Key Responsibilities

- Collaborate with engineers, architects, and product teams to design, build, test, and deploy custom applications and services
- Develop API-driven and platform-based solutions across front-end and back-end using your primary language (Python, Java, or TypeScript)
- Work in Agile delivery models (Scrum, Lean, XP) contributing reliably to sprint cycles and communicating progress clearly
- Use AI coding assistants daily as a standard part of delivery — actively, frequently, and with demonstrable impact on your productivity and output quality
- Apply AI across the software delivery lifecycle: AI-generated tests, AI-assisted debugging, AI-accelerated code review, and prompt engineering for development tasks
- Validate AI-generated outputs — check for errors, limitations, and hallucinations; develop sound judgment about when AI output is reliable and when human verification is required
- Contribute to proofs of concept, technical documentation, and solution development alongside senior engineers
- Engage in client-facing environments and learn to communicate technical concepts clearly to non-technical stakeholders
- Develop your understanding of how agentic systems work — how agents are orchestrated, how LLMs are called, and how software connects to AI pipelines — through on-the-job exposure and active self-development

Basic Qualifications

- Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, or a related field




- Foundational programming experience in at least one primary language: Python, Java, TypeScript, or Node.js
- Basic understanding of web technologies including JavaScript, HTML, and CSS
- Academic projects, internships, or personal projects in software development that demonstrate you can build and ship working code
- Understanding of Agile delivery fundamentals
- Active and frequent use of AI tools in day-to-day study or work — successful candidates can demonstrate practical, everyday examples of how they leverage AI to solve problems, accelerate learning, and improve their output
- Sound judgment when using AI: ability to validate outputs, understand limitations, and show curiosity about how AI is reshaping contemporary software engineering
- Demonstrated curiosity about agentic AI — evidence of self-directed exploration through personal projects, side builds, online courses, or experimentation with tools like LangChain, LangGraph, AutoGen, or equivalent; we are looking for inclination and initiative, not production experience

Preferred Skills & Exposure

- Some exposure to LLM APIs in any context (personal projects, coursework, or work)
- API and service-oriented architecture
- Databases — SQL or NoSQL
- Cloud platforms (AWS, Azure, or GCP) and DevOps concepts
- Frontend frameworks such as React or Angular
- Containers (Docker) and CI/CD pipeline basics

📌 Early Talent - AI Native Engineer (Telangana)
🏢 Cerebra
📍 Telangana