Naut Space
Finding exceptional talent starts with understanding what a client actually needs. That goes beyond technical skills and experience.
Most applicants will have relevant experience on paper. The harder question is whether they can operate effectively in an international startup or scale-up: work independently, communicate clearly, handle ambiguity, take initiative and adapt to the way a team actually works.
Our goal is long-term alignment between the client and candidate, with the opportunity to build and expand a team here in Sri Lanka. For that to happen, both sides need to be genuinely happy with the match.
We use technology to make the process faster, but we don’t use it to make the judgment for us.
Our 4-step vetting process.
- 01 Profile & portfolio review Education, experience, work samples and responses give us a strong picture of the candidate
- 02 The 10-minute alignment call A quick call helps to assess genuine interest, communication and working style
- 03 Role-specific take-home assessments A role-specific test designed around the kind of work the candidate will actually be doing
- 04 The deep-dive final interview A long-form interview with the founders to evaluate soft skills, proactivity, culture fit and how they’ll thrive within the team
Step 01
Profile & portfolio review.
Hundreds of applications can come in for a single posting, so it would be both impractical and unnecessary to put every candidate through testing or interviews.
Our role at this stage is to define what an ideal candidate looks like, eliminate clear mismatches, and then rank the remaining profiles based on their CV and screening questionnaire. For marketing and other creative roles, we also review the candidate’s portfolio.
Education, the companies someone has worked for, the length of time they spent there, and the type of work they’ve done can all provide strong signals. Together, these give us an initial view of whether someone has the experience, trajectory and background to be a strong fit before we invest more time in the process.
1. What we look for
- Tenure & adaptability. How long someone stays at a company can tell us something about the environments they are used to. Someone who has spent 15 years in a large enterprise may be excellent at what they do, but we need to understand whether they are comfortable with the speed, ambiguity and changing priorities of a startup environment.
- Practical execution. We look for evidence of what someone actually did, not just what their job description said they were responsible for. What did they work on every day? What did they build, manage or improve? What tools did they use? If a CV doesn’t give us enough detail, we’ll ask the candidate directly rather than make assumptions.
- International experience. Working with global teams requires more than English fluency. We look for experience communicating with people across different cultures, time zones and working styles.
- Remote autonomy. Remote work requires people who can manage their own time, communicate asynchronously and keep moving without constant supervision. Previous experience working this way is a strong signal.
Where AI fits in
We use AI to do more than scan CVs for keywords. Our team uses modern LLMs and reasoning models to understand the business context behind a role and interpret a candidate’s experience against what the client actually needs.
Instead of simply asking “Does this CV contain the right words?”, we can ask:
- What experience is genuinely relevant to this role?
- What evidence is there that the candidate has actually done this work?
- Which parts of their background are transferable, even if the job title or industry doesn’t match exactly?
- What important experience is missing or unclear?
- Are there inconsistencies between the CV, questionnaire and portfolio?
- What should we ask the candidate about before making a decision?
AI can then summarise the relevant experience, surface strong signals, flag potential gaps and generate areas for us to explore in the next conversation. It acts as an intelligent first-pass analyst, helping our team process large volumes of information consistently and spend more time on the candidates who warrant a closer look.
But it doesn’t decide who advances. Every shortlisted profile is reviewed by a human. AI can surface evidence and questions, but our team makes the judgment about whether someone’s experience, trajectory and potential actually make sense for the role.
2. The 5-minute screening questionnaire
Our questionnaire gives us a quick understanding of whether the role works for the candidate and whether the candidate works for the role.
- Self-selection. Candidates see the key requirements early, so they can decide whether the opportunity genuinely makes sense for them.
- Practical logistics. We verify availability, start dates, existing commitments, time zone compatibility and other practical considerations.
- Communication. We include one or two open-ended questions about the candidate’s interest in the role. We’re not looking for perfectly polished answers. We’re interested in how someone naturally communicates their thoughts and whether there is genuine interest behind the application.
A standard system might reject someone automatically because they have a two-month notice period. We would rather understand the situation first. Sometimes an exceptional candidate is worth waiting for.
3. Portfolio review
For creative, marketing and engineering roles, a portfolio often tells us more than a CV can. We look at:
- Focus & domain depth. If someone applies as a videographer, we want to see meaningful video work, not a portfolio dominated by static graphics.
- Brand & aesthetic alignment. If a client operates an organic food brand with a natural visual identity, we look for candidates who can demonstrate that they understand and can work within that visual world.
- Intentional AI usage. We also look at how candidates use AI. For some clients, strong AI-assisted workflows are a major advantage. For others, handcrafted work and traditional production skills matter more. We assess against what the role actually requires.
Where AI fits in — nowhere
Portfolios are reviewed manually. Visual taste, context and creative judgment are difficult to reduce to a score.
Step 02
The 10-minute alignment call.
Once a candidate passes the initial screening, we have a short 10-minute call before asking them to complete a take-home assessment.
We introduced this step for a simple reason: we don’t want candidates spending 90 minutes on a test before either side knows whether they actually want to work together.
Candidates can make a CV sound impressive, sometimes stretching the line between what they’ve done and how it’s presented, but a short conversation helps us spot the red flags that a polished CV tries to hide.
A two-way check
A quick call gives candidates a realistic sense of the role, client, expectations and working environment, while allowing us to gauge their genuine interest, English fluency, communication style and whether the opportunity actually makes sense for them.
Instant clarification
CVs and portfolios rarely tell the whole story.
If someone lists video editing experience but their portfolio is mostly graphic design, we’ll ask about it. If they have a two-month notice period, we’ll find out whether there is flexibility.
We would rather ask a question than reject a potentially excellent candidate based on incomplete information.
Where AI fits in — nowhere
This is deliberately human. There is no automated video score or AI-generated assessment of personality. A real person speaks to every candidate at this stage.
Step 03
Role-specific take-home assessments.
This is where we move from what someone says they can do to what they can actually do.
Our assessments are designed around realistic work rather than abstract questions. We want to see how someone thinks, prioritises, communicates and executes when given a problem to solve.
We also cap most assessments at 60–90 minutes. Good candidates are often already employed, and we don’t believe a hiring process should require hours of free labour.
Executive assistants: the chaos simulation
What we test: attention to detail, prioritisation, crisis management, judgment, communication and knowing when to escalate.
How we test it: candidates receive a fake inbox with 12 emails, a messy calendar, a travel booking tool and a chaotic message from a founder.
There are deliberate traps. An expiring passport might be buried inside a flight confirmation. A low-priority email might be demanding an immediate response while a genuinely important issue sits quietly in the inbox.
There isn’t one perfect answer. We want to see what the candidate notices, what they prioritise and how they make decisions.
Marketing & growth: real-world analysis
What we test: critical thinking, brand awareness, tool fluency, strategic thinking and execution.
The exact exercise varies by specialisation, but we anchor it to a real, active Instagram page from an industry-adjacent company rather than asking candidates to perform unpaid work on a client’s live account.
- Analytical and strategic roles. Candidates might audit the account, identify what is working, highlight opportunities and explain why.
- Visual and graphic design roles. We might give them a short founder-style brief and ask them to create two graphics: one that works within the existing visual identity and another that pushes the creative direction further.
This lets us see both restraint and creativity.
Software engineering & technical roles
What we test: codebase navigation, debugging, async communication, edge-case thinking and practical engineering judgment.
Instead of abstract algorithm questions, candidates typically receive a lightweight repository containing an existing bug or a small enhancement request. We look at:
- Code quality & architecture. How cleanly they approach the problem and structure the solution.
- Async documentation. How clearly they explain setup, trade-offs and technical decisions.
- AI utilisation. How effectively they use modern AI tools to write, test or refactor code while still maintaining security, performance and engineering standards.
Where AI fits in
We actively encourage candidates to use AI during assessments. That’s the reality of modern work, and knowing how to use these tools well is increasingly part of the job.
We also use AI on our side to help build assessments, check benchmark conditions and speed up initial grading.
But the final score is always reviewed by a human. AI can tell us whether a particular condition was met. It is much less reliable at understanding a clever workaround, a subtle communication choice or why an engineer made a particular architectural trade-off.
For highly technical roles, we also bring in senior developer advisors to review code, architecture and technical decisions.
Our golden rule: keep improving the tests
Building a test that looks clever on paper is easy. Building one that actually predicts job performance takes constant iteration.
We adjust our assessments based on candidate feedback and actual hiring outcomes. If a test starts feeling like a performative exercise rather than a reflection of the work, we rewrite it.
Step 04
The deep-dive final interview.
The final interview is where we slow down.
At this point, we’ve already established that the candidate has the baseline skills and can execute the work. Now we want to understand how they operate over the long term.
What we focus on
- Proactivity & initiative. We explore situations where candidates had to act with incomplete information, anticipate problems or unblock themselves without constant direction.
- Career journey. We discuss career moves, employment gaps and changes in direction to understand the context behind someone’s experience rather than making assumptions from a CV.
- Commitment & bandwidth. If someone has freelance work or other commitments, we make sure they genuinely have the time and focus required for the role.
- Cross-border working. We explore previous experience working directly with founders and teams across Europe, the UK and the US, including how they handle different communication styles and expectations.
- Strengths & blind spots. We ask what types of work candidates genuinely enjoy, where they feel strongest and where they need support. This helps us understand where someone is most likely to thrive.
- Curiosity. We like hearing about what candidates build, learn or explore outside their core role. An engineer experimenting with AI workflows or a marketer learning design tells us something about their curiosity and willingness to keep developing.
- Practical expectations. We discuss salary, contract terms, working hours and other expectations openly. There should be no surprises once someone joins.
Where AI fits in — nowhere
The final interview is a human conversation. We use everything we’ve learned throughout the process to guide the discussion, but the final assessment comes from our team.
Putting it all together: why this framework works.
A good hiring process shouldn’t just find people who look qualified on paper. It should reduce the risk of discovering six months later that someone wasn’t suited to the way your team actually works.
Our framework is designed around three principles:
1. Technology for speed, humans for judgment
We use AI where it genuinely saves time — processing information, organising data, building assessments and checking standardised outputs. We don’t use it to make the important decisions about people.
2. Test the work, not just the CV
Candidates don’t reach our clients based solely on what they’ve written about themselves. We look at their work, speak to them directly and give them realistic problems to solve. By the time someone reaches the final stage, we’ve seen much more than their CV.
3. Alignment before placement
The goal isn’t simply to fill a position. We want someone who can perform the work, communicate effectively, work independently and genuinely enjoy the environment they’re joining.
That’s better for the candidate, better for the client and ultimately better for building a team that lasts.
Frequently asked questions.
Why do you allow candidates to use AI during take-home assessments?
Because that’s how modern work increasingly happens. We want to know whether someone can use AI effectively while still exercising judgment, reviewing outputs and taking responsibility for the final result.
How long does the remote hiring process take?
Our full vetting process typically takes 2–3 weeks from application to placement. We use technology to reduce unnecessary delays while keeping the important human touchpoints in the process.
How long do take-home assessments take?
Most practical assessments are capped at 60–90 minutes. We want enough time to see how someone works without turning the hiring process into an unpaid project.
Why do you conduct a 10-minute call before the technical test?
Because both sides should have a basic understanding of the opportunity before investing significant time. A short conversation lets us clarify expectations, answer questions and make sure there is genuine interest before asking a candidate to complete a longer assessment.
How do you evaluate communication and other non-technical qualities?
Through direct human interaction. We use the initial call and final interview to assess communication, working style, initiative, adaptability and long-term alignment. These qualities are difficult to understand from a CV or automated score alone.