AI Full Stack Engineer

AIFull StackEngineer

(AIEnabled& AgentDriven Development)

About the role

We are looking foraAIFullStackEngineer who builds modern applications using AI as afirstclasscapabilityboth as part of the development workflow and as part of the systems we ship.

This role goes beyond simply usingAI coding assistants. You willhavestrongunderstanding ofPrompt Engineering Vibe Coding Rework Rate ReductionandleverageCustomAgents and integrations built around theModel Context Protocol (MCP).You will apply strong software engineering fundamentals toassemble integrate and operationalize AI capabilities into real production systems.

The goal of this role is to significantly shorten development and feedback cyclesby automating routine engineering work augmenting human decision-making and embedding intelligence directly into our development workflows and the applications we deliver

Whatyoulldo

CoreFull StackEngineering:

• Contribute to platform enablement architecture decisions code reviews and shared engineering standards

• Design build test deploy andoperatefullstacksoftware solutions

• Own featuresendtoend: system designplatformimplementation testing observability and lifecycle support

• Collaborate withbusinessteams to translate requirements into scalable solutions

AIcentricfull stackdevelopment

• Design and implementCustom AIAgentsto support workflows such as:

• Task automation

• Decision support and summarization

• Multistepreasoning andtooldrivenexecution

• Fluent in prompt engineering and Vibe Coding Prototypes

• Build and integrate systems using theModel Context Protocol (MCP)to enable:

• Structured context sharing between models tools and agents

• Tool and capability exposure toLLMbasedagents

• Interoperability across AI components withouthardcodedintegrations

• Integrate applications with external and internal AI services (LLMs embeddings search tools) viawelldesignedAPIs

• Harden AI components for24x7 mission criticalphysical manufacturingsystemswith attention to:

• Reliabilityandresiliency

• Latency andperformance

• Security permissions and data boundaries

• Observabilityand maintainability

• Utilizeretrievalaugmentedgeneration (RAG)systems

AIenableddevelopment practices

• UseAIassistedtools to accelerate development (code generation refactoring test creation documentation)

• Critically evaluate and refineAIgeneratedoutput rather than accepting it blindly

• Apply human judgment to architecture correctness andlongtermmaintainability

Whatwerelooking for

Corefull stackengineering skills

• Strong foundationinfull stacksoftware engineering fundamentals includingobject-oriented design clean code practices testing strategies and long-term maintainability.

• Proven experience building and operating production-grade backend or full-stack systems includingAPI design service integration anddata persistence.

• Ability to design and evolve scalable system architectures making thoughtful tradeoffs across performance reliability security and developer productivity.

• Experience working incloud-native environments including CI/CD pipelines containerized deployments and modern operational practices.

• Solid understanding ofdata modeling and storage technologies spanning relational and non-relational databases and selecting the right tool for the problem.

• Track recordof owning software end-to-endfrom design andimplementation through testing deployment observability and lifecycle support.

• Comfortable collaborating across engineering and business teams to translate requirements into robust scalable solutions.

• Technologies you may encounterinclude:modern backend frameworks (for example C# ) frontend frameworks (for example Angular) RESTful APIs SQL and NoSQL databases and Kubernetes-based container platforms.

AIcentricskills

• Experience designingandimplementingCustom AI agentsbeyond simple chat interfaces. Thisshould include experiencedevelopingskillsfor custom agents.

• AI native skills likePrompt Engineering Vibe Coding Context Window management & Chain of thoughts Design

• Experience integrating systems usingModel Context Protocol (MCP)or equivalent structured agent/tool interfaces

• Strong understanding of prompt designandtool invocation

• Ability to reason abouthallucination risk failure modes permissions and guardrails inAIenabledsystems

• Handsonexperience integratingRAGbasedsystems