Software Associates

DOCTUTORIALS
Software Associate
Role Summary
The Software Associate is an entry-level full-stack engineering role for candidates with strong fundamentals, learning agility and practical exposure to AI-assisted software development.

Key Responsibilities
1. Application Development

• Develop and maintain backend APIs using Python and FastAPI.
• Build responsive web components using React, Next.js and TypeScript/JavaScript.
• Work with SQL databases, Git, automated tests and development environments.
• Understand requirements, estimate assigned work and complete tasks with quality.

2. AI-assisted Engineering

• Use approved AI coding tools for learning, code generation, debugging and documentation.
• Understand basic LLM, RAG, Agentic AI and API-based AI integration concepts.
• Review and test AI-generated code instead of using it without validation.
• Never share credentials, production data or confidential source code with unapproved tools.

3. Quality and Collaboration

• Write clean code, unit tests and technical documentation.
• Participate in code reviews, QA support and production-defect analysis.
• Raise blockers early and take ownership of assigned work through closure.
• Continuously improve technical, product and communication skills.

Required Skills and Experience

• 0+ years; capable freshers are eligible.
• Strong programming, data structures, problem-solving and web-development fundamentals.
• Working knowledge of Python, FastAPI or a similar API framework.
• Working knowledge of React/Next.js, JavaScript/TypeScript, HTML and CSS.
• Basic SQL, Git, testing and debugging knowledge.
• Practical understanding of Generative AI, LLMs, RAG, Agentic AI and responsible AI use relevant to the role.
• Ability to use approved AI tools productively while protecting source code, credentials, learner data and organisational information.
• Commitment to human review, testing, security validation and traceability for AI-assisted outputs.

Good-to-Have Experience

• Academic or personal projects using FastAPI, React/Next.js, LLM APIs or RAG.
• Docker, AWS or CI/CD exposure.
• EdTech or medical-learning interest.

How Success Will Be Measured

• Assigned features are completed with improving quality and independence.
• Code-review feedback is applied consistently.
• AI tools are used safely and productively.
• Technical and product knowledge grows measurably.
• Work consistently delivers measurable outcomes and business valuenot merely completion of assigned tasks or activities.

Expected mindset: Own the outcome, use AI responsibly, communicate risks early and deliver secure, measurable value for DocTutorials and its learners.