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

Ethical Hat Security Pvt. Ltd.

Países Bajos

A distancia

EUR 70.000 - 95.000

Jornada completa

Hace 10 días

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

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Descripción de la vacante

Ethical Hat Security Pvt. Ltd. is hiring a remote full-stack Software Engineer to design and grow web products, integrating AI features and LLM capabilities.

You will build backend services, REST APIs, and secure data flows, while delivering polished frontend interfaces and dashboards. You will work on MCP server integration, SSO, MFA, and RBAC, ensuring secure coding, testing, and compliant deployments across Windows and Linux environments.

Formación

  • Production web apps: 3+ years end-to-end

Responsabilidades

  • Design, build and maintain backend services and APIs.
  • Build clean, responsive frontend screens.
  • Design database schemas and write efficient queries.
  • Build dashboards, workflows, RBAC, file uploads and report exports.
  • Write data migration scripts when systems change.
  • Build and document REST APIs and third-party integrations.
  • Set up authentication: SSO (OIDC, SAML), MFA, RBAC.
  • Follow secure development practice: code reviews, dependency & SAST scanning, fix vulnerabilities.
  • Package and deploy releases for cloud and on-premises (Windows & Linux).
  • Build AI assistants inside the product, summarize data, draft reports.
  • Extract and classify information from documents with human confirmation.
  • Measure AI quality and cost, improve release by release.
  • Build MCP server exposing product data as tools/resources.
  • Let AI clients work with product via MCP server.
  • Enforce the same user roles and data boundaries with audit logs.
  • Guard against prompt injection and keep customer data separate.
  • Run open models via Ollama/vLLM; switch providers behind one interface.
  • Connect to external MCP servers or agent frameworks.
  • Log every AI call with inputs/outputs/latency/cost; alerts on failures.

Conocimientos

Java
Groovy
Grails framework
MariaDB
Neo4j
Tomcat
Keycloak
OIDC
SAML
MFA
RBAC
REST APIs
Windows Server
Linux (Ubuntu)
SAST
SBOM
Penetration testing
English writing

Educación

Degree in Computer Science or similar

Herramientas

pgvector
Qdrant
LangChain
LangGraph
Spring AI
LlamaIndex
Ollama
vLLM

Descripción del empleo

Ethical Hat Security Pvt. Ltd. | Full time

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

EthicalHat is a global cybersecurity provider with delivery centers in California, USA and Gurugram, India. Our security operations center is run by analysts and engineers with deep experience in cyber defence, and our offensive, product, cloud and AI specialists work alongside them, so what we learn attacking systems makes us better at defending them.

Job Description

This is a remote position.

We at ETHICALHAT Cyber Security 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

• 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 result.

• 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.

Requirements

• 3+ years building production web applications, end to end.

• Backend: Java (OpenJDK) and Groovy with the Grails framework.

• 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.

Area

What we expect

LLM APIs

Hands-on use of at least one major API (Anthropic Claude, OpenAI, Google Gemini or Azure OpenAI): streaming, tool/function calling, structured JSON output, token and cost control

Retrieval (RAG)

Chunking and embedding documents, vector search with pgvector, Qdrant or similar, citing sources in answers

Writing and versioning prompts, few-shot examples, system prompts that keep answers grounded

Evaluation

Test sets and automated checks for accuracy, hallucination and regressions before each release

AI safety

Guarding against prompt injection from user content, keeping customer data separate, redacting sensitive data, human approval for actions an AI suggests

Running open models (Llama, Mistral, Qwen) through Ollama or vLLM; switching providers behind one interface

MCP server

Building an MCP server with an official SDK (TypeScript, Python or Java): tools, resources and prompts; stdio and Streamable HTTP transports; OAuth-based auth; testing with MCP Inspector and real clients

Agents and frameworks

Connecting to external MCP servers or using agent frameworks (LangChain, LangGraph, Spring AI, LlamaIndex) where useful

Observability

Logging every AI call with inputs, outputs, latency and cost; alerts on failures

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