Software Developer _AI Native Developer

AMPITY INFOTECH

Job Description

Software Developer AI-Native Developer

Full-Stack Development | AI-Assisted Engineering | LLM/Agent Features

Location: Remote (India)

Employment Type: Full-time

Team: Client Delivery Engineering

Reports To: Tech Lead / Engagement Lead

About Ampity Infotech

Ampity Infotech is a cloud and DevOps engineering firm that helps growing companies design, build, and operate production-grade software and infrastructure on AWS. We work directly with client engineering and leadership teams, and we build with AI as a core part of how we work, not as a side experiment.

Role Summary

As a Software Developer on Ampity's delivery team, you will build full-stack features for client products and use AI coding tools (Claude Code, GitHub Copilot, Cursor, or similar) as a default part of your daily workflow, not an occasional shortcut. Beyond writing AI-assisted code, you will also help build AI-powered capabilities into client products themselves: LLM integrations, retrieval-augmented generation, and agentic workflows. You are expected to move fast with AI, and to have the judgment to verify, test, and take ownership of everything that reaches production.

What You'll Own

• Design and build features across the stack (frontend, backend, APIs, data layer) for client products, using frameworks appropriate to each engagement.
• Use AI-assisted development tools as a default part of the workflow: decomposing tasks, generating and reviewing code, and accelerating delivery.
• Rigorously test, review, and fact-check AI-generated code before it ships; catch plausible-but-wrong suggestions rather than accepting polished output on faith.
• Build AI/LLM-powered product features where an engagement calls for it: prompt design, RAG pipelines, tool-calling or agent workflows, and integration with model providers (OpenAI, Anthropic, AWS Bedrock, etc.).
• Write clean, tested, well-documented code and implementation notes so knowledge transfers to teammates and the client, not just to you.
• Participate in code review, raise risk early, and seek review on unfamiliar or high-risk changes rather than guessing.
• Collaborate directly with client engineering teams and communicate technical decisions and trade-offs clearly.
• Contribute to CI/CD, basic AWS deployment, and observability for the features you build.

Required Qualifications

• 1-4 years of hands-on software development experience, with production code shipped to real users.
• Strong proficiency in at least one modern backend language (Python, Node.js/TypeScript, Go, or Java) and comfort working across the stack.
• Daily, hands-on experience using AI coding assistants (Claude Code, GitHub Copilot, Cursor, ChatGPT, or similar) in a real development workflow, not just occasional use.
• Demonstrated judgment in verifying AI-generated code: testing discipline, code review habits, and the ability to spot subtle bugs or security issues in AI output.
• Working knowledge of REST or GraphQL APIs, relational or NoSQL databases, and Git-based version control.
• Basic understanding of cloud platforms (AWS preferred) and how applications are deployed and run in production.
• Ability to write clearly: code comments, PR descriptions, and implementation notes a teammate can pick up without you.

Nice to Have

• Experience building with LLM APIs (OpenAI, Anthropic, AWS Bedrock) or frameworks such as LangChain or LlamaIndex.
• Experience with retrieval-augmented generation (RAG), vector databases (Pinecone, pgvector, OpenSearch), or agentic/tool-calling workflows.
• Exposure to prompt engineering and evaluation or testing of LLM outputs.
• Experience with containerization (Docker) and basic Kubernetes.
• Prior experience in a client-facing consulting or product development environment.

What We Value

Ampity looks for developers who use AI to move faster without outsourcing their judgment. In practice, that means we weigh these traits heavily in this role:

• AI fluency with scepticism — you use AI to accelerate work and know how to verify its output before it reaches production.
• Production ownership — you understand incidents, cost, and maintenance, not just initial delivery.
• Trade-off reasoning — you compare options for the actual constraints of a client or feature, rather than reciting best practices.
• Clarity — you can explain a decision, including its uncertainty, to a teammate and to a client.
• Knowledge transfer — you make the team and the client stronger rather than accumulating private expertise.

How to Apply

Apply on – [email protected]