SMX

SMX

Senior Cloud (DevSecOPs) Developer (5424)

Fort Washington, MD · Senior

No sponsorship$11k-$27kDetected 4 days ago
CI/CDMachine LearningLLMsCybersecurityLeadership

About the role

  • The leadership team will foster the organizational culture of high performing solution delivery.
  • This position is onsite in Camp Springs, Maryland and requires a Top-Secret clearance.

Responsibilities

  • SMX does not sponsor a new applicant for employment authorization or immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).

Requirements

  • Required Skills & Experience
  • Bachelor's degree required
  • Ability to communicate complex technical details clearly to diverse audiences

Skills

  • SMX is seeking a Senior Cloud DevSecOps Developer.

Compensation

  • $105,100 - $175,000 USD

Benefits

  • At SMX, one of our Core Values is to Invest in Our People so we offer a competitive mix of compensation, learning & development opportunities, and benefits.
  • Some key components of our robust benefits include health insurance, paid leave, and retirement.
  • From priority national security initiatives for the DoD to highly assured and compliant solutions for healthcare, we understand that digital transformation is key to your future success.
  • We share your vision for the future and strive to accelerate your impact on the world.
  • Selected applicant may be subject to a background investigation and/or education verification.

Equal opportunity

  • SMX is an Equal Opportunity employer including disabilities and veterans.

Visa & Work Authorization

  • SMX does not sponsor a new applicant for employment authorization or immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization t

This listing is sourced directly from SMX's careers page and normalized into a canonical job model.