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AI-DLC Developer / AI-Native Software Engineer

Transcend IT SolutionsChicago, IL🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeOn Site
LocationChicago, IL, United States
GitScrum.NETJavaPythonGenerative AIAzureJavaScriptTypeScriptPrompt EngineeringCI/CDRAG

Job description

Job Title: AI-DLC Developer / AI-Native Software Engineer
Experience Required: 8+ Years
Work Mode: Onsite(Hybrid - 3 Days/Week Onsite)
Location: - Chicago, IL / Edina, MN (Hybrid – 3 days’ Work from Office)
Employment Type: Contract
Duration: - 6-12 Months
Role Overview & What's In It For You:
We are looking for a hands-on AI-DLC Developer / AI-Native Software Engineer who can use AI to fundamentally change how applications are designed, built, tested, and delivered. This is not a traditional AI/ML Engineer role working within a conventional Scrum or Waterfall lifecycle. The ideal candidate can take an ambiguous business problem and rapidly turn it into a working, validated solution using AI-assisted development.
The expected development loop is: Understand Intent → Generate → Build → Evaluate → Refine → Deliver.
Key Responsibilities:
  • Build end-to-end applications using an AI-assisted development lifecycle.
  • Rapidly convert business requirements and ideas into working prototypes and PoCs, often within days.
  • Use AI throughout development, including solution design, coding, testing, debugging, documentation, and refinement.
  • Develop applications, APIs, integrations, workflows, automation, and AI/agentic solutions.
  • Create reusable development harnesses, templates, accelerators, prompts/context frameworks, test suites, and evaluation utilities.
  • Work directly with business/domain experts to build, demonstrate, receive feedback, and continuously refine solutions.
  • Define acceptance criteria and continuously evaluate AI-generated output for correctness, quality, security, usability, and business fit.
  • Convert rapidly developed prototypes into secure, maintainable, production-ready applications.
  • Apply strong engineering judgment to determine what AI can accelerate and what still requires deeper engineering and human validation.
What We Are Looking For (Candidate Persona):
Someone who:
  • Builds, not just designs or manages.
  • Can go from idea to working prototype quickly.
  • Uses AI across the entire engineering lifecycle, not just for code generation.
  • Is comfortable experimenting, evaluating, failing fast, and iterating.
  • Can work across frontend, backend, integrations, data, AI, testing, and deployment as needed.
  • Understands the difference between a rapid prototype and production-ready software.
  • Measures progress through working and validated software, not just completed development tasks.
What This Role Is NOT:
We are not looking for someone whose experience is limited to:
  • Traditional AI/ML development within Scrum/Waterfall.
  • Prompt engineering or RAG development alone.
  • Using Copilot/ChatGPT only for coding productivity.
  • Architecture without hands-on development.
  • Project/Program Management or Scrum delivery.
  • Building PoCs without understanding production engineering.
Educational Qualifications & Skills:
Educational Qualifications:
  • Engineering Degree – BE / ME / BTech / MTech / BSc / MSc.
  • Technical certification in multiple technologies is desirable.
Mandatory Skills:
  • Strong hands-on software/application development experience, with demonstrated experience using AI-assisted or AI-native development approaches to build real applications.
  • Strong experience with rapid prototyping and PoC development, including hands-on experience with tools such as Claude/Claude Code, GitHub Copilot, Cursor, OpenAI/Codex, Gemini, Azure OpenAI, or similar.
  • Strong programming skills in Python, JavaScript/TypeScript, Java, .NET, or equivalent modern development technologies.
  • Experience with APIs, integrations, databases, cloud services, CI/CD, automated testing, and application security.
  • Exposure to Agentic AI, LLMs, RAG, tool calling, context engineering, and AI evaluation (experience creating reusable AI development accelerators or evaluation harnesses is highly desirable).
  • Good understanding of software architecture, security, scalability, observability, and production engineering.

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