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SITEFY
We're Hiring · AI Engineering

AI Engineer – Agents & Automation

Build AI systems that do real work. Design, integrate and deploy agents, LLM applications and intelligent workflows that solve measurable business problems.

📍 Bangalore 🤖 AI Agents ⚡ Automation 🔌 APIs 💻 Engineering
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DepartmentAI & Engineering
LocationBangalore
EmploymentFull-Time
Primary OutcomeProduction AI Systems
Your Mission

Take AI from impressive demo to reliable production system.

Sitefy is interested in AI that produces business outcomes—not agents that look good only in demos. You'll build systems that can reason, use tools, interact with business software and reliably complete useful work.

01

Understand

Translate a business workflow or bottleneck into a clear AI engineering problem.

02

Build

Develop agents, LLM workflows, integrations and supporting backend systems.

03

Ship

Deploy, evaluate, monitor and improve systems until they are reliable in production.

What You'll Build

Practical AI for real business workflows.

AI agents that interact with external tools and APIs.
Business-process automation powered by LLMs.
Lead-generation and sales-assistance agents.
CRM and operational AI workflows.
Content and marketing automation systems.
Knowledge and retrieval systems where appropriate.
Structured extraction and document-processing workflows.
Internal AI copilots and productivity systems.
What You'll Own

Engineering beyond the prompt.

Build production-oriented LLM applications.
Design agentic workflows and tool integrations.
Integrate third-party APIs and business systems.
Implement retrieval or knowledge systems when they genuinely improve the solution.
Create structured automation pipelines around AI models.
Design prompts, schemas and tool interfaces.
Evaluate output quality systematically.
Handle failures, retries and edge cases.
Optimize latency and model/API cost.
Implement appropriate logging and monitoring.
Work with application developers on production integration.
Document architecture and deployment clearly.
WHO-Style Scorecard

What winning looks like.

We care less about how many AI frameworks you can name and more about whether you can repeatedly turn a requirement into a reliable, measurable production system.

Fast Requirement → working prototype cycle
↑ Deployments Useful AI workflows shipped into production
Reliable Low failure rates and strong handling of edge cases
High Quality Evaluated output accuracy and usefulness
Efficient Reasonable model, token, API and infrastructure costs
Maintainable Clean code, architecture and documentation
Technical Competencies

What we're looking for.

Python / Backend Development LLM APIs Tool Calling Agentic Workflows REST APIs Webhooks RAG Fundamentals Databases Structured Outputs Evaluation Prompt Engineering Git Debugging Cloud Deployment
Who Should Apply?

You may be a strong fit if...

You can write production-quality code, not just prompts.
You understand APIs, backend logic and data flow.
You can explain when an agent is useful—and when normal software is better.
You think about reliability, security and edge cases.
You test AI output rather than trusting a few good examples.
You care about model and infrastructure cost.
You can learn new models and tools without becoming dependent on one framework.
You want to ship systems used by real businesses.
Practical Audition

Show us how you solve an AI problem.

AI Engineering Challenge

Design and prototype a small business agent.

We'll give you a realistic business workflow—for example, an incoming lead that needs to be understood, qualified, enriched, entered into CRM and assigned a next action.

  • Explain where AI should and shouldn't be used.
  • Design the architecture.
  • Choose the model/tool approach.
  • Build or outline the core workflow.
  • Explain how you would evaluate output quality.
  • Handle failures and edge cases.
  • Explain deployment and monitoring.
  • Estimate the major cost drivers.
Select

Our hiring process.

Step 01
Application

Share projects, GitHub or examples of AI systems you've actually built.

Step 02
Technical Screen

Discuss architecture, APIs, LLMs, debugging and your strongest engineering work.

Step 03
Practical Challenge

Design or build a small AI-agent workflow around a realistic business problem.

Step 04
WHO Interview

Walk through previous roles, outcomes, failures, managers and reasons for leaving.

Step 05
Reference & Offer

Final validation where applicable followed by expectations and offer.

Why Sitefy?

Don't just experiment with AI. Ship it.

You'll work on AI tied directly to business operations, revenue, customer acquisition and software products rather than isolated demos.

BuildShip real AI systems.
OwnershipWork from problem through deployment.
VarietySolve different business workflows.
ImpactSee people use what you build.
GrowthDevelop toward AI architecture and engineering leadership.

Can you make AI actually do the work?

Join Sitefy's Bangalore AI team and build agents and intelligent automation that move from prototype to production.

Apply for AI Engineer →
Apply Now →
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