L #2867
Applications open
Full-Time Job
AI Engineer
TerraTern
About the role
About The Job
Department: Technology & Product
Employment Type: Full-time
About TerraTern
TerraTern is one of India’s fastest-growing Global Talent Mobility startups, helping individuals navigate international relocation with confidence. We deliver end-to-end visa support, job search guidance, and mobility resources designed for global aspirants. Transparency, precision, and client trust are the foundation of everything we build.
Role Overview
We are looking for an AI Engineer to build products that use large language models to help people plan their move abroad. You will work with our product and tech teams to take an idea from a rough sketch to a working feature that real users rely on. Freshers with good projects and a strong interest in AI are welcome to apply.
Key Responsibilities
- Build AI features using LLM APIs, such as chat assistants, document readers and smart search.
- Set up RAG systems so our AI answers from TerraTern’s own trusted information.
- Create AI agents and workflows that handle repeat tasks for our users and our team.
- Connect AI features to our website, apps and internal tools through clean APIs.
- Test every feature on real questions, and fix wrong or unclear answers before users see them.
- Watch speed, cost and accuracy after launch, and bring all three in line.
- Work with product managers and designers so each feature is easy to use and solves a real problem.
Eligibility & Requirements
- 1 to 3 years of experience building software or AI applications, or a fresher with strong projects, internships or open-source work.
- Bachelor’s or Master’s degree in Computer Science, Engineering, AI or a related field.
- Good Python skills, and comfort with APIs, Git and a database.
- Hands-on use of at least one LLM API such as OpenAI, Claude or Gemini.
- Basic understanding of embeddings, vector search and prompt design.
- Clear communication, and the ability to explain technical ideas in simple words.
- Curiosity, ownership and a habit of finishing what you start.
Nice to Have
- Experience with LangChain, LlamaIndex, n8n or similar tools.
- A deployed AI project, even a small personal one.
- Interest in immigration, education or global careers.
Why Join TerraTern
- Impactful Work: Build tools that help people reach jobs and study options abroad.
- Professional Growth: Learn from the team and work on real AI products from day one.
- Entrepreneurial Culture: Share your ideas, try them out and own the result.
- Collaborative Environment: Work closely with product, sales and operations in a team that likes to learn together.
Skills: llms,agents,api,ai,ml,prompt engineering,langchain,rag,python
Eligibility & process
Who can apply
Seniority: Entry level. Employment type: Full-time
Skills & stack
Selection process
Details are shared by the recruiter after shortlisting.
Prep kit
20 resourcesStudy material 4
Aptitude Practice Questions & Mock Tests
Curated logical, quantitative, and verbal reasoning problems for the initial online screening round.
Company-Specific Interview Preparation Corner
Detailed interview experiences, exam formats, and previous test questions for TerraTern and tech roles.
Technical Placement Question Bank
High-yield coding cheat sheets, core CS fundamentals (OOP, DBMS, OS, Networks), and rapid revision guides.
Algorithm, DSA & Live Code Debugger Practice
Hands-on problem sets to improve coding speed and step-by-step memory debugging.
Company-specific guides 4
APTITUDE & LOGIC
Aptitude Practice Questions & Online Mock Tests
Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.
COMPANY GUIDE
TerraTern Interview Preparation Corner
Comprehensive guide covering typical interview formats, common questions, and preparation tips for TerraTern and off-campus tech roles.
MOCK TESTS & PAPERS
Comprehensive Interview Prep Resources & Syllabus
Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.
CODING PRACTICE
Algorithm and Data Structure Problem Set
Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA)
Aptitude, Quantitative Logic & 2 Coding Problems
Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1
Core Tech Stack (Python, Git, Machine Learning, Generative AI / LLMs, PyTorch, TensorFlow, LLMs, SQL) & Live Code Tracing
Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving
Database Schemas, APIs & Architecture Basics
Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion
TerraTern Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
Model answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer
Model answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer
Model answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer
Model answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer
Model answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Behavioural & HR questions 3
Why do you want to join TerraTern as a AI Engineer?
Highlight TerraTern's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Highlight TerraTern's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Competitive Package
Bengaluru, India
Seniority: Entry level. Employment type: …
