DevOps Engineer (GenAI Exposure)

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McLean, VA (Onsite – In-Person Interview Required)
C2C

We are seeking a DevOps Engineer with exposure to Generative AI technologies to join our team in McLean, VA. This role focuses on building and maintaining scalable cloud infrastructure, CI/CD pipelines, and supporting emerging GenAI/ML workloads. The ideal candidate has strong DevOps fundamentals and a growing interest or hands-on experience in LLM-based systems and MLOps practices.

 Key Responsibilities

  • Design, implement, and maintain CI/CD pipelines using tools like Jenkins, GitHub Actions, or GitLab CI
  • Manage cloud infrastructure (AWS preferred) using Infrastructure as Code (Terraform/CloudFormation)
  • Deploy and manage containerized applications using Docker and Kubernetes (EKS preferred)
  • Collaborate with data science/AI teams to support GenAI/ML model deployment pipelines
  • Build and maintain MLOps workflows, including model versioning, monitoring, and scaling
  • Support integration of LLM-based applications (RAG pipelines, APIs, vector databases)
  • Monitor system performance using tools like Prometheus, Grafana, or CloudWatch
  • Ensure security, compliance, and reliability of infrastructure

 Required Qualifications

  • Bachelor’s degree in Computer Science, Engineering, or related field
  • 3–7 years of experience in DevOps / Cloud Engineering
  • Strong experience with AWS (EC2, S3, Lambda, EKS) or equivalent cloud platforms
  • Hands-on experience with Docker & Kubernetes
  • Experience building CI/CD pipelines
  • Proficiency in Python or Bash scripting
  • Understanding of Linux systems and networking basics

 Preferred (GenAI / AI Exposure)

  • Exposure to Generative AI concepts (LLMs, RAG, embeddings)
  • Experience with tools like LangChain, OpenAI APIs, Hugging Face
  • Familiarity with vector databases (Pinecone, FAISS, Weaviate)
  • Basic understanding of MLOps tools (MLflow, Kubeflow, SageMaker)
  • Experience deploying or supporting ML/AI workloads in production

 Nice to Have

  • Experience with Terraform modules & multi-environment deployments
  • Knowledge of security best practices (IAM, secrets management)
  • Exposure to data pipelines (Airflow, Kafka)
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