Gen AI - InfoSec Engineer V

Reston, VA, US • Posted 15 hours ago • Updated 2 hours ago
Contract Corp To Corp
On-site
Fitment

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Job Details

Skills

  • Information Security
  • Business Process
  • Backend Development
  • Decision-making
  • Orchestration
  • Workflow
  • Scalability
  • Web Services
  • Interfaces
  • Continuous Integration
  • Continuous Delivery
  • Vulnerability Scanning
  • Management
  • Collaboration
  • Stacks Blockchain
  • Software Engineering
  • Python
  • GraphQL
  • WebSocket
  • Generative Artificial Intelligence (AI)
  • LangChain
  • Natural Language Processing
  • Data Analysis
  • Knowledge Base
  • Semantic Search
  • Vector Databases
  • Cloud Computing
  • Amazon Web Services
  • Amazon S3
  • Database
  • PostgreSQL
  • Amazon DynamoDB
  • OAuth
  • OIDC
  • SSO
  • Authentication
  • Authorization
  • DevOps
  • Jenkins
  • GitLab
  • Docker
  • React.js
  • API
  • JIRA
  • Confluence
  • Microsoft SharePoint
  • Artificial Intelligence

Summary

Job Description:

  • Title: Gen AI - InfoSec Engineer V
  • Skill Set summary:
      • Senior Full Stack GenAI Engineer with 10+ years of overall software engineering experience
      • 3+ years hands-on experience delivering GenAI-based enterprise applications and design and build agentic AI solutions that automate enterprise workloads and business processes.
      • The ideal candidate will have strong expertise in Python-based backend development, LLM-powered applications, cloud-native deployment, vector databases, and modern DevOps practices.
      • This role involves building end-to-end AI systems that integrate with enterprise platforms, automate workflows, and deliver production-grade AI applications.
  • Key Responsibilities:
      • Design and develop agentic AI applications that automate enterprise workflows and decision-making processes.
      • Build scalable backend services using Python, FastAPI, and Pydantic.
      • Develop and deploy LLM-powered applications using models such as GPT and Claude.
      • Build AI agents and orchestration workflows using LangChain or Strands.
      • Implement Retrieval Augmented Generation (RAG) solutions using vector databases (pgvector, Pinecone, Weaviate).
      • Perform data analysis, preparation, and curation to build high-quality datasets for AI and knowledge retrieval systems.
      • Design and implement document ingestion pipelines for enterprise knowledge sources such as SharePoint, Confluence, and Jira.
      • Deploy AI workloads on AWS (Bedrock, ECS Fargate, S3) with proper security and scalability practices.
      • Develop and integrate enterprise APIs using REST, GraphQL, WebSockets, and web services.
      • Implement secure authentication and authorization using Ping Identity, OAuth2, OIDC, and SSO.
      • Build user interfaces for AI applications using ReactJS or Streamlit.
  • DevOps & Deployment:
      • Build and manage CI/CD pipelines using Jenkins or GitLab.
      • Implement GitOps practices for automated deployments.
      • Containerize applications using Docker and deploy to cloud platforms.
      • Implement security best practices, vulnerability scanning, dependency management, and container security.

Required Skills

    • Strong full stack engineering mindset with GenAI expertise.
    • Experience building production-grade AI systems.
    • Ability to work across AI, backend, cloud, and DevOps stacks.
    • Passion for building automation solutions powered by agentic AI.

________________________________________

  • Overall Experience:
    • 10+ years of software engineering experience
    • 3+ years hands-on experience delivering GenAI-based enterprise applications
  • Backend & APIs
    • Python
    • FastAPI
    • Pydantic
    • REST APIs, GraphQL, WebSockets
  • GenAI & Agent Frameworks
    • LLMs (GPT, Claude)
    • LangChain or Strands
    • Retrieval Augmented Generation (RAG)
    • NLP (Natural Language Processing)
  • Data & AI Pipelines
    • Data analysis, data preparation, and data curation
    • Document ingestion and knowledge base creation
    • Embeddings and semantic search
  • Vector Databases
    • pgvector
    • Pinecone
    • Weaviate
  • Cloud & Platforms: AWS (Bedrock, ECS Fargate, S3, Guardrails)
  • Databases
    • PostgreSQL
    • DynamoDB
  • Security & Identity
    • Ping Identity
    • OAuth2 / OIDC
    • SSO, Authentication & Authorization
  • DevOps
    • Jenkins
    • GitLab
    • GitOps practices
    • Docker containerization
    • Security vulnerability mitigation
  • Frontend
    • ReactJS
    • Streamlit
  • Enterprise Tools
    • Portkey (AI Gateway)
    • Apigee (API Gateway)
    • Jira, Confluence, SharePoint

________________________________________
Preferred Qualifications
Experience building AI agents for enterprise automation.
Experience implementing AI guardrails and LLM governance frameworks.
Experience building enterprise copilots or knowledge assistants.
Familiarity with LLMOps and AI observability platforms

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 91022079
  • Position Id: 2026-47967/576327
  • Posted 15 hours ago
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