Software Engineer – AI-Assisted Product Delivery

DecentralCode; Salem; On-site; INR 1,500,000 - 3,500,000; Full time

Job summary

DecentralCode seeks a Software Engineer - AI-Assisted Product Delivery to transform real customer challenges into scalable product capabilities for logistics teams in their day-to-day operations. This combined product engineering and customer implementation role involves direct customer work while converting requirements into reusable platform capabilities.

You will lead from requirements through design, development, testing, deployment, and production support, focusing on AI-assisted coding and

Qualifications

• The ideal candidate should have strong experience in Python backend development, APIs, integrations, databases, asynchronous processing, cloud technologies, automated testing, and production systems.

Responsibilities

• Design, develop, and maintain scalable Python backend services and APIs.
• Build and maintain integrations between customer and our systems.
• Develop workflow, operational process, and dossier-management capabilities.
• Design and implement document ingestion, extraction, validation, and processing functionality.
• Develop reliable asynchronous processing, background workflows, and failure-handling mechanisms.
• Translate customer-specific requirements into reusable and scalable product capabilities.
• Identify common patterns across customer implementations and develop platform-level solutions that can benefit multiple customers.
• Work closely with customers, product teams, and fellow engineers to understand operational requirements and translate them into technical solutions.
• Take full ownership of features from requirement analysis through design, development, testing, deployment, and production monitoring.
• Investigate and resolve production issues while identifying improvements that prevent similar issues from occurring again.
• Write clean, maintainable, well-tested, and production-ready code.
• Continuously improve existing architecture as the platform and customer base scale.
• Evaluate technical trade-offs and determine when quick implementation is appropriate and when a more scalable architectural solution is required.
• Use AI

Skills

Python backend

APIs

Integrations

Databases

Asynchronous processing

Cloud technologies

Automated testing

Production systems

AI-assisted development

Job description

Job Description

Software Engineer - AI-Assisted Product Delivery

Introduction

We are building the Operational Control Layer for Logistics.

Logistics operations are complex, with work distributed across emails, documents, operational systems, and people, while exceptions and changing circumstances are part of everyday operations.

Our project brings these elements together into one intelligent operational layer that understands what is happening, organizes the work, and helps operational teams take the right actions.

We combine Artificial Intelligence, workflow automation, and human decision-making to help logistics companies operate with greater control and significantly reduce manual work.

Our focus is on building a scalable logistics coordination platform, rather than creating separate customer-specific automation solutions.

As an early-stage startup with active customers across Europe, we offer the opportunity to work directly with customers, contribute to product decisions, and take significant ownership of both product development and customer implementations.

You will work in an environment with short feedback cycles, evolving requirements, and opportunities to directly influence how the product, technology, and company develop.

Location

India

Employment Type: Full-time

We are looking for

We are looking for an experienced and highly motivated Software Engineer - AI-Assisted Product Delivery who can transform real customer challenges into scalable product capabilities used by logistics teams in their day-to-day operations.

This is a combined product engineering and customer implementation role.

You will work directly on customer implementations while also identifying opportunities to convert customer-specific requirements into reusable capabilities within the our platform.

The ideal candidate should have strong experience in Python backend development, APIs, integrations, databases, asynchronous processing, cloud technologies, automated testing, and production systems.

AI-assisted software development is an important part of the role. We extensively use AI coding agents such as Claude Code, Codex, and similar tools to improve engineering productivity.

You should be comfortable using AI agents as part of your daily development workflow while maintaining ownership of the technical decisions, architecture, code quality, testing, maintainability, and production readiness of the software.

You will be expected to take problems from initial requirements through design, development, testing, deployment, and production support.

Responsibilities

• Design, develop, and maintain scalable Python backend services and APIs.
• Build and maintain integrations between customer and our systems.
• Develop workflow, operational process, and dossier-management capabilities.
• Design and implement document ingestion, extraction, validation, and processing functionality.
• Develop reliable asynchronous processing, background workflows, and failure-handling mechanisms.
• Translate customer-specific requirements into reusable and scalable product capabilities.
• Identify common patterns across customer implementations and develop platform-level solutions that can benefit multiple customers.
• Work closely with customers, product teams, and fellow engineers to understand operational requirements and translate them into technical solutions.
• Take full ownership of features from requirement analysis through design, development, testing, deployment, and production monitoring.
• Investigate and resolve production issues while identifying improvements that prevent similar issues from occurring again.
• Write clean, maintainable, well-tested, and production-ready code.
• Continuously improve existing architecture as the platform and customer base scale.
• Evaluate technical trade-offs and determine when quick implementation is appropriate and when a more scalable architectural solution is required.
• Use AI