FullStack Developer – AI Integration (3 to 14 Yrs)

Winzons; India; On-site; INR 3,000,000 - 6,000,000; Full time

Benefits offered by this job

Competitive salary

Mediclaim plans

AI tooling access

Educational resources

Fintech exposure

Job summary

Hireit73 is seeking an experienced Fullstack Developer in Mumbai to build a platform where AI is the development baseline. You will integrate AI tooling, large language model APIs, and agentic workflows to automate lending processes such as underwriting and fraud detection while maintaining strong fundamentals: secure, clean, and scalable code.

The role covers core engineering and AI integration with a focus on deploying production-grade features, high-quality testing, and collaboration with

Qualifications

• BCA or Engineer or equivalent degree.
• AI/ML degree not mandatory; hands-on AI tooling counts.

Responsibilities

• Analyse and maintain existing software applications.
• Design highly scalable, testable code.
• Use server-side scripts to create micro-services powering customer journeys; build web systems with N-tier architectures, security models.

Education

BCA or Engineer or equivalent degree

AI/ML degree not mandatory

Tools

Python

PHP

Laravel

Angular

React

HTML

CSS

JavaScript

MySQL

MongoDB

NoSQL

REST

SOAP

Git

AWS

Playwright

Job description

Company Name: Hireit73
Job Role: FullStack Developer - AI Integration & Agentic Development
Experience Required: 14 Years
Location: Mumbai, India
Department: Technology
Industry: Fintech / Artificial Intelligence / Software Development
Qualification: BCA / Engineering or equivalent degree (AI/ML degree not mandatory)

The Position :

As a Fullstack Developer, youll be building on a platform where AI is not an optional add-on it is the development baseline. You will use AI coding assistants (Claude Code, Gemini, or AntiGravity) as your primary IDE, integrate large language model APIs into product features, and build agentic workflows that automate credit underwriting, fraud detection, and document processing. At the same time, you remain a craftsman of the fundamentals: clean, secure, testable code that solves major lending problems at scale.

You will be involved in building software which not only looks great, but solves major lending problems in the country. Youll design systems, make organisation frameworks and components, help in defining the look and feel of credit systems and continually grow as a full stack developer.

Roles & Responsibilities :

Core Engineering :

• Analyse and maintain existing software applications.
• Design highly scalable, testable code.
• Use server-side scripts to create micro-services that power our Customer Experience and User journeys; build web-based software systems utilising N-tier architectures, dynamic content, highly-scalable approaches, and complex security models & implementations.
• Fully comprehend, effectively communicate, and enforce goals and objectives, feedback, measurable, and improvement plans.
• Mentor other engineers, support the technical culture, and help grow the team.
• Communicate with project leads, product managers and other software developers.
• Participate in Change Control Board (CCB) reviews and maintain audit-ready change logs for all production deployments.

AI Integration & Agentic Development :

• Use AI coding assistants as the primary development workflow this is mandatory, not optional.
• Integrate LLM APIs (Anthropic Claude, Google Gemini) into product features : credit underwriting agents, document-processing pipelines, and fraud-scoring systems.
• Design and build agentic workflows define tool schemas, implement MCP (Model Context Protocol) servers in TypeScript or Python, and wire up multi-step agent orchestration.
• Write, version-control, and iteratively improve system prompts and prompt templates for production AI features; treat prompts as first-class code artefacts.
• Build evaluation harnesses to test AI output quality, catch regressions, and validate model behaviour on regulated financial data.
• Apply deterministic parsing and validation layers over LLM outputs especially for financial fields where hallucination is a compliance risk.

DevOps & Quality :

• Maintain CI/CD pipelines on AWS; practise infrastructure-as-code and security-first deployment patterns.
• Write Playwright end-to-end tests covering critical lending workflows.

Key Skills / Requirements :

Education :

• BCA or Engineer or any similar degree.
• No formal AI/ML degree required demonstrated hands-on experience with AI tooling counts more.

AI Tooling Mandatory :

• Proficiency with an AI coding assistant (Claude Code, GitHub Copilot, or Cursor) as a daily development tool non-negotiable.
• Working experience integrating LLM APIs (Anthropic, OpenAI, or Google Gemini) into production applications.
• Practical prompt engineering: system prompts, few-shot examples, chain-of-thought, output validation.
• Understanding of agentic system design: tool-calling, MCP protocol, multi-agent orchestration.

Core Stack :

• PHP Frameworks : Laravel, any other framework.
• Back-End : PHP, Python.
• JavaScript Frameworks : Angular, React.
• Front-End : HTML, CSS and JavaScript.
• Databases : MySQL, NoSQL and MongoDB.
• Should have worked on web-services (REST, SOAP).
• Previous experience in GIT is a must.

Strong Advantage :

• MCP Server development (TypeScript or Python, Streamable HTTP transport).
• Experience with vector databases and RAG (retrieval-augmented generation) architectures.
• Knowledge of AWS (EC2, RDS, Lambda, SQS) and Agile delivery.
• Familiarity with AI evaluation frameworks and structured testing of LLM outputs.
• Domain knowledge in fintech / lending (LOS, LMS, bureau reporting, co-lending).
• Experience with Playwright or other automated end-to-end testing frameworks.

Benefits :

• Competitive salary packages and bonuses.
• Mediclaim plans for you and your dependents.
• Company-expensed access to AI tooling: Anthropic Claude Pro, GitHub Copilot, and equivalent developer AI subscriptions.
• Access to educational resources for self-improvement technical and non-technical.
• Direct exposure to cutting-edge fintech infrastructure: co-lending, capital markets (PTC/DA), AI underwriting, and trade finance tokenisation.