APP Engineer

TekWissen•Dallas, TX

1d•Onsite

About The Position

TekWissen is recruiting an AI-First Engineer with supply chain management (SCM) planning expertise to help transform how supply chain applications are designed, developed, tested, deployed, and supported. The role applies AI-enabled engineering practices across the software development lifecycle (SDLC), using AI to improve productivity, code quality, testing efficiency, operational support, and software delivery outcomes. The successful candidate will demonstrate and quantify business outcomes from AI adoption, such as shorter development cycles, improved quality, reduced testing effort, faster deployments, and faster issue resolution. The engineer will use AI and large language model technologies to analyze business requirements and SCM specifications; generate designs, assessments, traceability matrices, alternatives, and estimates; and accelerate fit-gap analysis and cloud upgrade impact assessments. The role also involves AI-assisted development and modernization of SCM customizations, integrations, extensions, reports, and automation, as well as AI-supported testing, CI/CD practices, documentation, deployment, environment management, and operational support. This is a six-month temporary assignment, onsite in Dallas, Texas.

Requirements

10 years of experience.
SCM planning expertise.
Proven track record of applying AI across the software development lifecycle.
Ability to demonstrate and quantify measurable business outcomes achieved through AI adoption.
Experience with AI-assisted developer workflows, prompt engineering, and RAG patterns.
Experience or familiarity with AI tools and technologies listed in the posting, including GitHub Copilot, Oracle Code Assist, ChatGPT, Claude, Agentic AI frameworks, OCI Generative AI, and Windsurf.
Development experience across PL/SQL, Java, JavaScript, Groovy, VBCS, OIC, and APEX.

Responsibilities

Apply AI-enabled engineering practices throughout all phases of the software lifecycle.
Use AI and LLM technologies to analyze business requirements, BRDs, user stories, process flows, and SCM functional specifications.
Generate technical designs, impact assessments, traceability matrices, solution alternatives, and effort estimates through AI-assisted workflows.
Use AI to accelerate fit-gap analysis, quarterly cloud upgrade impact assessments, and knowledge discovery.
Use AI coding tools and frameworks to develop, optimize, refactor, reverse engineer, and modernize software across PL/SQL, Java, JavaScript, Groovy, VBCS, OIC, and APEX.
Develop SCM customizations, integrations, extensions, reports, and automation solutions using AI-enabled practices.
Apply AI to automate integration mappings, API creation, report generation, and technical documentation.
Build AI-powered functional, integration, regression, performance, and user acceptance testing strategies.
Use AI for test-case generation, test-data creation, defect identification, test maintenance, defect triage, root cause analysis, and predictive quality insights.
Implement AI-enhanced regression testing frameworks to support quarterly cloud releases.
Integrate AI-assisted code reviews, security analysis, static code scanning, and quality gates into CI/CD pipelines.
Use AI to generate deployment documentation, release notes, implementation guides, and operational runbooks.
Apply AI-powered monitoring and analytics to assess quarterly release readiness and business impact.
Support AI-driven deployment automation and environment management practices.
Quantify and communicate outcomes from AI adoption, including cycle-time reduction, improved code quality, reduced defects and testing effort, faster deployments and incident resolution, and increased developer productivity.