Ask These Five Questions Before Taking a Job at an AI Startup (A Job Seeker’s Due Diligence)

Before you say yes: a job seeker’s urgent checklist for AI startups in 2026

Hesitant about taking a role at an AI startup? You're not alone. Between rapid pivots, funding volatility, and new regulations that reshaped the industry in late 2025 and early 2026, job safety matters more than ever. If you need income stability, clear career paths, and a low-risk work environment, this guide gives you five concrete questions to ask in interviews — and the exact research steps to verify the answers.

Why this matters now (short version)

After a turbulent 2024–2025 cycle of heavy AI hiring, 2026 has seen consolidation, higher regulatory scrutiny (US and EU), and a wave of startups proving that tech excitement doesn't automatically equal long-term stability. Q1 2026 market notes and company resets — eliminating debt while acquiring assets but still facing falling revenue and government-concentration risk — are real-world examples: upside can exist, but so can hidden risk. That’s why you need a focused due-diligence script before accepting any offer.

The five questions to ask (and why each one matters)

Ask these five questions during interviews with hiring managers, founders, or HR. For each question below you’ll get: what to ask verbatim, what the answer should look like, follow-ups, red flags, and how to independently verify claims.

1) What is the company’s current debt and covenant status, and how does it affect runway?

What to ask: “Can you outline current debt obligations, any lender covenants, and how those affect hiring or product plans?”

Why it matters: Debt and covenants can limit flexibility. A company that just eliminated debt — like BigBear.ai did in its recent reset — may be stronger. But refinancing risk or restrictive covenants can force layoffs or freezes even if the product is promising.

• Good answer: No or manageable debt; clear refinancing or cash strategy; runway projection that supports hiring.
• Bad answer / red flag: Evasiveness, “we’ll handle it,” high-interest bridge loans, or covenants that require rapid revenue milestones.

Follow-ups: Ask for runway in months, burn rate trends, and whether fundraising is ongoing. You can phrase it softer: “What would need to change for the company to pause hiring?”

How to verify: If public, check SEC filings/earnings calls (EDGAR, investor deck). For private companies, search Crunchbase/PitchBook for funding rounds, use LinkedIn headcount trends, and ask to see a high-level finance slide if comfortable. For government contractors, check recent contract awards on SAM.gov or USASpending.gov for cash flow signals.

2) How concentrated is revenue by customer or contract type?

What to ask: “What percentage of revenue comes from your top three customers and which sectors (government, enterprise, single vertical) are you most dependent on?”

Why it matters: High customer concentration — especially single large government contracts — is a failure vector. BigBear.ai’s case highlighted government concentration risk: winning a FedRAMP-approved platform is valuable, but if most revenue comes from one agency, losing that contract can be catastrophic.

• Good answer: Diversified customer base, multiple contract types (SaaS, services), and an active pipeline across industries.
• Bad answer / red flag: >40-50% revenue from one client or from a single government vertical, high contract churn risk.

Follow-ups: Ask about contract length, renewal rates, and termination clauses. “What would happen to headcount or roadmap if Client X did not renew next year?”

How to verify: For public firms, read the 10-K/10-Q and investor presentations. For private firms, check press releases for major deals, SAM.gov for federal contracts, customer case studies, and LinkedIn job postings (hiring patterns often reveal revenue focus).

3) What are the revenue trends and unit economics (growth, churn, CAC/LTV)?

What to ask: “Can you share high-level trends for ARR/MMR growth, churn rate, and CAC-to-LTV? How have these trended in the past 12–18 months?”

Why it matters: Revenue trend lines and unit economics tell you whether growth is sustainable. Falling revenue or worsening CAC/LTV ratios are the most common precursors to headcount reductions in 2024–2026.

• Good answer: Demonstrable ARR or MRR growth, improving retention, and reasonable CAC-to-LTV ratios with a clear route to profitability or a strategic path to scale.
• Bad answer / red flag: Flat or declining revenue, no sightline to improved unit economics, or heavy reliance on one-time implementation fees vs. recurring revenue.

Follow-ups: Ask to quantify churn, customer lifetime, and sales cycle. “How long on average is a sales cycle, and what percent of revenue is recurring vs. one-time?”

How to verify: For public companies, check quarterly revenue disclosures and management commentary. For startups, look for recurring revenue language in press releases, customer logos, and whether pricing is principally subscription-based. Use third-party analyses (Gartner, Forrester, industry newsletters) for sector context.

4) What platform and compliance certifications do you hold, and who owns the IP and model governance?

What to ask: “Which certifications and compliance frameworks does your platform have (FedRAMP, SOC 2, ISO 27001, NIST RMF alignment), and who owns the IP — the company or customers?”

Why it matters: In 2026, certifications and model-governance frameworks are table stakes for many government and enterprise AI deals. A company may tout a FedRAMP-approved platform (a clear signal of government readiness), but you must understand the scope, level (FedRAMP Low/Moderate/High), and whether this platform status covers the products you’d work on.

• Good answer: Clear certification list, public proof (FedRAMP marketplace entry, SOC 2 reports), and well-defined IP ownership and model governance policies including version control, red-team testing, and incident response.
• Bad answer / red flag: Vague certification claims, “in progress” without timelines, unclear IP terms, or no formal model governance (a risk in regulated sectors).

Follow-ups: “Can you point me to the public certification entry or a redacted attestation? How are model changes governed and audited?”

How to verify: Look up FedRAMP Marketplace entries, request SOC 2 or ISO certificates, and search for compliance attestations. For model governance, review product documentation, whitepapers, or ask for a summary of the model lifecycle process. In the U.S., FedRAMP and NIST references are strong signals of maturity.

5) What’s the hiring plan if revenue misses or if a large contract ends — and what safety nets exist for employees?

What to ask: “If revenue falls short or a major contract is lost, what are the contingency plans for employees (hiring freezes, severance policies, redeployment, accelerated fundraising)?”

Why it matters: You’re not just hiring into a role — you’re buying employment stability. Startups that plan for downturns (cross-training, transparent severance policies, retention bonuses tied to KPIs) protect staff better than those that act ad-hoc.

• Good answer: Clear contingency plans, cross-training policies, transparent communication cadence, and examples of past handling of downturns.
• Bad answer / red flag: No plan, “we’ll figure it out,” or pay structure heavy on equity with little protection for cash pay.

Follow-ups: Ask about historical examples of realignment and how the company supported staff. “Have you ever restructured? If so, what was the process and support offered?”

How to verify: Check Glassdoor for layoff/restructuring notes, LinkedIn for sudden headcount dips, and ask to speak with a hiring manager or recent joiner who can attest to transparency in practice.

Practical pre-interview research checklist

Use this checklist to verify answers before you ask the hiring team — the more prepared you are, the better the conversation and the less rope they have to be vague.

1. Public filings and investor decks (EDGAR for public companies; investor presentations on the company site).
2. Crunchbase/PitchBook for funding rounds, valuations, and investor names (use investor updates to gauge support).
3. SAM.gov and USASpending.gov for federal contract awards (search contractor name or DUNS/CAGE codes).
4. FedRAMP Marketplace and certification registries (SOC 2, ISO logos on the site; request attestation if needed).
5. LinkedIn headcount and hiring trends (look at job postings by function and geographic slowdowns).
6. Glassdoor/Blind for employee commentary on layoffs, management, and communication style.
7. Product documentation, white papers, and GitHub (if open source) to test technical maturity.
8. News coverage (industry newsletters, TechCrunch, The Information) for any recent pivots or funding news in late 2025–early 2026.

How to ask — sample scripts you can use in interviews

Keep questions direct but collaborative. You want to assess risk without sounding hostile. Here are three scripts depending on stage and interviewer:

• For the recruiter or hiring manager (early-stage): “I’m excited about this role. To make the best decision, could you share whether the company has any outstanding debt or covenants and how that might affect hiring plans?”
• For the founder or CFO (later stage): “How concentrated is revenue among top clients and what contingency plans do you have if a major contract isn’t renewed?”
• For the CTO or product lead: “Can you point me to the platform’s compliance certifications and describe your model-governance processes for deployments?”

“A company can sound very promising — great tech, smart people — but single-contract dependency or unclear certification scope can quickly make good work dangerous for employees. Ask directly.” — Senior product leader, 2026

Red flags that should make you pause

• Evasive answers to direct questions about debt, runway, or customer concentration.
• Heavy emphasis on equity as compensation without clear cash-pay stability or severance policy.
• Certifications claimed but not verifiable on public registries (FedRAMP, SOC 2, ISO).
• No stated contingency plan for contract loss or revenue dips.
• Recent mass layoffs or rapid headcount swings on LinkedIn with no transparent explanation.

When the data conflicts with what they say

If your independent research contradicts answers you receive, be frank but tactful. Example: “I noticed on SAM.gov a large award in 2024 that seems to represent a significant portion of revenue. How has the company diversified since then?” If the team can explain changes with proof (new logos, product expansion), you’re in a better spot. If they dodge, that’s a sign to keep options open.

Putting this into context: BigBear.ai and 2026 market realities

BigBear.ai’s recent reset — eliminating debt and bringing a FedRAMP-approved platform into the fold — shows both sides of the coin. FedRAMP status can unlock large government revenue, but falling revenue and contract concentration can still leave the company exposed. In 2026, many AI startups face similar trade-offs: compliance maturity unlocks contracts but also raises dependency on a specific customer type. Your job is to spot whether the company has balanced that risk.

Actionable takeaways — a one-page checklist to use before saying yes

• Ask the five questions: debt, concentration, revenue trends, certifications/IP, contingency plans.
• Verify claims with public registries (EDGAR, FedRAMP, SAM.gov), Crunchbase, and LinkedIn.
• Prefer firms with diversified revenue, improving unit economics, and verifiable certifications.
• Negotiate for protections: a longer salary guarantee, clear severance, or staged equity vesting if risk is high.
• Ask for written confirmations where appropriate (e.g., role security period or hiring plan tied to funding milestones).

Final thoughts — balancing opportunity and safety

AI startups still offer fast career growth, impactful product work, and upside. But 2026’s market reality demands smarter due diligence. Use the five questions above as a default script — verify answers independently, look for public proof, and insist on transparency. That way you can join an AI startup with realistic expectations and a plan for your career safety.

Next steps (call to action)

If you’re interviewing with an AI startup now, print the five-question checklist, run the research steps, and use the sample scripts in your next conversation. Want a ready-made one-page PDF checklist and email templates to ask recruiters these questions? Visit jobless.cloud/checklists to download templates, interview scripts, and a customizable due-diligence tracker.

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