI agents.
- Gain hands-on experience with agentic technologies such as LangGraph and Model Context Protocol (MCP).
- Collaborate with engineering, product, and business stakeholders to translate business challenges into practical technology solutions.
- Work with engineering and business partners to shape solutions, priorities, and outcomes from concept through delivery.
- Participate in solution design, demonstrations, planning sessions, code reviews, and technical discussions.
- Write tests, troubleshoot applications, document work, and contribute to reliable deployment practices.
- Review and validate AI-generated code and content rather than accepting generated outputs at face value.
- Follow practices for secure coding, data privacy, application reliability, logging, and responsible AI development.
- Learn from feedback, ask questions, take ownership, and continuously expand technical capabilities.
Benefits
- Medical, dental, and vision coverage
- 401(k) plan
- Tuition reimbursement program
- Paid time off and holidays, including at least 23 vacation days per year and 9 company-designated holidays, based on date of hire
- Paid parental leave
- Paid caregiver leave
- Additional sick leave may be available, subject to applicable terms
- Adoption reimbursement
- Short-term and long-term disability benefits
- Life and accidental death insurance
- Supplemental benefit programs, including critical illness, accident, hospital indemnity, and group legal
- Employee Assistance Programs (EAP)
- Employee wellness programs
- Employee discounts of up to 50% on eligible AT&T mobility plans and accessories, AT&T internet and fiber where available, and AT&T phone
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Entry Level
