Software Engineer (Full-Stack, AI & LLM Integration)

Ethicalhat; India; Remote; INR 900,000 - 1,500,000; Full time

Job summary

Ethicalhat is hiring a full-stack Software Engineer to build and grow web products, adding AI features such as LLM-powered assistance, AI integrations, and an MCP server for safe data access.

You will design backend services, develop responsive frontend screens, and implement secure authentication (SSO, MFA, RBAC) while ensuring code quality and documentation.

Qualifications

• At least 3+ years building production web applications end-to-end.
• Backend: Java (OpenJDK) and Groovy with Grails.
• Frontend: JS, HTML, CSS.
• Databases: MariaDB and Neo4j.
• APIs: REST design and docs.

Responsibilities

• Design, build and maintain backend services and APIs.
• Build frontend screens and dashboards.
• Design DB schemas and write efficient queries.
• Implement authentication: SSO, MFA, RBAC.
• Document REST APIs and third-party integrations.

Skills

Java/OpenJDK

Groovy/Grails

Frontend JS/HTML/CSS

SQL/MariaDB

Neo4j/Cypher

REST APIs

Security and IAM

TLS/PKI

SAST/ SBOM

Written English specs

Education

Degree in Computer Science

Tools

Grails

MariaDB

Neo4j

Okta

OIDC/SAML

Job description

Role summary

We are hiring a full-stack Software Engineer to build and grow our web products, and to add AI features to them: LLM-powered assistance, AI integrations, and an MCP server that lets AI assistants work with our product data safely.

Key responsibilities

Product engineering

• Design, build and maintain backend services and APIs.
• Build clean, responsive frontend screens.
• Design database schemas and write efficient queries.
• Build features such as dashboards, workflows, role-based access, file uploads and report exports (CSV, PDF, PPTX).
• Write data migration scripts when systems change.

Integrations and security

• Build and document REST APIs and third-party integrations.
• Set up authentication: SSO (OIDC, SAML), MFA, role-based access control.
• Follow secure development practice: code reviews, dependency and SAST scanning, fixing reported vulnerabilities.
• Package and deploy releases for cloud and on-premises setups (Windows and Linux).

AI and LLM features

• Build AI assistants inside the product that answer user questions in plain language, grounded in our own data.
• Use LLMs to summarize data, draft reports and suggest next steps for users.
• Extract and classify information from uploaded documents, with a human confirming results.
• Measure AI quality and cost, and improve them release by release.

MCP server

• Build and maintain an MCP (Model Context Protocol) server that exposes product data and actions as tools and resources.
• Let AI clients such as Claude, ChatGPT or IDE agents work with the product through that server.
• Enforce the same user roles and data boundaries in the MCP server as in the web app, with audit logs for every AI action.

Required skills and qualifications

• 3+ years building production web applications, end to end.
• Backend: Java (OpenJDK) and Groovy with the Grails framework.
• Frontend:js, JavaScript, HTML and CSS.
• Databases: MariaDB (schema design, SQL, backup and restore with Mariabackup) and Neo4j (graph modelling, Cypher queries).
• Application server: Apache Tomcat, including TLS setup.
• Identity and access: Keycloak; SSO with OIDC and SAML using Okta, Microsoft Entra ID and Auth0; MFA and role-based access control.
• APIs: REST API design and documentation.
• Platforms: installing, upgrading and running applications on Windows Server and Linux (Ubuntu), including unattended upgrades.
• Secure coding practice: SAST scanning, dependency checks, SBOM maintenance, fixing penetration test findings.
• Clear written English for specs, API docs and user guides.
• Degree in Computer Science or similar, or equivalent hands-on experience.

AI, LLM and MCP requirements

The candidate must have shipped at least one LLM feature to real users, not only a demo.

Nice to have

• Experience building B2B or SaaS products with multi-tenant data.
• Experience with security, compliance or audit-related software.
• Generating PDF, PPTX or Excel reports from code.
• Building installers or packages for on-premises software.
• Open-source contributions, especially MCP servers or LLM tooling.

What success looks like

1. First 30 days: Sets up the codebase locally, understands the data model, and ships two or three small fixes.
2. By 60 days: Ships the first AI feature with cited sources, and a working MCP server with read-only tools.
3. By 90 days: Owns a module end to end, adds write actions to the MCP server with role checks and audit logs, and has AI evaluations running in CI.

Interview process and how to apply

1. Intro call (30 min): background, interests, availability.
2. Take-home task (3-4 hours): build a small MCP server that exposes a sample dataset as tools, plus one LLM call that summarizes the results.
3. Technical interview (60 min): walk through the task, then a system design question, such as adding an AI assistant to a multi-user web app safely.
4. Founder chat (30 min): working style, ownership, expectations.