L #2972
Applications open
Full-Time Job
AI Forward Deployed Engineer (AI FDE)
TerraTern
About the role
About The Job
Department: Founder’s Office
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 Forward Deployed Engineer to sit close to our founders and our teams, find the slow and manual parts of our work, and fix them with AI. You will not wait for a long spec. You will talk to the people doing the work, build a working solution quickly, and stay with it until it makes their day easier. Freshers with good projects and a strong urge to build are welcome to apply.
Key Responsibilities
- Work with the founders and team leads in sales, counselling, operations and marketing to understand where time and effort are being lost.
- Build AI tools and automations for those problems, using LLM APIs, agents and no-code tools such as n8n.
- Ship small working versions fast, put them in front of the team, and improve them based on real feedback.
- Identify the bottlenecks, go into the depth of the problem and solve it from the roots using AI, wear any hat as per the requirements
- Train team members to use what you build, and stay with them until they are comfortable.
- Track the time saved and the results each tool brings, and share them with the founders.
- Write simple notes on how each tool works, so anyone on the team can run and fix it.
Eligibility & Requirements
- 1 to 3 years of experience in software, automation or AI work, or a fresher with strong projects, internships or a good portfolio.
- Bachelor’s or Master’s degree in Computer Science, Engineering or a related field.
- Good Python skills, and comfort with APIs, SQL and Git.
- Hands-on use of at least one LLM API such as OpenAI, Claude or Gemini.
- Clear communication, and the ability to explain technical ideas in simple words to people who are not technical.
- Comfort with unclear problems, and the habit of asking good questions before building.
- High ownership, a strong sense of urgency and a habit of finishing what you start.
Nice to Have
- Experience with n8n, Zapier, Make or similar automation tools.
- Experience with RAG, agents or chat assistants.
- A project you built and shipped that real people used, even a small one.
- Interest in immigration, education or global careers.
Why Join TerraTern
- High Impact: Build tools that your own colleagues use every day, and see the result within days.
- Fast Growth: Work close to the founders and learn how a business runs while you build for it.
- Entrepreneurial Culture: Share your ideas, try them out and own the result.
- Collaborative Environment: Work with every team in the company, in a group that likes to learn together.
Skills: product,automation,ownership,apis,agents
Eligibility & process
Who can apply
Seniority: Associate. 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, SQL, Git, Generative AI / LLMs, Machine Learning, PyTorch, TensorFlow, LLMs) & 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 Forward Deployed Engineer (AI FDE)?
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: Associate. Employment type: Fu…
