AI Engineer/Staff Software Engineer Agentic Development
for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. The posting includes: description (intro) maybe "About the role". Then "Key Responsibilities:" with bullet list. Then "Learning Content & Assessment Development" (maybe part of responsibilities). Then "Full Stack Development" (maybe responsibilities). Then "Required Skills:" (skills). Then "Preferred Qualifications:" (qualifications). Then "Education & Experience:" (qualifications). Then "Nice-to-Have:" (maybe qualifications or preferences). There's no explicit Pay, Schedule, Benefits. So we should not include those sections.
We need to avoid repeating job title as heading. Use for each section heading. Use - for any list of duties/requirements/benefits. Use
for prose.
We need to preserve all substantive information, not invent or summarize away detail. Remove boilerplate etc. There's no cookie/navigation etc.
We need to include sections only when posting has real specific content. So we can have sections: About the role (intro paragraph), Responsibilities (maybe combine key responsibilities, learning content, full stack dev), Required Skills (skills), Preferred Qualifications (preferred quals + education & experience + nice-to-have maybe). Could split into Qualifications and Preferred Qualifications. But we need to avoid thin sections. Let's think.
We have:
- Intro paragraph: "We are seeking a highly skilled AI Engineer who can define and scale how our engineering organization builds simulation software with AI agents. This role requires deep fluency in 'loop engineering' with tools like Claude Code: designing the feedback loops, guardrails, and workflows that let AI agents safely and effectively contribute to production codebases. You'll need to understand the full agentic software development lifecycle, from context design through evaluation, deployment, and observability, while also being a hands-on expert across our core stack. This is a staff-level role: you'll collaborate with other engineers to set technical direction, define best practices for agentic development across teams, and remain deeply hands-on in architecture and code."
That's substantive.
Then "Key Responsibilities:" with bullet list items:
- AI & Generative AI Development
- Design and implement "loop engineering" workflows using Claude Code and similar tools, defining how agents plan, execute, test, and iterate on code changes
- Architect Model Context Protocol (MCP) servers and tool schemas that are legible and safe for LLM agents to use
- Define human-in-the-loop checkpoints, autonomy boundaries, and rollback strategies for agent-driven changes
- Build evaluation harnesses and observability practices to measure agent output quality and catch regressions
- Design and review microservice and microfrontend architecture using C4 diagrams and Domain-Driven Design principles
- Drive test-driven development practices across teams, including contract testing between services
- Own technical decisions across our Java microservices, Node.js services, React/microfrontend UI, and Python tooling
- Learning Content & Assessment Development
- Design and develop hands-on lab activities, practical exercises, guided projects, and simulations.
- Create technical learning content for AI, cloud, software engineering, and emerging technologies.
- Develop assessment questions including: o Multiple Choice Questions (MCQs) o Scenario-based questions o Coding exercises o Capstone projects o Knowledge checks
- Utilize Claude and other AI tools to generate, review, and improve educational content.
- Align content with learning objectives, competency frameworks, and certification standards.
- Full Stack Development
- Develop responsive web applications using React.js.
- Build backend services and APIs using Node.js and Express.js.
- Integrate AI services and LLM APIs into web applications.
- Design and implement secure RESTful APIs and microservices.
- Develop dashboards for content management, assessment reporting, and learner analytics.
Then "Required Skills:" with list:
- Generative AI Claude (Anthropic), OpenAI, Azure OpenAI
- Prompt Engineering
- AI Agent Development
- RAG Architecture
- Vector Databases
- LLM Evaluation & Testing
- MCP and Tool Integrations
- Programming JavaScript / TypeScript Node.js React.js Python REST APIs JSON
- AI Frameworks & Libraries LangChain LangGraph
- Databases PostgreSQL MongoDB Redis Vector Databases
- Front-End Development React.js HTML5 CSS3 Material UI / Bootstrap Responsive Design
- Backend Development Node.js Express.js Microservices Architecture Authentication & Authorization
Then "Preferred Qualifications:" list:
- Experience creating learning content, labs, or certification preparation material.
- Experience with AI-based assessment generation and automated evaluation systems.
- Familiarity with Learning Management Systems (LMS).
- Experience building Agentic AI and multi-agent solutions.
- Understanding of instructional design principles.
- Experience working with educational technology platforms.
Then "Education & Experience:" list:
- Bachelor's or Master's degree in Computer Science, Information Technology, AI/ML, or related field.
- 7+ years of software development experience.
- 2+ years of Generative AI / LLM application development experience.
- Demonstrated experience creating AI-powered learning solutions, labs, or assessment content.
Then "Nice-to-Have:" list:
- Experience in Education Technology (EdTech)
- Knowledge of Bloom's Taxonomy and competency-based learning
- Experience with AI tutoring systems and adaptive learning platforms
We need to decide sections. Could have:
About the role
...
Responsibilities
...
Required Skills
...
Preferred Qualifications
...
Education & Experience
...
Nice-to-Have
...
But we need to avoid thin sections; Nice-to-Have may be considered thin but it's substantive. Could combine Preferred Qualifications and Education & Experience and Nice-to-Have into a single "Qualifications" section? But the instruction: Prefer a few substantive sections over many thin ones. So maybe combine all qualification-like info into one section "Qualifications". However we have distinct categories: Preferred Qualifications, Education & Experience, Nice-to-Have. Could combine them.
But we also have Required Skills separate.
Thus sections: About the role, Responsibilities, Required Skills, Qualifications (combining Preferred Qualifications, Education & Experience, Nice-to-Have). That's 4 sections.
We need to ensure we don't create sections with filler like "commensurate with experience". Not present.
We need to preserve all substantive info. So we need to include all bullet points from each category.
We need to format bullet points as - . For sub-bullets (like o Multiple Choice Questions) we can treat as
- inside same list or nested? The instruction: Use
- for any list of duties/requirements/benefits. It doesn't forbid nested lists. We can keep simple flat list; but we need to preserve the content. Could keep as separate
- lines.
For the "Develop assessment questions including: o Multiple Choice Questions (MCQs) o Scenario-based questions o Coding exercises o Capstone projects o Knowledge checks" we can make a
- that contains that sentence with the subitems maybe as a comma-separated list. Or we could break into nested
. Safer to keep as one - with the subitems separated by commas.
Similarly for "Programming JavaScript / TypeScript Node.js React.js Python REST APIs JSON" we can keep as one
- .
We need to avoid repeating job title as heading. Not needed.
We must not include markdown code fences. Just raw HTML.
Let's craft.
First, About the role paragraph: combine the intro paragraph.
Then Responsibilities: we need to list all responsibilities bullet points. Could group them under subheadings? Not required; just a list.
We'll create
with each responsibility as - . For the sub-bullets under each main bullet (like AI & Generative AI Development has multiple subpoints), we could either flatten: each subpoint as its own
- . That preserves detail.
Thus list:
- Design and implement "loop engineering" workflows using Claude Code and similar tools, defining how agents plan, execute, test, and iterate on code changes
- Architect Model Context Protocol (MCP) servers and tool schemas that are legible and safe for LLM agents to use
- Define human-in-the-loop checkpoints, autonomy boundaries, and rollback strategies for agent-driven changes
- Build evaluation harnesses and observability practices to measure agent output quality and catch regressions
- Design and review microservice and microfrontend architecture using C4 diagrams and Domain-Driven Design principles
- Drive test-driven development practices across teams, including contract testing between services
- Own technical decisions across our Java microservices, Node.js services, React/microfrontend UI, and Python tooling
- Design and develop hands-on lab activities, practical exercises, guided projects, and simulations.
- Create technical learning content for AI, cloud, software engineering, and emerging technologies.
- Develop assessment questions including: Multiple Choice Questions (MCQs), Scenario-based questions, Coding exercises, Capstone projects, Knowledge checks
- Utilize Claude and other AI tools to generate, review, and improve educational content.
- Align content with learning objectives, competency frameworks, and certification standards.
- Develop responsive web applications using React.js.
- Build backend services and APIs using Node.js and Express.js.
- Integrate AI services and LLM APIs into web applications.
- Design and implement secure RESTful APIs and microservices.
- Develop dashboards for content management, assessment reporting, and learner analytics.
That covers all.
Now Required Skills list: flatten each bullet.
List items:
- Generative AI Claude (Anthropic), OpenAI, Azure OpenAI
- Prompt Engineering
- AI Agent Development
- RAG Architecture
- Vector Databases
- LLM Evaluation & Testing
- MCP and Tool Integrations
- Programming JavaScript / TypeScript Node.js React.js Python REST APIs JSON
- AI Frameworks & Libraries LangChain LangGraph
- Databases PostgreSQL MongoDB Redis Vector Databases
- Front-End Development React.js HTML5 CSS3 Material UI / Bootstrap Responsive Design
- Backend Development Node.js Express.js Microservices Architecture Authentication & Authorization
Now Qualifications section: combine Preferred Qualifications, Education & Experience, Nice-to-Have.
List items:
- Experience creating learning content, labs, or certification preparation material.
- Experience with AI-based assessment generation and automated evaluation systems.
- Familiarity with Learning Management Systems (LMS).
- Experience building Agentic AI and multi-agent solutions.
- Understanding of instructional design principles.
- Experience working with educational technology platforms.
- Bachelor's or Master's degree in Computer Science, Information Technology, AI/ML, or related field.
- 7+ years of software development experience.
- 2+ years of Generative AI / LLM application development experience.
- Demonstrated experience creating AI-powered learning solutions, labs, or assessment content.
- Experience in Education Technology (EdTech)
- Knowledge of Bloom's Taxonomy and competency-based learning
- Experience with AI tutoring systems and adaptive learning platforms
We should ensure no duplication: "Demonstrated experience creating AI-powered learning solutions, labs, or assessment content." appears also in Education & Experience; it's fine.
Now output HTML fragment.
We need to wrap each section in
heading and then content.
Let's produce:
About the role
We are seeking a highly skilled AI Engineer who can define and scale how our engineering organization builds simulation software with AI agents. This role requires deep fluency in "loop engineering" with tools like Claude Code: designing the feedback loops, guardrails, and workflows that let AI agents safely and effectively contribute to production codebases. You'll need to understand the full agentic software development lifecycle, from context design through evaluation, deployment, and observability, while also being a hands-on expert across our core stack. This is a
- for any list of duties/requirements/benefits. Use
for prose. We need to preserve all substantive information, not invent or summarize away detail. Remove boilerplate etc. There's no cookie/navigation etc. We need to include sections only when posting has real specific content. So we can have sections: About the role (intro paragraph), Responsibilities (maybe combine key responsibilities, learning content, full stack dev), Required Skills (skills), Preferred Qualifications (preferred quals + education & experience + nice-to-have maybe). Could split into Qualifications and Preferred Qualifications. But we need to avoid thin sections. Let's think. We have: - Intro paragraph: "We are seeking a highly skilled AI Engineer who can define and scale how our engineering organization builds simulation software with AI agents. This role requires deep fluency in 'loop engineering' with tools like Claude Code: designing the feedback loops, guardrails, and workflows that let AI agents safely and effectively contribute to production codebases. You'll need to understand the full agentic software development lifecycle, from context design through evaluation, deployment, and observability, while also being a hands-on expert across our core stack. This is a staff-level role: you'll collaborate with other engineers to set technical direction, define best practices for agentic development across teams, and remain deeply hands-on in architecture and code." That's substantive. Then "Key Responsibilities:" with bullet list items: - AI & Generative AI Development - Design and implement "loop engineering" workflows using Claude Code and similar tools, defining how agents plan, execute, test, and iterate on code changes - Architect Model Context Protocol (MCP) servers and tool schemas that are legible and safe for LLM agents to use - Define human-in-the-loop checkpoints, autonomy boundaries, and rollback strategies for agent-driven changes - Build evaluation harnesses and observability practices to measure agent output quality and catch regressions - Design and review microservice and microfrontend architecture using C4 diagrams and Domain-Driven Design principles - Drive test-driven development practices across teams, including contract testing between services - Own technical decisions across our Java microservices, Node.js services, React/microfrontend UI, and Python tooling - Learning Content & Assessment Development - Design and develop hands-on lab activities, practical exercises, guided projects, and simulations. - Create technical learning content for AI, cloud, software engineering, and emerging technologies. - Develop assessment questions including: o Multiple Choice Questions (MCQs) o Scenario-based questions o Coding exercises o Capstone projects o Knowledge checks - Utilize Claude and other AI tools to generate, review, and improve educational content. - Align content with learning objectives, competency frameworks, and certification standards. - Full Stack Development - Develop responsive web applications using React.js. - Build backend services and APIs using Node.js and Express.js. - Integrate AI services and LLM APIs into web applications. - Design and implement secure RESTful APIs and microservices. - Develop dashboards for content management, assessment reporting, and learner analytics. Then "Required Skills:" with list: - Generative AI Claude (Anthropic), OpenAI, Azure OpenAI - Prompt Engineering - AI Agent Development - RAG Architecture - Vector Databases - LLM Evaluation & Testing - MCP and Tool Integrations - Programming JavaScript / TypeScript Node.js React.js Python REST APIs JSON - AI Frameworks & Libraries LangChain LangGraph - Databases PostgreSQL MongoDB Redis Vector Databases - Front-End Development React.js HTML5 CSS3 Material UI / Bootstrap Responsive Design - Backend Development Node.js Express.js Microservices Architecture Authentication & Authorization Then "Preferred Qualifications:" list: - Experience creating learning content, labs, or certification preparation material. - Experience with AI-based assessment generation and automated evaluation systems. - Familiarity with Learning Management Systems (LMS). - Experience building Agentic AI and multi-agent solutions. - Understanding of instructional design principles. - Experience working with educational technology platforms. Then "Education & Experience:" list: - Bachelor's or Master's degree in Computer Science, Information Technology, AI/ML, or related field. - 7+ years of software development experience. - 2+ years of Generative AI / LLM application development experience. - Demonstrated experience creating AI-powered learning solutions, labs, or assessment content. Then "Nice-to-Have:" list: - Experience in Education Technology (EdTech) - Knowledge of Bloom's Taxonomy and competency-based learning - Experience with AI tutoring systems and adaptive learning platforms We need to decide sections. Could have:
About the role
...
Responsibilities
- ...
Required Skills
- ...
Preferred Qualifications
- ...
Education & Experience
- ...
Nice-to-Have
- ...
- . For sub-bullets (like o Multiple Choice Questions) we can treat as
- inside same list or nested? The instruction: Use
- for any list of duties/requirements/benefits. It doesn't forbid nested lists. We can keep simple flat list; but we need to preserve the content. Could keep as separate
- lines. For the "Develop assessment questions including: o Multiple Choice Questions (MCQs) o Scenario-based questions o Coding exercises o Capstone projects o Knowledge checks" we can make a
- that contains that sentence with the subitems maybe as a comma-separated list. Or we could break into nested
- . Safer to keep as one
- with the subitems separated by commas. Similarly for "Programming JavaScript / TypeScript Node.js React.js Python REST APIs JSON" we can keep as one
- .
We need to avoid repeating job title as heading. Not needed.
We must not include markdown code fences. Just raw HTML.
Let's craft.
First, About the role paragraph: combine the intro paragraph.
Then Responsibilities: we need to list all responsibilities bullet points. Could group them under subheadings? Not required; just a list.
We'll create
- with each responsibility as
- . For the sub-bullets under each main bullet (like AI & Generative AI Development has multiple subpoints), we could either flatten: each subpoint as its own
- . That preserves detail.
Thus list:
- Design and implement "loop engineering" workflows using Claude Code and similar tools, defining how agents plan, execute, test, and iterate on code changes
- Architect Model Context Protocol (MCP) servers and tool schemas that are legible and safe for LLM agents to use
- Define human-in-the-loop checkpoints, autonomy boundaries, and rollback strategies for agent-driven changes
- Build evaluation harnesses and observability practices to measure agent output quality and catch regressions
- Design and review microservice and microfrontend architecture using C4 diagrams and Domain-Driven Design principles
- Drive test-driven development practices across teams, including contract testing between services
- Own technical decisions across our Java microservices, Node.js services, React/microfrontend UI, and Python tooling
- Design and develop hands-on lab activities, practical exercises, guided projects, and simulations.
- Create technical learning content for AI, cloud, software engineering, and emerging technologies.
- Develop assessment questions including: Multiple Choice Questions (MCQs), Scenario-based questions, Coding exercises, Capstone projects, Knowledge checks
- Utilize Claude and other AI tools to generate, review, and improve educational content.
- Align content with learning objectives, competency frameworks, and certification standards.
- Develop responsive web applications using React.js.
- Build backend services and APIs using Node.js and Express.js.
- Integrate AI services and LLM APIs into web applications.
- Design and implement secure RESTful APIs and microservices.
- Develop dashboards for content management, assessment reporting, and learner analytics.
That covers all.
Now Required Skills list: flatten each bullet.
List items:
- Generative AI Claude (Anthropic), OpenAI, Azure OpenAI
- Prompt Engineering
- AI Agent Development
- RAG Architecture
- Vector Databases
- LLM Evaluation & Testing
- MCP and Tool Integrations
- Programming JavaScript / TypeScript Node.js React.js Python REST APIs JSON
- AI Frameworks & Libraries LangChain LangGraph
- Databases PostgreSQL MongoDB Redis Vector Databases
- Front-End Development React.js HTML5 CSS3 Material UI / Bootstrap Responsive Design
- Backend Development Node.js Express.js Microservices Architecture Authentication & Authorization
Now Qualifications section: combine Preferred Qualifications, Education & Experience, Nice-to-Have.
List items:
- Experience creating learning content, labs, or certification preparation material.
- Experience with AI-based assessment generation and automated evaluation systems.
- Familiarity with Learning Management Systems (LMS).
- Experience building Agentic AI and multi-agent solutions.
- Understanding of instructional design principles.
- Experience working with educational technology platforms.
- Bachelor's or Master's degree in Computer Science, Information Technology, AI/ML, or related field.
- 7+ years of software development experience.
- 2+ years of Generative AI / LLM application development experience.
- Demonstrated experience creating AI-powered learning solutions, labs, or assessment content.
- Experience in Education Technology (EdTech)
- Knowledge of Bloom's Taxonomy and competency-based learning
- Experience with AI tutoring systems and adaptive learning platforms
We should ensure no duplication: "Demonstrated experience creating AI-powered learning solutions, labs, or assessment content." appears also in Education & Experience; it's fine.
Now output HTML fragment.
We need to wrap each section in
heading and then content. Let's produce:
About the role
We are seeking a highly skilled AI Engineer who can define and scale how our engineering organization builds simulation software with AI agents. This role requires deep fluency in "loop engineering" with tools like Claude Code: designing the feedback loops, guardrails, and workflows that let AI agents safely and effectively contribute to production codebases. You'll need to understand the full agentic software development lifecycle, from context design through evaluation, deployment, and observability, while also being a hands-on expert across our core stack. This is a