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Aereo (Asteria Aerospace-adjacent drones) Placement Guide

Drone Technology & Geospatial AI · Bengaluru, India · ~200+ employees · Founded 2013

Aereo (formerly Aarav Unmanned Systems) is a drone-technology company providing drone hardware, geospatial data and AI-driven analytics for mining, infrastructure, energy and agriculture. A drone/AI/geospatial-engineering recruiter.

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Business Model

An end-to-end drone-and-geospatial-AI company turning aerial data into industrial insights.

Revenue streams

Key products

Customers

Salary & Roles

₹7 – 18+ LPA (drone/AI/geospatial engineer; senior higher)

Roles typically hiring for

Eligibility criteria

Typically 7.0+ CGPA, strong DSA/problem-solving. CS or allied branches preferred for SDE; open branches for analyst roles. Internship conversions common.

Hiring timeline

On-campus Aug–Oct for finals; summer internship hiring Jul–Sep for pre-finals. Offer to joining: 6–11 months.

Skills to prepare

Strong DSA (trees, graphs, DP)System design basicsOne strong languageProblem-solving under time pressureCS fundamentals (OS, DBMS, OOP)Behavioral / leadership stories

SWOT Analysis

Strengths

  • End-to-end drone + AI
  • Geospatial data depth
  • Industrial use-cases
  • Domestic-drone tailwind

Weaknesses

  • Capital intensity
  • Regulatory dependence (drone rules)
  • Hardware margins
  • Competition

Opportunities

  • Drone PLI & adoption
  • Geospatial AI
  • Mining/infra/agri
  • Enterprise programs

Threats

  • Regulatory changes
  • Competition
  • Funding
  • Tech shifts

Competitors

ideaForge Rival

Drone hardware.

Garuda Aerospace Rival

Drones.

Geospatial firms Rivals

Mapping.

Global drone Rivals

Hardware.

Industry Intelligence

Drones and geospatial AI digitise industrial inspection and mapping; Aereo leans on end-to-end drone-plus-AI for enterprises.

Key trends

Outlook

Drone adoption drives growth; regulation and competition are key watch points.

Drones + AI
Focus
Geospatial
Industrial
Use-cases
Mining/infra
Drone PLI
Tailwind
India
Growth
Stage
Scaling

Interview Process

Stage-by-stage, with tips and sample questions

1

Online Assessment

Timed coding test on a platform (HackerRank/Codility) with 2–3 DSA problems and sometimes MCQs on CS fundamentals.

Tips
  • Solve 150–250 LeetCode problems (easy→medium→hard)
  • Master arrays, strings, trees, graphs, DP
  • Dry-run edge cases before submitting
Sample questions
  • Two-pointer / sliding-window array problem
  • Tree traversal / lowest common ancestor
  • Dynamic programming (knapsack/LIS variant)
  • MCQs on time complexity & OS
2

Technical Round (DSA)

Live coding with an engineer. You explain your approach, optimise complexity, and write working code.

Tips
  • Think out loud — communication is scored
  • State brute force, then optimise
  • Discuss time & space complexity explicitly
Sample questions
  • Design an LRU cache
  • Detect a cycle in a linked list
  • Number of islands (BFS/DFS)
  • Find median of two sorted arrays
3

System / Design Round

For some roles: high-level design or low-level design (machine-coding) to test scalability and OOP modelling.

Tips
  • Learn fundamentals: load balancing, caching, sharding, queues
  • Clarify requirements before designing
  • Discuss trade-offs, not just one answer
Sample questions
  • Design a URL shortener
  • Design a rate limiter
  • Low-level design of a parking lot
  • How would you scale a notification system?
4

Behavioral / Bar-Raiser Round

Values and leadership-principles based. Uses your past experiences to predict how you work.

Tips
  • Prepare 6–8 STAR stories (Situation-Task-Action-Result)
  • Map stories to the company’s leadership principles
  • Show ownership, data-driven decisions, and impact
Sample questions
  • Tell me about a time you disagreed with a teammate.
  • Describe your most challenging project.
  • A time you took ownership beyond your role.
  • How do you prioritise when everything is urgent?

Frequently Asked Questions

Walk me through your resume.

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Why this company over its competitors?

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What are your salary expectations?

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How does a hash map work internally?

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Explain process vs thread.

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Design a system to handle 1M requests/sec.

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Estimate the number of delivery vans needed in Bengaluru.

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How would you reduce checkout abandonment on our app?

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