AI Engineer, Agents & Intelligence

Scalio; Bengaluru; On-site; INR 3,000,000 - 6,000,000; Full time

Benefits offered by this job

Equity

Job summary

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.

We’re looking for an AI Engineer to build the intelligence layer behind it: agents that understand a business, remember context, use tools, make decisions and execute marketing workflows.

Qualifications

• 2–5 years engineering experience; exceptional candidates outside range accepted.
• Hands-on experience building and shipping LLM/AI systems.
• Experience with RAG, embeddings, vector databases or search.
• Experience building agents, tool-calling systems or agentic workflows.
• Understanding memory, context management and stateful AI systems.
• Strong backend fundamentals: APIs, databases, async systems and production infrastructure.
• Ability to take an ambiguous problem from idea → architecture → production.
• Strong curiosity and ability to quickly adopt new AI models and techniques.
• LangGraph / LlamaIndex / OpenAI Agents SDK / PydanticAI or similar.
• LLM evaluation and observability.
• Docker / cloud infrastructure.
• Open-source contributions or impressive personal AI projects.
• Heavy use of Claude Code, Codex, Cursor or similar AI coding tools.

Responsibilities

• Build AI agents and multi-step workflows.
• Long-term memory for businesses and users.
• RAG, embeddings and vector search implementations.
• Tool calling and API orchestration development.
• Context engineering and model routing.
• AI evaluation, tracing and reliability work.
• Production LLM systems optimized for quality, latency and cost.

Skills

Software engineering fundamentals

2–5 years engineering experience

Hands-on AI systems

RAG and embeddings

Agentic workflows

Memory/context management

Backend fundamentals

Production infrastructure

Ambiguity to production

Curiosity to adopt new models

LangGraph / LlamaIndex / OpenAI Agents

LLM evaluation & observability

Docker / cloud infra

Open-source contributions

AI coding tools (Claude etc)

Tools

LangGraph

LlamaIndex

OpenAI Agents SDK

PydanticAI

Docker

Job description

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.

Compensation: ₹30–60 LPA annual fixed salary plus equity. Equity terms discussed during the hiring process.

We’re looking for an AI Engineer to build the intelligence layer behind it: agents that understand a business, remember context, use tools, make decisions and execute marketing workflows.

This is not a prompt-engineering role and not an ML research role.

You’ll work on:

• AI agents and multi-step workflows
• Long-term memory for businesses and users
• RAG, retrieval, embeddings and vector search
• Tool/function calling and API orchestration
• Context engineering and model routing
• AI evaluation, tracing and reliability
• Production LLM systems optimized for quality, latency and cost

What we’re looking for

• Strong software engineering fundamentals
• Approximately 2–5 years of engineering experience, though exceptional candidates can be outside this range
• Hands‑on experience building and shipping LLM/AI systems
• Experience with RAG, embeddings, vector databases or search
• Experience building agents, tool‑calling systems or agentic workflows
• Understanding of memory, context management and stateful AI systems
• Strong backend fundamentals: APIs, databases, async systems and production infrastructure
• Ability to take an ambiguous problem from idea → architecture → production
• Strong curiosity and ability to quickly adopt new AI models and techniques
• LangGraph / LlamaIndex / OpenAI Agents SDK / PydanticAI or similar
• LLM evaluation and observability
• Docker / cloud infrastructure
• Open‑source contributions or impressive personal AI projects
• Heavy use of Claude Code, Codex, Cursor or similar AI coding tools

What we care about less

• Having worked at a famous company
• Knowing every AI framework
• Exact number of years of experience

We care much more about what you’ve actually built and shipped.

If you’ve built something technically impressive, tell us about it.

Required written questions

• 1. What is the most technically complex AI/LLM system you have personally built and shipped to production? Briefly explain what you built, your specific contribution, scale/users, and one difficult problem you solved.
• 2. Share a link to something you have built: GitHub, demo, product, technical article, paper, open‑source project, etc. What part did you personally build?
• 3. Suppose an AI agent needs to remember a business's important information across 6 months of conversations and actions. How would you design its memory system? Briefly describe what you would store, where you would store it, and how you would retrieve/update it.
• 4. Describe an AI agent or agentic workflow you've built. What tools could it use, how did you manage state/context, and what happened when the model made a wrong decision?
• 5. How have you evaluated whether an LLM/RAG/agent system actually improved? Give one example of a metric, test set, or evaluation process you have used.
• 6. You inherit a production RAG agent with 90% retrieval recall but poor answer quality. What would you investigate first?

availability to work full-time on-site in Bengaluru

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