A Software Engineer at Observe.AI plays a critical role in building and scaling the next generation of AI-powered conversation intelligence. The company specializes in analyzing contact center interactions using state-of-the-art speech-to-text, natural language processing (NLP), and large language models (LLMs). As a member of the engineering team, you will design, develop, and maintain high-throughput pipelines that process millions of voice and text data points in real time. The impact of this role is direct and highly visible. You will contribute to core products that transform raw customer interactions into actionable business insights, automated QA workflows, and real-time agent coaching. This requires solving complex engineering challenges around low latency, high availability, and massive scale. You will work on optimizing data ingestion pipelines, integrating sophisticated machine learning models into production workflows, and building robust APIs that power intuitive enterprise dashboards. Engineering at Observe.AI is fast-paced and highly collaborative. You will work alongside machine learning researchers, product managers, and data engineers to turn cutting-edge technology into reliable, enterprise-grade software. This position demands a strong foundation in computer science fundamentals, a passion for clean code, and the ability to navigate complex, distributed environments.
Initial Screening
reportedThe process begins with an initial screening or an online coding assessment.
What to demonstrate
- The process begins with an initial screening or an online coding assessment
- Depth in Coding Assessments
How to prepare
- Be able to walk your CV end to end in two minutes, and say why this company specifically.
- Have your salary expectations, notice period and location constraints ready, and ask for the rest of the loop in writing.
Machine Coding Round
reportedCandidates are evaluated on practical coding skills by writing fully functional code.
What to demonstrate
- Candidates are evaluated on practical coding skills by writing fully functional code
- Depth in Coding Assessments
How to prepare
- Answer aloud and timed: Implement an in-memory key-value store with support for time-based expiration (TTL) and concurrent read/write operations.
- Answer aloud and timed: Design a low-level notification service that supports multiple channels (SMS, Email, Push) and handles rate-limiting per user.
Technical Deep Dives
reportedA series of technical interviews focusing on coding speed and architectural depth.
What to demonstrate
- A series of technical interviews focusing on coding speed and architectural depth
- Depth in Coding Assessments
How to prepare
- Answer aloud and timed: Given an array of strings representing speech transcripts, find the longest common prefix or pattern across multiple conversation logs.
- Answer aloud and timed: Solve a medium-to-hard graph traversal problem, such as finding the shortest path or detecting cycles in a task-dependency network.
System Architecture Interview
reportedLater stages focus on system architecture and leadership capabilities.
What to demonstrate
- Later stages focus on system architecture and leadership capabilities
- Depth in Coding Assessments
How to prepare
- Answer aloud and timed: Implement an efficient algorithm to merge overlapping time intervals representing agent call shifts.
- Answer aloud and timed: Given a stream of real-time call volume data, find the moving average and identify sudden spikes using a sliding window approach.
Cultural Fit Assessment
reportedEnsures candidates can contribute to the scaling challenges of the conversational AI platform.
What to demonstrate
- Ensures candidates can contribute to the scaling challenges of the conversational AI platform
- Depth in Coding Assessments
How to prepare
- Answer aloud and timed: Explain the difference between optimistic and pessimistic locking, and how you would apply them in a high-concurrency transaction environment.
- Answer aloud and timed: How do you design an optimal database schema and indexing strategy for storing millions of daily call transcripts?
PracHub editorial advice for the preparation topics above.
Drive the System Design Conversation
Do not wait for the interviewer to prompt you. Start by clarifying requirements, defining scale assumptions (QPS, storage), outlining the API contracts, and then drawing the high-level architecture.
Be prepared for deep-dive questions on your past projects
Interviewers will drill down into your technical decisions, database choices, and architectural tradeoffs.
Focus on Edge Cases in Coding
Whether in HackerRank, DSA, or Machine Coding, always write code that explicitly handles null values, empty inputs, and concurrency issues. This demonstrates production-level maturity.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Implement an in-memory key-value store with support for time-based expiration (TTL) and concurrent read/write
Implement an in-memory key-value store with support for time-based expiration (TTL) and concurrent read/write operations.
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
Given an array of strings representing speech transcripts, find the longest common prefix or pattern across mu
Given an array of strings representing speech transcripts, find the longest common prefix or pattern across multiple conversation logs.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
Solve a medium-to-hard graph traversal problem, such as finding the shortest path or detecting cycles in a tas
Solve a medium-to-hard graph traversal problem, such as finding the shortest path or detecting cycles in a task-dependency network.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
Implement an efficient algorithm to merge overlapping time intervals representing agent call shifts.
Implement an efficient algorithm to merge overlapping time intervals representing agent call shifts.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
Given a stream of real-time call volume data, find the moving average and identify sudden spikes using a slidi
Given a stream of real-time call volume data, find the moving average and identify sudden spikes using a sliding window approach.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
Explain the difference between optimistic and pessimistic locking, and how you would apply them in a high-conc
Explain the difference between optimistic and pessimistic locking, and how you would apply them in a high-concurrency transaction environment.
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
Explain how operating system threads handle context switching and how to prevent deadlocks in multi-threaded a
Explain how operating system threads handle context switching and how to prevent deadlocks in multi-threaded applications.
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
Stop tag and share joins from fanning out a page
resource_tag is (resource_id, tag_id) with PK (resource_id, tag_id); resource_share is (resource_id, shared_with_user_id, permission). The tagged-and-shared listing inner-joins resource to both, filters tenant_id, tag_id = ANY($2) and shared_with_user_id = $3, orders by updated_at DESC and takes 50. Pages come back with fewer than 50 distinct resources and the total in the header is far too high. Explain the row multiplication, rewrite both the page query and the count query so each is correct, and name the index each one needs. PostgreSQL 16.
Approach
- Do the arithmetic against the predicates that are actually there. An inner join emits one row per matching child row, and both joins are filtered: tag_id = ANY($2) admits only the requested tags, shared_with_user_id = $3 admits one user's share rows. So a resource holding three of the requested tags and shared with $3 once yields three rows, not one — the multiplier is its count of matching tags times its share rows for that single user, and that second factor is 1 unless the table admits duplicate (resource_id, shared_with_user_id) pairs. LIMIT 50 then limits rows rather than resources, and COUNT(*) counts pairs — the header is the product, not the population.
- Reject DISTINCT as the fix. It deduplicates after the product has been built, so the planner must materialise and sort the fanned-out set before the LIMIT can apply, and it leaves any SUM or AVG in the same select list wrong.
- Rewrite both filters as semi-joins, keeping resource as the only row source: AND EXISTS (SELECT 1 FROM resource_tag rt WHERE rt.resource_id = r.resource_id AND rt.tag_id = ANY($2)) and the same shape against resource_share. A semi-join stops at the first match per resource and preserves the driving index order, so ORDER BY updated_at DESC, resource_id DESC LIMIT 50 still stops after 50 rows.
- Count with the same predicates and no join at all: SELECT count(*) FROM resource r WHERE r.tenant_id = $1 AND r.status = 'active' AND EXISTS (...) AND EXISTS (...). Nothing multiplies a resource, so the number is the population.
Follow-up
- The filter changes from 'any of these tags' to 'all of these tags'. Rewrite it and state what it costs relative to the ANY form.
- A resource can be shared with the same user twice under different permissions. Does your count change, and should it?
Explain why the owner filter ignores the listing index
The only index on resource is (tenant_id, status, updated_at DESC, resource_id DESC). A new endpoint returns one user's resources across all statuses, newest created first: WHERE tenant_id = $1 AND owner_user_id = $2 ORDER BY created_at DESC LIMIT 20. On a tenant with 2M rows it takes 900 ms and EXPLAIN shows a sort above a large scan. Explain precisely why the existing index cannot serve it, give the index that can, and state which of these the new index still will not help: owner_user_id alone across tenants; the same query ordered by updated_at. PostgreSQL 16.
Approach
- Separate the two jobs an index does. For filtering, a composite btree is seekable only on a left prefix, so with no predicate on status the scan can at best range over tenant_id and test owner_user_id per row; PostgreSQL 16 has no btree skip scan to jump the unconstrained column.
- For ordering, the index is sorted by (status, updated_at) within a tenant and not by created_at, so the LIMIT cannot stop early: every matching row is read and then sorted. That is the 'Sort Method: top-N heapsort' line, and it is why the plan reads 2M rows to answer with 20.
- Derive the replacement from the access path — equality, equality, then the ordering column: CREATE INDEX CONCURRENTLY ON resource (tenant_id, owner_user_id, created_at DESC). The scan seeks to the (tenant, owner) range and walks 20 entries in order, so the Sort node disappears along with the row-read.
- Treat INCLUDE (title, status) as conditional, not free. An index-only scan still visits the heap for any row whose page is not marked all-visible, so on a table taking 1.2k writes/second the win depends on autovacuum keeping the visibility map current, and the wider index costs more on every insert.
Follow-up
- 90% of rows are status='active'. Would a partial index WHERE status = 'active' change your answer, and for which of the three queries?
- A dashboard runs this for 40 owners in one page load. What changes about the design?
Design an expense-sharing application (similar to Splitwise) supporting unequal splits, group expenses, and ba
Design an expense-sharing application (similar to Splitwise) supporting unequal splits, group expenses, and balance simplification.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Design a speech-based task processing system that prioritizes audio files based on duration and customer tier.
Design a speech-based task processing system that prioritizes audio files based on duration and customer tier.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Design a low-level notification service that supports multiple channels (SMS, Email, Push) and handles rate-li
Design a low-level notification service that supports multiple channels (SMS, Email, Push) and handles rate-limiting per user.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
How do you design an optimal database schema and indexing strategy for storing millions of daily call transcri
How do you design an optimal database schema and indexing strategy for storing millions of daily call transcripts?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
How does a database transaction maintain ACID properties, and what are the different transaction isolation lev
How does a database transaction maintain ACID properties, and what are the different transaction isolation levels?
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Walk me through the most technically challenging project on your resume, explaining your architectural choices
Walk me through the most technically challenging project on your resume, explaining your architectural choices and what you would change today.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Describe a situation where you had to debug a critical production outage under tight time constraints. How did
Describe a situation where you had to debug a critical production outage under tight time constraints. How did you identify the root cause?
Approach
- Establish what changed and when, before forming any theory.
- Pick a bisection that eliminates candidates whichever way it turns out.
- Check the instrumentation before believing the symptom.
- Separate the trigger from the cause; the deploy is rarely the bug.
Follow-up
- What would you look at first, and what would it rule out?
- How would you tell a cause from a coincidence here?
Built from the rounds and topics Observe.AI candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Observe.AI loop
- Write out the reported sequence: Initial Screening, Machine Coding Round, Technical Deep Dives, System Architecture Interview, Cultural Fit Assessment.
- For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.
Deliverable: A one-page map of the 5 reported rounds, with the weakest marked.
02Work Coding Assessments
- Spend the session on Coding Assessments, which Observe.AI candidates report being tested on.
- Write one worked example in Coding Assessments and time yourself on it.
Deliverable: One timed worked example in Coding Assessments.
03Work Data Structures & Algorithms (DSA)
- Spend the session on Data Structures & Algorithms (DSA), which Observe.AI candidates report being tested on.
- Write one worked example in Data Structures & Algorithms (DSA) and time yourself on it.
Deliverable: One timed worked example in Data Structures & Algorithms (DSA).
04Work Machine Coding
- Spend the session on Machine Coding, which Observe.AI candidates report being tested on.
- Write one worked example in Machine Coding and time yourself on it.
Deliverable: One timed worked example in Machine Coding.
05Answer out loud: Machine Coding & Low-Level Design
- Answer aloud, timed: Design an expense-sharing application (similar to Splitwise) supporting unequal splits, group expenses, and balance simplification.
- Answer aloud, timed: Design a speech-based task processing system that prioritizes audio files based on duration and customer tier.
Deliverable: Spoken answers to 2 reported Machine Coding & Low-Level Design question(s), under time.
06Answer out loud: Data Structures & Algorithms
- Answer aloud, timed: Given an array of strings representing speech transcripts, find the longest common prefix or pattern across multiple conversation logs.
- Answer aloud, timed: Solve a medium-to-hard graph traversal problem, such as finding the shortest path or detecting cycles in a task-dependency network.
Deliverable: Spoken answers to 2 reported Data Structures & Algorithms question(s), under time.
07Answer out loud: Computer Science Fundamentals
- Answer aloud, timed: Explain the difference between optimistic and pessimistic locking, and how you would apply them in a high-concurrency transaction environment.
- Answer aloud, timed: How do you design an optimal database schema and indexing strategy for storing millions of daily call transcripts?
Deliverable: Spoken answers to 2 reported Computer Science Fundamentals question(s), under time.
Expand any day for tasks and deliverables. Your progress is saved on this device.
Behavioural rounds judge the decision you made and what it cost.
How do you handle a scenario where you disagree with a product manager or a tech lead on a technical approach?
How do you handle a scenario where you disagree with a product manager or a tech lead on a technical approach?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Tell me about a time you had to quickly learn a new technology or framework to deliver a critical business fea
Tell me about a time you had to quickly learn a new technology or framework to deliver a critical business feature.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Tell callers you do not own that their integration breaks
A field in a write endpoint's response must change shape. You own the endpoint; you do not own the four internal callers or the outbound webhook consumers who read it. Describe a deprecation you were responsible for: what you shipped first, how you established who was actually reading the field, the window you gave and what set its length, what you did about the consumer who never moved, and how you decided removal was safe. Name the signal you used, not the announcement you sent.
Approach
- Establish the reader set empirically rather than from a wiki of owners: per-field usage counters keyed by principal, or access logs attributed to a consumer. State the blind spot of whichever you pick, since a consumer that reads the field only on a monthly job will not appear in a week of logs.
- Ship additive first. Populate the new field alongside the old one so no reader is forced to move, which is also what keeps a rolling deploy safe, because old and new instances answer the same requests at the same time and a rollback must still find the old shape present.
- Set the window from the slowest legitimate consumer's release cadence, not from your calendar, and decide separately what to do for a consumer with no release process at all, such as an external webhook endpoint you can only email.
- Convert silence into evidence before you rely on it: a short, low-traffic removal window that makes a still-dependent consumer fail visibly and loudly while you are watching, rather than at three in the morning after you have moved on.
Follow-up
- How would you detect a consumer that reads the field only during a monthly export?
- One caller refuses to move and has a commercial relationship behind it. What changes in your plan and what does not?
- 01
How do you handle a scenario where you disagree with a product manager or a tech lead on a technical approach?
- 02
Tell me about a time you had to quickly learn a new technology or framework to deliver a critical business feature.
- 03
A field in a write endpoint's response must change shape. You own the endpoint; you do not own the four internal callers or the outbound webhook consumers who read it. Describe a deprecation you were responsible for: what you shipped first, how you established who was actually reading the field, the window you gave and what set its length, what you did about the consumer who never moved, and how you decided removal was safe. Name the signal you used, not the announcement you sent.
What is the most critical round in the Observe.AI software engineering loop?
The Machine Coding round is highly critical. It acts as a major filter because it tests your practical coding, architecture, and testing skills simultaneously. Having a fully functional, clean, and tested solution is essential to advance.
Observe.AI Software Engineer candidate reports ↗How deep do I need to go into Machine Learning concepts?
Unless you are applying for a specialized ML Engineer role, you do not need to know how to train models. However, you should understand how to integrate ML APIs, design pipelines that handle model latency, and orchestrate data flows for AI models.
Observe.AI Software Engineer candidate reports ↗What is the typical timeframe for the entire interview process?
The process generally takes 3 to 4 weeks from the initial recruiter screen to the final offer. However, ensure you maintain active communication with your HR contact to keep the process moving smoothly.
Observe.AI Software Engineer candidate reports ↗Are remote work options supported for this position?
Observe.AI operates with hybrid and location-specific expectations depending on the office location (such as Bengaluru or the US). It is highly recommended to clarify the specific hybrid policy for your target office during your initial HR screen.
Observe.AI Software Engineer candidate reports ↗What topics does Observe.AI test in interviews?
Observe.AI interviews most often cover Problem Solving, Communication Skills, Machine Learning (Core Concepts), Agentic AI, and Coding Assessments. The exact emphasis depends on the specific role you apply for.
Observe.AI Software Engineer candidate reports ↗Sources & methodology 3 sources ↗
No official company page is cited. Rounds and questions come from candidate reports and PracHub editorial material; each source shows the date it was read.
- 01Observe.AI Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
Candidate reports · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
PracHub page · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
PracHub page · Accessed 2026-09-22
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