AI Engineer, Agents & Intelligence

About the Role

Scalio is assembling a specialized AI marketing team aimed at empowering millions of small businesses. The company seeks individuals who take initiative, plan thoughtfully, and consistently deliver measurable results to customers.

This role as an AI Engineer focuses on creating the intelligence layer underpinning AI agents that comprehend business contexts, retain information, use tools, make decisions, and automate marketing workflows. It is distinct from prompt engineering or machine learning research positions.

Key Responsibilities

• Develop AI agents capable of executing multi-step workflows.
• Implement systems for long-term memory management relating to businesses and users.
• Work with retrieval-augmented generation (RAG), embeddings, and vector search technologies.
• Build tool and function calling integrations and orchestrate APIs.
• Manage context engineering and model routing for AI systems.
• Focus on AI system evaluation, reliability tracing, and quality assurance.
• Design and deploy production-scale large language model (LLM) infrastructures optimized for performance, latency, and cost.

Candidate Profile

• Strong foundation in software engineering principles.
• Proficient in Python programming.
• Typically 2 to 5 years of relevant engineering experience, though outstanding candidates outside this bracket are welcome.
• Demonstrated experience building and launching LLM or AI-driven systems.
• Familiarity with RAG, embeddings, vector databases, or related search technologies.
• Experience developing agents, tool-calling mechanisms, or agentic workflow systems.
• Knowledge of AI memory handling, context management, and stateful architectures.
• Solid backend skills including API design, databases, asynchronous systems, and production infrastructure.
• Ability to transform ambiguous concepts into scalable architectural and production-ready solutions.
• Curiosity and agility to adopt emerging AI models and methodologies swiftly.

Preferred Skills

• Experience with LangGraph, LlamaIndex, OpenAI Agents SDK, PydanticAI, or similar frameworks.
• MCP certification.
• Proficiency in hybrid search or reranking techniques.
• Competence in LLM evaluation, monitoring, and observability.
• Knowledge of multimodal AI systems.
• Hands-on experience with Redis, PostgreSQL, and pgvector.
• Use of Docker and cloud infrastructure technologies.
• Contributions to open-source projects or notable personal AI initiatives.
• Extensive use of AI coding assistants like Claude Code, Codex, or Cursor.

What We Value Less

• Academic degrees.
• Performance on algorithmic challenges like LeetCode.
• Employment at well-known companies.
• Familiarity with all AI frameworks.
• Precise length of experience.

Application Requirements

Applicants must provide detailed answers to the following written questions as part of the application process:

1. Describe the most complex AI/LLM system you have developed and deployed to production, including your role, scale, and a challenging problem solved.
2. Share a link to a project, demo, technical article, or open-source work you contributed to and clarify your personal involvement.
3. Explain the design of a memory system for an AI agent retaining business-critical information across six months of interactions.
4. Detail an AI agent or agentic workflow you have built, its tools, context handling, and response to incorrect model decisions.
5. Describe how you measured improvement in an LLM, RAG, or agent system, citing specific metrics or evaluation methods.
6. Discuss how you would assess a production RAG agent with strong recall but poor output quality.

Applicants should submit their name, email, phone (with country code), CV/resume link, relevant experience, Bengaluru on-site availability, and responses to all questions. Clear documentation of personal contributions with concrete examples is essential. Confidential employer or client data should be omitted.

Compensation and Location

The position is based on-site in Bengaluru, India, with an annual fixed salary range of ₹30,00,000 to ₹60,00,000 plus equity. Equity terms will be discussed during the interview process.