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OSS Solution Architect
Job in
Dallas, Dallas County, Texas, 75201, USA
Listed on 2026-08-05
Listing for:
TechDigital Corporation
Full Time
position Listed on 2026-08-05
Job specializations:
-
Software Development
Data Engineering, AI Engineer (Applied/Software)
Job Description & How to Apply Below
Key Requirements:
- Senior Leader with 15+ years of Telecom OSS infrastructure experience, including leadership of large, cross-functional modernization programs. Deep technical expertise in TIRKS circuit provisioning life cycles.
- Strong IBM Mainframe skills (z/OS, JCL, IMS, VSAM, CICS).
- Hands-on modern architecture experience (APIs, microservices, AWS/Azure).
- Master of SQL, data modeling, and enterprise ETL migration tools.
- Proven mainframe modernization experience — led or architected at least one large scale legacy modernization program using a tiered disposition model (retire, re-host, replatform, AI-assisted refactor, replace-with-COTS).
- Familiarity with real-time API enablement patterns (z/OS Connect, CICS Transaction Gateway, MQ-based request/reply) and data replication / CDC approaches (e.g., Debezium, Db2) is strongly preferred.
- Applied Gen-AI tooling for modernization — hands-on experience using generative AI tools (e.g., Git Hub Copilot, Amazon Q Developer / Code Whisperer, Claude, or equivalent) for legacy code comprehension, COBOL/JCL analysis and auto documentation, test-case generation, and AI-assisted refactoring.
- Must be able to define where AI accelerates delivery and where human-in-the-loop (HITL) review and validation are mandatory.
- Degree in Computer Science, Telecom, or Network Engineering.
1. System Transformation — Map and migrate legacy TIRKS mainframe systems to cloudor service-based platforms.
2. Interface Deconstruction — Rewire complex integrations between TIRKS and adjacent modules such as SWITCH, FACS, WFA, and SOAC.
3. Data Migration — Oversee extraction and validation of critical network inventory, CFAs, and trunk line data.
4. AI-Assisted Modernization — Establish and govern the use of Gen-AI tooling across the modernization lifecycle: reverse-engineering undocumented logic, generating design and test artifacts, and accelerating code refactoring — with appropriate
guardrails, review gates, and quality controls.
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