AI Native Software Engineer

## Why Indexnine?

We believe that great people build great products. That’s why we’ve created an environment where talent thrives.

### Health & Wellness

Comprehensive health, dental, and vision insurance, plus wellness programs and mental health support.

### Work-Life Balance

Flexible working hours, remote work options, and unlimited PTO to maintain a healthy work-life balance.

### Professional Growth

Continuous learning opportunities, conference attendance, and skill development programs.

### Collaborative Culture

Work with talented, passionate people in an inclusive and supportive environment.

### Competitive Compensation

Competitive salaries, equity participation, and performance-based bonuses.

### Innovation & Impact

Innovation-driven projects with new technologies, open-source contributions, and real-world impact.

We are looking for AI-native Engineers who can build applications using AI and full-stack
technologies, leveraging modern tools like Copilots, Agents, and LLMs to deliver production-ready solutions.

You will work in an environment where:

• Code is co-created with AI
• Specs are translated into working systems using AI tools
• Speed, quality, and product thinking matter equally

### Responsibilities

• Build and scale AI-native applications from prototype to production
• Translate PRDs into working systems using AI-assisted development
• Design and develop full-stack solutions (frontend, backend, APIs)
• Integrate LLMs, RAG pipelines, and embeddings into real-world use cases
• Leverage AI tools (Copilot, Cursor, Claude) to accelerate development
• Optimize performance, cost, and reliability

### Requirements

Programming & Backend

• Python (preferred), Node.js / JavaScript
• Experience building APIs (REST/GraphQL)

Frontend

• React or similar frameworks
• Basic UI/API integration understanding

AI / LLMs

• LLM APIs (OpenAI, Anthropic)
• Prompt engineering basics
• RAG and embeddings exposure
• Interaction with agents & agentic workflow (Nice to have)

Tools

• Copilot, Cursor, Claude
• LangChain, LlamaIndex (Nice to have)

Cloud

• AWS / GCP / Azure basics
• Deployment and debugging awareness

Core Skills

• Product thinking and user-focused development
• AI-assisted development workflow
• Strong full-stack fundamentals
• LLM integration and debugging
• AI workflows and automation understanding
• Performance, cost, and reliability awareness

### Experience Bands

1–3 Years

• Use AI tools for development and debugging
• Basic prompt engineering and output evaluation
• Build small AI features and API integrations

3–6 Years

• Build end-to-end features independently
• Work on RAG and AI workflows in production
• Improve system performance and reliability

6–8 Years

• Design AI systems and architectures
• Handle ambiguity and lead technical decisions
• Mentor team and define best practices

### Nice to Have

• Experience working with agent-based systems and agentic workflows
• Built copilots, internal tools, or automation-driven applications using AI
• Exposure to fast-paced product or startup environments
• Experience in building benchmarking frameworks for LLMs (A/B testing, offline and end-to-end evaluation) to measure quality, latency, and cost trade-offs
• Understanding of LLM proxy patterns including routing, caching, safety filters, and rate limiting across multiple models/vendors

### Qualifications

• B.E / B.Tech / M.Tech / MCA