AI Engineering Intern / Harness Engineering Intern

Round 1: Online assessment (coding & logical reasoning) → Round 2: Technical interview (system design, AI concepts, coding) → Round 3: HR interview (fit, motivation, cultural alignment)

Google is known for its open, innovative work culture that encourages employees to spend 20% of their time on passion projects. The company offers strong growth opportunities, mentorship programs, and a balanced work‑life environment with flexible policies and extensive employee benefits.

Google's interview process typically consists of an online coding assessment followed by two to three technical rounds focusing on data structures, algorithms, system design, and AI concepts. The difficulty is high, with emphasis on problem‑solving speed and clarity of thought. Candidates are advised to practice coding under time constraints and be ready to discuss their projects in depth.

B.Tech/B.E/M.Tech/M.Sc in Computer Science, Information Technology, Electronics & Communication or related streams; Minimum CGPA 6.5/10 (or equivalent); Final year students of 2024, 2025 or 2026 batches; No active backlogs at the time of joining; Strong academic record and passion for AI + software engineering.

Jar is an emerging technology startup focused on building AI‑driven productivity tools for software engineering teams. Founded by a group of engineers passionate about automating repetitive coding tasks, Jar aims to create "harnesses" – intelligent assistants that sit inside the development pipeline and help engineers write, test, debug, and ship code faster. The company operates out of a vibrant office in Koramangala, Bengaluru, and follows a fast‑paced, experiment‑first culture where every intern gets to contribute to real product features from day one. The AI Engineering Intern role is designed for fresh graduates or final‑year students who want to blend their software development skills with cutting‑edge AI research. Interns will work on end‑to‑end AI‑powered systems that augment engineering workflows. This includes designing prompts for large language models, building feedback loops that let the AI learn from developer actions, and integrating the solutions with existing CI/CD pipelines. The position offers exposure to both frontend and backend development, as well as DevOps practices, making it a holistic learning experience. Key responsibilities include: 1. Designing and implementing AI‑driven modules that assist developers in code generation, testing, and debugging. 2. Building full‑stack prototypes that connect frontend interfaces with backend services and databases. 3. Experimenting with agentic AI and loop‑based programming techniques to create self‑improving tools. 4. Collaborating with senior engineers to integrate AI harnesses into the company’s CI/CD infrastructure. 5. Writing clean, maintainable code and conducting unit/integration testing. 6. Conducting performance benchmarking of AI models and optimizing latency. 7. Documenting design decisions, experiment results, and user feedback. 8. Exploring emerging research papers on AI‑assisted software engineering and proposing practical implementations. 9. Managing cloud resources and ensuring security best practices in deployment. 10. Independently troubleshooting issues and iterating on solutions based on real‑world usage. The tech stack typically involves React or Vue for the frontend, Node.js/Python for backend services, PostgreSQL or MongoDB for data storage, Docker/Kubernetes for containerization, and cloud platforms such as AWS or GCP for hosting. Familiarity with LLM APIs (e.g., OpenAI, Anthropic) and prompt engineering is a plus. Growth path: High‑performing interns may receive a full‑time offer as AI Engineer or Software Engineer, with opportunities to lead product modules, contribute to research publications, and mentor future interns. Jar’s flat hierarchy ensures visibility to leadership and rapid skill development. Why join Jar? You will work on tangible AI products that directly impact developer productivity, gain hands‑on experience across the full technology stack, and be part of a collaborative team that values curiosity, experimentation, and ownership. The role is ideal for candidates who love building tools that engineers actually use and who thrive in a startup environment where ideas move quickly from concept to production.