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Georgia IT Inc

Software Developer- Texas

Georgia IT Inc, Texas City, Texas, us, 77592

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Job Title: Software Developer (SailPoint IIQ & Okta Integration) - Remote (Texas) Location:

Texas (Remote-friendly) Job Type:

Full-time | Long-term project Industry:

IT Services | Government Projects

Job Description: We are seeking a

highly skilled and motivated Software Developer

with a strong background in

SailPoint IdentityIQ (IIQ)

and

Okta SSO integration . This exciting opportunity allows you to work

remotely from Texas , collaborating with talented architects, UX designers, analysts, and project managers on impactful enterprise-level projects. You will be responsible for

designing, developing, and managing software solutions , with a special focus on

identity access management (IAM) ,

application integration , and

agile delivery .

Roles and Responsibilities:

Design, develop, test, and deploy scalable software applications Integrate identity and access systems like

SailPoint IIQ

and

Okta SSO Build and maintain

API services

for access policies and external app integration Work closely with UI/UX designers, architects, and business analysts to ensure seamless software solutions Evaluate and test new programs to ensure high performance Participate in Agile/Scrum sprints and contribute to timely project deliveries Support application and identity governance requirements across teams

Must-Have Skills & Qualifications:

6+ years of experience in

Agile/Scrum-based solution delivery 6+ years collaborating with architects and delivery teams for SailPoint IIQ deployment 4+ years of hands-on

SailPoint IIQ development

- workflows, rules, connectors, policies 4+ years of experience with

Okta Single Sign-On (SSO)

integrations 4+ years developing

RESTful APIs

for access and identity systems Ability to work independently with minimal supervision Strong communication and documentation skills

Preferred (Bonus Points):

2+ years of experience working with

Texas State Agencies Familiarity with

Azure AD

and cloud-based IAM environments