Scalio — Senior Applied AI Engineer — Application

Senior Applied AI Engineer

Full-time | Bengaluru, India | On-site

Compensation: ₹40–70 LPA annual fixed salary

Scalio is building an AI marketing team for millions of small businesses. We’re looking for people who take ownership, build thoughtfully, and turn their work into measurable customer outcomes.

The role

Own customer-facing AI products from experimentation through production. Combine product judgment, full-stack engineering, and applied AI expertise to build marketing experiences that reliably help small businesses complete useful work.

What you’ll work on

• End-to-end AI features spanning interfaces, APIs, and agent workflows.

• Tool use, structured outputs, retrieval, and failure recovery.

• Evaluation datasets, user feedback loops, and systematic improvements.

• Quality, latency, cost, and observability in production.

• Translating customer problems into useful product behavior.

What we’re looking for

• 4+ years of software engineering experience.

• Hands-on experience shipping production LLM products.

• Ability to own frontend, backend, APIs, databases, and integrations.

• Strong product intuition and comfort investigating real user behavior.

• Experience taking complex projects from prototype to dependable product.

Strong plus

Multimodal systems, long-running agents, mentoring engineers, customer discovery, and AI evaluation infrastructure.

Application — all six answers required

Complete the application fields below, including your phone number with country code, résumé/CV link and all six answers. Include relevant links and clearly explain your personal contribution. Use concrete examples; generic answers will not stand out. Please omit confidential employer or customer information.

We care more about demonstrated work and results than degrees, company names, or familiarity with every tool.

Name *

Email *

Phone number (including country code) *

Résumé/CV link *

Relevant software engineering experience in years *

Are you willing to work full-time, on-site in Bengaluru? *

Yes

1. Describe a customer-facing AI product you personally shipped. What user problem did it solve, what did you build, and what happened after launch? *

2. Share a working product, demo, repository, or technical write-up. Identify your contribution. *

3. How would you turn a promising agent prototype into a dependable product? Explain your priorities for evaluation, UX, failure handling, latency, and cost. *

4. Describe an improvement driven by user behavior or feedback. What changed, and how did you measure success? *

5. Give an example where you improved AI quality without simply switching to a larger model. *

6. An agent produces technically valid results, but users abandon the workflow. What would you investigate and test first? *

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