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Tempus labs Software Engineer Interview Guide

Tempus labs Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

As a Software Engineer at Tempus Labs, you will sit at the intersection of technology and precision medicine. You will design, build, and scale the critical software infrastructure that processes immense volumes of clinical and genomic data. Your work directly empowers physicians to make real-time, data-driven treatment decisions, accelerating the pace of personalized cancer care and therapeutic discovery. The engineering team is responsible for developing high-performance data pipelines, robust APIs, and interactive visualization tools that make complex biological data accessible and actionable. This role requires solving complex distributed systems challenges, optimizing data storage, and ensuring the seamless integration of machine learning models into clinical workflows.

This guide is scoped to a Software Engineer candidate at Tempus labs.

Focus areas

  • System Design
  • Coding Interview Practice
  • JavaScript

The Tempus labs interview process

Tempus labs candidates report 3 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Recruiter Screen

Initial rapid screen to align on your background and interest in the company.

What to demonstrate

  • Initial rapid screen to align on your background and interest in the company
  • Depth in System Design

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.

Technical Screen

Assessment of foundational programming and database knowledge through online assessment.

What to demonstrate

  • Assessment of foundational programming and database knowledge through online assessment
  • Depth in System Design

How to prepare

  • Answer aloud and timed: Solve a classic array manipulation problem (such as finding duplicates or subarray sums) within an optimal time complexity.
  • Answer aloud and timed: Write a program to parse, clean, and format unstructured clinical trial text inputs.

Virtual Onsite Interview

Comprehensive interview loop with multiple rounds focusing on live coding, system design, and behavioral alignment.

What to demonstrate

  • Comprehensive interview loop with multiple rounds focusing on live coding, system design, and behavioral alignment
  • Depth in System Design

How to prepare

  • Answer aloud and timed: Design a RESTful API using Node.js and Express to handle real-time clinical data ingestion.
  • Answer aloud and timed: How would you design a scalable clinical trial matching system that handles millions of patient profiles and complex eligibility criteria?

Where candidates lose points

Master the JavaScript Ecosystem

Given our heavy reliance on Node.js, Express, and React, brush up on core language concepts such as promises, async/await, closures, and state management before your technical rounds.

Practice SQL Aggregations

Ensure you can comfortably write and optimize queries on the fly. Focus on relational database design principles and understand when to normalize versus denormalize data.

Be Ready for Behavioral Scenarios

Prepare concrete examples of how you have handled shifting priorities, resolved technical disagreements, and collaborated with product managers in past roles.

Ask Clarifying Questions

During both the coding and system design rounds, avoid jumping straight into a solution. Take a few minutes to clarify requirements, discuss edge cases, and outline your approach with your interviewers.

Questions & practice

Given an input string, write a function to calculate the term frequency-inverse document frequency (TF-IDF) of

Medium · Coding and Algorithms

Given an input string, write a function to calculate the term frequency-inverse document frequency (TF-IDF) of specific terms.

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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 a function that processes an array of data and outputs a specific string format based on dynamic inp

Medium · Coding and Algorithms

Implement a function that processes an array of data and outputs a specific string format based on dynamic input parameters in JavaScript.

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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 classic array manipulation problem (such as finding duplicates or subarray sums) within an optimal tim

Medium · Coding and Algorithms

Solve a classic array manipulation problem (such as finding duplicates or subarray sums) within an optimal time complexity.

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

Write a program to parse, clean, and format unstructured clinical trial text inputs.

Medium · Coding and Algorithms

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

Write a SQL query to join patient demographic tables with clinical test results, returning the most recent tes

Medium · Database and SQL

Write a SQL query to join patient demographic tables with clinical test results, returning the most recent test record per patient.

Approach

  1. Name the grain you start from and join outward from it.
  2. Check whether any join is one-to-many before aggregating, or the sums inflate.
  3. Say which index the query would use, and what makes it unusable.
  4. Handle the rows that do not match: that is usually the actual question.

Follow-up

  • How does the query change if that join becomes one-to-many?
  • What happens to this when the table is ten times larger?

How would you optimize a slow-performing SQL query that aggregates large volumes of daily diagnostic data?

Medium · Database and SQL

Approach

  1. Name the grain you start from and join outward from it.
  2. Check whether any join is one-to-many before aggregating, or the sums inflate.
  3. Say which index the query would use, and what makes it unusable.
  4. Handle the rows that do not match: that is usually the actual question.

Follow-up

  • How does the query change if that join becomes one-to-many?
  • What happens to this when the table is ten times larger?

Design a RESTful API using Node.js and Express to handle real-time clinical data ingestion.

Medium · System Design and API Development

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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 would you design a scalable clinical trial matching system that handles millions of patient profiles and c

Medium · System Design and API Development

How would you design a scalable clinical trial matching system that handles millions of patient profiles and complex eligibility criteria?

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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?

Discuss the architectural trade-offs of using a relational database versus a NoSQL database for storing genomi

Medium · System Design and API Development

Discuss the architectural trade-offs of using a relational database versus a NoSQL database for storing genomic sequencing results.

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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?

Explain how you would implement rate limiting and secure authentication for a public-facing healthcare API.

Medium · System Design and API Development

Approach

  1. Say who the caller is and what they do when the call fails halfway.
  2. Define the identity of a request so a retry cannot double-apply it.
  3. Separate accepted, pending, failed and confirmed; they are different facts.
  4. Design the error taxonomy before the success shape; callers branch on it.

Follow-up

  • What happens if the caller retries after a timeout?
  • How does a client discover it is on an old version of this contract?

Explain the difference between inner joins, outer joins, and subqueries, and when to use each when querying cl

Medium · Database and SQL

Explain the difference between inner joins, outer joins, and subqueries, and when to use each when querying clinical datasets.

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

Read latency spikes on a sixty-second sawtooth

Medium · cache stampede · single-flight · ttl

The cached listing read path serves about 14k reads/second at an 85% hit rate. p99 sits at 35 ms for 57 seconds, jumps to 900 ms for 3, and repeats. During each spike the primary shows several hundred identical listing queries starting within the same millisecond, all carrying one large tenant's id. Cache entries use a 60-second TTL. Give the mechanism, the ordered checks, the fix, and the correctness hazard your fix must not introduce.

Approach

  1. Match the period to a configured number before theorising about load. A spike every 60 seconds against a 60-second TTL is an entry expiring, and you confirm it by correlating spike timestamps with the entry's write time rather than with the traffic curve. If the period had matched a cron or a GC interval instead, this is a different investigation.
  2. Establish the concurrency of the miss. Several hundred identical queries in one millisecond means the miss path has no coalescing: every request that arrives between expiry and repopulation recomputes. The herd size is that key's arrival rate times its recompute time, so at 1.2k reads/second for the hot key and a 250 ms recompute you expect about 300 concurrent misses, which matches what is observed.
  3. Add single-flight on the miss path so one caller per key recomputes under a short-lived lock while the rest wait for its result. Prefer stale-while-revalidate where the read tolerates it: return the expired value immediately and refresh asynchronously, which removes the latency spike rather than serialising it into a queue of waiters.
  4. De-synchronise the keys. Write TTLs with jitter, for example 60 seconds plus or minus 10%, so a deploy or a mass invalidation does not align every key on the same second and turn a per-key herd into a fleet-wide one.

Follow-up

  • The same sawtooth appears on a key that is invalidated on write rather than expired. Is that the same bug?
  • How does your answer change if the recompute takes 4 seconds instead of 250 ms?

Suggested practice checklist

Built from the rounds and topics Tempus labs candidates report.

Day 1 — Map the Tempus labs loop

  • Write out the reported sequence: Recruiter Screen, Technical Screen, Virtual Onsite Interview.
  • 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 3 reported rounds, with the weakest marked.

Day 2 — Work System Design

  • Spend the session on System Design, which Tempus labs candidates report being tested on.
  • Write one worked example in System Design and time yourself on it.

Deliverable: One timed worked example in System Design.

Day 3 — Work Coding Interview Practice

  • Spend the session on Coding Interview Practice, which Tempus labs candidates report being tested on.
  • Write one worked example in Coding Interview Practice and time yourself on it.

Deliverable: One timed worked example in Coding Interview Practice.

Day 4 — Work JavaScript

  • Spend the session on JavaScript, which Tempus labs candidates report being tested on.
  • Write one worked example in JavaScript and time yourself on it.

Deliverable: One timed worked example in JavaScript.

Day 5 — Answer out loud: Coding and Algorithms

  • Answer aloud, timed: Given an input string, write a function to calculate the term frequency-inverse document frequency (TF-IDF) of specific terms.
  • Answer aloud, timed: Implement a function that processes an array of data and outputs a specific string format based on dynamic input parameters in JavaScript.

Deliverable: Spoken answers to 2 reported Coding and Algorithms question(s), under time.

Day 6 — Answer out loud: System Design and API Development

  • Answer aloud, timed: Design a RESTful API using Node.js and Express to handle real-time clinical data ingestion.
  • Answer aloud, timed: How would you design a scalable clinical trial matching system that handles millions of patient profiles and complex eligibility criteria?

Deliverable: Spoken answers to 2 reported System Design and API Development question(s), under time.

Day 7 — Answer out loud: Database and SQL

  • Answer aloud, timed: Write a SQL query to join patient demographic tables with clinical test results, returning the most recent test record per patient.
  • Answer aloud, timed: How would you optimize a slow-performing SQL query that aggregates large volumes of daily diagnostic data?

Deliverable: Spoken answers to 2 reported Database and SQL question(s), under time.

Behavioural preparation

Behavioural rounds judge the decision you made and what it cost.

Describe a time when you had to work under tight deadlines with constantly shifting product priorities. How di

Medium · Behavioral and Collaboration

Describe a time when you had to work under tight deadlines with constantly shifting product priorities. How did you manage your time and deliver?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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?

How do you handle a situation where there is a disagreement between engineering and product management regardi

Medium · Behavioral and Collaboration

How do you handle a situation where there is a disagreement between engineering and product management regarding a feature's technical scope?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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?

Why are you interested in joining Tempus Labs, and how do you see your engineering background contributing to

Medium · Behavioral and Collaboration

Why are you interested in joining Tempus Labs, and how do you see your engineering background contributing to our mission of precision medicine?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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 complex technical challenge you solved in your previous role. How did you communicate the tech

Medium · Behavioral and Collaboration

Tell me about a complex technical challenge you solved in your previous role. How did you communicate the technical details to non-technical stakeholders?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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?