AI-Native Software Engineer

Vibehackers; Chennai District; On-site; INR 3,000,000 - 5,400,000; Full time

Job summary

Vibehackers is seeking a Senior AI-Native Software Engineer to design and build production-grade agentic systems, RAG pipelines, and multi-agent workflows. You will own architecture, APIs, data models, and CI/CD in an AI-native environment.

You will lead HITL validation, audit AI-generated code, and collaborate across backend, frontend, and cloud services to deliver robust AI-driven applications. Open positions: 5; Interview slots: immediate scheduling.

Qualifications

• 6–10 years of experience in software engineering or AI-native development.

Responsibilities

• Design system architecture, APIs, and data models for AI-driven applications.

Skills

System design

Data modeling

Data structures

Algorithms

Distributed systems

Prompt engineering

Context engineering

AI-generated code review

CI/CD

Automated testing

Asynchronous programming

Communication

MLOps

Tools

Cursor

Windsurf

GitHub Copilot

Claude Code

Aider

Codex CLI

Job description

Heavy AI-native focus: building agentic systems, RAG, and using AI-assistant tools like Cursor and GitHub Copilot—explicitly about vibe coding with AI tooling.

About the Role

Senior AI-Native Software Engineer role to design and build production-grade agentic systems, RAG pipelines, and multi-agent workflows. The position focuses on system architecture, APIs, backend/frontend development, HITL validation, CI/CD, and auditing AI-generated code in an AI-native development environment.

Job Description

Role

Senior AI-Native Software Engineer responsible for designing and building production-grade AI-driven applications and agentic systems. The role covers architecture, APIs, data models, RAG pipelines, multi-agent workflows, HITL validation, and full SDLC ownership including CI/CD and automated testing.

Key Responsibilities

• Design system architecture, APIs, and data models for AI-driven applications.
• Build and manage production-grade agentic systems and multi-agent workflows.
• Design and implement Retrieval-Augmented Generation (RAG) pipelines.
• Define AI specifications, prompts, context rules, and validation strategies.
• Review, test, debug, and audit AI-generated code.
• Build backend services, APIs, and frontend components where required.
• Design Human-in-the-Loop (HITL) validation processes for critical workflows.
• Work across the complete SDLC, including CI/CD and automated testing.

Mandatory Requirements

• 6–10 years of experience.
• Strong computer science fundamentals: data structures, algorithms, system design, distributed systems.
• Hands-on experience in AI-generated code review and code auditing.
• Production experience with agentic AI frameworks (e.g., LangGraph, LangChain, AutoGen).
• Strong experience with RAG architecture, vector databases, embeddings, hybrid search, and retrieval evaluation.
• Expertise with AI-native development tools (e.g., Cursor, Windsurf, GitHub Copilot, Claude Code, Aider, Codex CLI).
• Prompt engineering and context engineering skills.
• Experience with cloud platforms (Azure, AWS, GCP), REST APIs, asynchronous programming, CI/CD and automated testing.
• Valid passport and UAN (mandatory).

Preferred Skills

• Experience with SAP SuccessFactors, Workday, Oracle HCM, Concur, or similar enterprise platforms.
• MLOps, model training/fine-tuning, or evaluation frameworks.
• GitHub or portfolio showcasing AI-native or agentic development projects.

Logistics

• Open positions: 5
• Interview slots available: 15 (immediate scheduling)

Skills

System Design APIs Data Modeling Data Structures Algorithms Distributed Systems Prompt Engineering Context Engineering AI-generated Code Review Code Auditing Debugging Human-in-the-Loop (HITL) CI/CD Automated Testing Asynchronous Programming Communication RAG Architecture Vector Databases Embeddings Retrieval Evaluation MLOps