Sr. Engineer, AI Applications
for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We have location, description, essential functions (responsibilities), required qualifications, preferred qualifications, salary range. Also maybe "About the role" from first paragraph. We'll need to map. We must not repeat job title as heading. No Job ID. Remove boilerplate: EEO, equal opportunity, etc. Also remove "Note To Recruiters" etc. Also remove "Location: San Jose, CA (On-site)" maybe we keep as a short paragraph? It's location info; we can include in a
maybe under About the role? The instruction: "Do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short
or drop it." So location can be a short
. We'll include location as a paragraph before sections maybe. We need to preserve all substantive information; do not invent or summarize away detail. So we need to include all essential functions bullet points, required qualifications bullet points, preferred qualifications bullet points, salary range. We must not create sections like Benefits, Pay, Schedule unless posting actually states them. Pay is stated: Salary range: $150,000 - $192,000. So we can include a Pay section with that. Benefits not mentioned, so omit. Schedule not mentioned (though location says On-site, but that's location not schedule). So omit Schedule. We need sections: About the role (intro paragraph), Responsibilities (Essential Functions), Requirements (maybe Required Qualifications?), Qualifications (maybe Preferred Qualifications?), Skills (maybe combine programming fluency etc? But we have required qualifications includes programming fluency etc. Could put under Skills. But we must not create thin sections. Let's think: The posting includes "Required Qualifications" with education, experience, AI/LLM experience, agentic tooling, cross-functional communication, track record, self-direction, programming fluency, devOps fundamentals. Also "Preferred Qualifications" with security & IP awareness, master's preferred, evaluation and guardrails, deep-tech background. We could map: About the role (intro), Responsibilities (Essential Functions), Requirements (Required Qualifications), Qualifications (Preferred Qualifications), Skills (maybe combine programming fluency and devops fundamentals? But those are already in Required Qualifications. Might be redundant. Better to have sections: About the role, Responsibilities, Requirements (covers required qualifications), Preferred Qualifications (maybe as Qualifications?), Skills (maybe not needed). But we need to follow instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It says "e.g." meaning those are examples; we can use those headings if we have content. We should not create empty sections. So we need to decide which headings we will use with actual content. We have content for About the role (intro). Responsibilities (Essential Functions). Requirements (Required Qualifications). Qualifications (Preferred Qualifications). Skills? Could we extract skills like programming fluency, devops fundamentals as separate? But they are part of required qualifications; we could still put them under Skills heading, but then we would duplicate content. Better to put them under Requirements (since they are qualifications). The instruction: "Prefer a few substantive sections over many thin ones." So we can combine Required Qualifications and Skills into one Requirements section. And Preferred Qualifications could be a Qualifications section. That seems reasonable. Pay section: salary range. Thus sections: About the role, Responsibilities, Requirements, Qualifications, Pay. We need to output HTML fragment only, no /. Use
for each heading. Use - for any list of duties/requirements/benefits. Use
for prose.
We need to preserve all substantive information: location, intro paragraph, essential functions bullet points, required qualifications bullet points (including sub-items?), preferred qualifications bullet points, salary range.
We must not include boilerplate like EEO, note to recruiters, etc.
We need to ensure we don't invent or summarize away detail. So we need to keep each bullet point as is.
Let's extract the intro paragraph: "Location: San Jose, CA (On-site) Ayar Labs is shattering AI data bottlenecks by moving data at the speed of light. As pioneers of co-packaged optics (CPO), we are using light instead of electricity to move data faster, further, and with a fraction of the energy needed to fuel the explosive growth of AI models. Backed by industry giants like NVIDIA, AMD, Mediatek and Intel and manufactured in partnership with the world’s leading semiconductor ecosystem, Ayar Labs’ co-packaged optics solution is key to unleashing next-generation AI scale-up architectures. This AI Application Engineer is a builder who turns AI into tools our Ayar Labs employees actually use. You will design, build, and deploy tools that put AI directly into the hands of engineering, operations, and business teams who know their own work, but aren't software or AI specialists. This is a self-motivated individual contributor role for someone with hands-on experience who can take a vague request and turn it into a working, reliable tool. You will partner closely with stakeholders across the business, and with the rest of IT, to build AI-powered tools that will actually move the needle. Beyond building, you will help shape the standards, processes, and infrastructure this new AI function uses to grow, leveraging modern DevOps tooling alongside LLM and AI APIs to ship solutions that hold up in production."
We can keep location as a short
maybe before About the role? Or incorporate location into About the role paragraph. The instruction: "Do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short
or drop it." So location is minor metadata; we can make a short
for location. Then About the role heading with the rest.
Thus:
Location: San Jose, CA (On-site)
About the role
[the rest of intro paragraph without location]
Now Responsibilities: Essential Functions bullet points list:
- Be the Go-To for AI Tooling: Serve as a primary builder for AI-powered internal tools, turning requests from across the company into scoped, working solutions.
- Design and Ship AI-Powered Applications: Build the apps, dashboards, services, and interfaces that put AI capabilities directly in front of users, so they can get their work done without needing to understand how the AI works.
- Integrate LLM and AI APIs: Connect tools such as OpenAI, Anthropic, Gemini, or open weight models into real company workflows and data sources, so the AI is doing useful work rather than sitting in a demo.
- Own the Infrastructure Behind It: Build and maintain the pipelines, containerized deployments, infrastructure automation, and monitoring these tools run on, so what you ship keeps working after launch.
- Support the People Using What You Build: Troubleshoot issues directly with users, and drive adoption through documentation and training people will actually use.
- Track the AI Landscape: Evaluate new AI tools, platforms, and vendors for opportunities which fit our company needs.
We need to preserve exactly as given. Use - .
Now Requirements: Required Qualifications bullet points:
Education: Bachelor's degree in computer science, software engineering, electrical engineering, computer engineering, mathematics, physics, or another STEM or engineering field.
Experience: 2+ years in software engineering, DevOps, or platform engineering. Strong independent projects, internships, or open-source contributions are encouraged to apply.
AI/LLM Application Experience: Hands-on experience working across model APIs — Anthropic, OpenAI, Gemini, and open weight models — building a range of AI-powered tools such as chat and assistant interfaces, document processing and summarization, workflow automation, or code-generation tooling.
Agentic Tooling & Judgment: Experience building AI skills that can be shared across teams and the organization, and MCP (Model Context Protocol) servers that support technical users. Sound judgment on when to rely on the tools already built into major frontier model apps and when it's worth building something custom instead.
Cross-Functional Communication: Strong written and verbal skills, with the ability to translate a request from someone outside software or AI into a working tool.
Track Record of Shipping: A history of building internal tools or applications that other people actually use, not coursework or personal experiments alone.
Self-Direction: Comfortable operating without an existing playbook, and motivated by the chance to help write one.
Programming Fluency: Working proficiency in Python, plus at least one of JavaScript/TypeScript, Go, or a similar modern language.
DevOps Fundamentals: Comfort with the tools that keep applications running in production — version control, CI/CD, containerization and orchestration, infrastructure-as-code, and monitoring. Cloud platform experience (AWS, Azure, or GCP) is a plus.
We need to keep each bullet as
- . Possibly we could keep the bold headings inside li? The original had bold headings like **Education:** etc. We should preserve the text exactly, including the bold markers? The original uses ** for bold. In plain text we can keep the asterisks? The instruction: preserve ALL substantive information; do not invent or summarize away detail. So we should keep the asterisks as they appear. So each
- will contain the line exactly as in posting, including the asterisks.
Now Qualifications: Preferred Qualifications bullet points:
- Security & IP Awareness: Thoughtful about data handling, access control, and IP protection when introducing AI tools into a company that guards sensitive engineering and manufacturing data
- A master's or other postgraduate degree is preferred.
- Evaluation and Guardrails: Experience testing and evaluating AI-powered features, and building in the guardrails that keep them reliable and safe for internal users.
- Deep-Tech Background: Prior experience at a hardware, semiconductor, or deep-tech company, or another environment with highly technical, non-software users.
We need to preserve exactly.
Now Pay: Salary range: $150,000 - $192,000
We can put as
Salary range: $150,000 - $192,000
under Pay
.
We must not include Benefits or Schedule.
Now ensure we removed boilerplate: "Note To Recruiters Principals only..." etc. Also EEO statement. Also "Remuneration for recruiting activities..." etc. Also "Ayar Labs is an Equal Opportunity Employer..." etc. Also "Veterans are more than welcome..." etc. All removed.
Now output HTML fragment.
Let's construct:
Location: San Jose, CA (On-site)
About the role
Ayar Labs is shattering AI data bottlenecks by moving data at the speed of light. As pioneers of co-packaged optics (CPO), we are using light instead of electricity to move data faster, further, and with a fraction of the energy needed to fuel the explosive growth of AI models. Backed by industry giants like NVIDIA, AMD, Mediatek and Intel and manufactured in partnership with the world’s leading semiconductor ecosystem, Ayar Labs’ co-packaged optics solution is key to unleashing next-generation AI scale-up architectures. This AI Application Engineer is a builder who turns AI into tools our Ayar Labs employees actually use. You will design, build, and deploy tools that put AI directly into the hands of engineering, operations, and business teams who know their own work, but aren't software or AI specialists. This is a self-motivated individual contributor role for someone with hands-on experience who can take a vague request and turn it into a working, reliable tool. You will partner closely with stakeholders across the business, and with the rest of IT, to build AI-powered tools that will actually move the needle. Beyond building, you will help shape the standards, processes, and infrastructure this new AI function uses to grow, leveraging modern DevOps tool
for prose. We need to preserve all substantive information: location, intro paragraph, essential functions bullet points, required qualifications bullet points (including sub-items?), preferred qualifications bullet points, salary range. We must not include boilerplate like EEO, note to recruiters, etc. We need to ensure we don't invent or summarize away detail. So we need to keep each bullet point as is. Let's extract the intro paragraph: "Location: San Jose, CA (On-site) Ayar Labs is shattering AI data bottlenecks by moving data at the speed of light. As pioneers of co-packaged optics (CPO), we are using light instead of electricity to move data faster, further, and with a fraction of the energy needed to fuel the explosive growth of AI models. Backed by industry giants like NVIDIA, AMD, Mediatek and Intel and manufactured in partnership with the world’s leading semiconductor ecosystem, Ayar Labs’ co-packaged optics solution is key to unleashing next-generation AI scale-up architectures. This AI Application Engineer is a builder who turns AI into tools our Ayar Labs employees actually use. You will design, build, and deploy tools that put AI directly into the hands of engineering, operations, and business teams who know their own work, but aren't software or AI specialists. This is a self-motivated individual contributor role for someone with hands-on experience who can take a vague request and turn it into a working, reliable tool. You will partner closely with stakeholders across the business, and with the rest of IT, to build AI-powered tools that will actually move the needle. Beyond building, you will help shape the standards, processes, and infrastructure this new AI function uses to grow, leveraging modern DevOps tooling alongside LLM and AI APIs to ship solutions that hold up in production." We can keep location as a short
maybe before About the role? Or incorporate location into About the role paragraph. The instruction: "Do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short
or drop it." So location is minor metadata; we can make a short
for location. Then About the role heading with the rest. Thus:
Location: San Jose, CA (On-site)
About the role
[the rest of intro paragraph without location]
Now Responsibilities: Essential Functions bullet points list: - Be the Go-To for AI Tooling: Serve as a primary builder for AI-powered internal tools, turning requests from across the company into scoped, working solutions. - Design and Ship AI-Powered Applications: Build the apps, dashboards, services, and interfaces that put AI capabilities directly in front of users, so they can get their work done without needing to understand how the AI works. - Integrate LLM and AI APIs: Connect tools such as OpenAI, Anthropic, Gemini, or open weight models into real company workflows and data sources, so the AI is doing useful work rather than sitting in a demo. - Own the Infrastructure Behind It: Build and maintain the pipelines, containerized deployments, infrastructure automation, and monitoring these tools run on, so what you ship keeps working after launch. - Support the People Using What You Build: Troubleshoot issues directly with users, and drive adoption through documentation and training people will actually use. - Track the AI Landscape: Evaluate new AI tools, platforms, and vendors for opportunities which fit our company needs. We need to preserve exactly as given. Use- . Now Requirements: Required Qualifications bullet points: Education: Bachelor's degree in computer science, software engineering, electrical engineering, computer engineering, mathematics, physics, or another STEM or engineering field. Experience: 2+ years in software engineering, DevOps, or platform engineering. Strong independent projects, internships, or open-source contributions are encouraged to apply. AI/LLM Application Experience: Hands-on experience working across model APIs — Anthropic, OpenAI, Gemini, and open weight models — building a range of AI-powered tools such as chat and assistant interfaces, document processing and summarization, workflow automation, or code-generation tooling. Agentic Tooling & Judgment: Experience building AI skills that can be shared across teams and the organization, and MCP (Model Context Protocol) servers that support technical users. Sound judgment on when to rely on the tools already built into major frontier model apps and when it's worth building something custom instead. Cross-Functional Communication: Strong written and verbal skills, with the ability to translate a request from someone outside software or AI into a working tool. Track Record of Shipping: A history of building internal tools or applications that other people actually use, not coursework or personal experiments alone. Self-Direction: Comfortable operating without an existing playbook, and motivated by the chance to help write one. Programming Fluency: Working proficiency in Python, plus at least one of JavaScript/TypeScript, Go, or a similar modern language. DevOps Fundamentals: Comfort with the tools that keep applications running in production — version control, CI/CD, containerization and orchestration, infrastructure-as-code, and monitoring. Cloud platform experience (AWS, Azure, or GCP) is a plus. We need to keep each bullet as
- . Possibly we could keep the bold headings inside li? The original had bold headings like **Education:** etc. We should preserve the text exactly, including the bold markers? The original uses ** for bold. In plain text we can keep the asterisks? The instruction: preserve ALL substantive information; do not invent or summarize away detail. So we should keep the asterisks as they appear. So each
- will contain the line exactly as in posting, including the asterisks.
Now Qualifications: Preferred Qualifications bullet points:
- Security & IP Awareness: Thoughtful about data handling, access control, and IP protection when introducing AI tools into a company that guards sensitive engineering and manufacturing data
- A master's or other postgraduate degree is preferred.
- Evaluation and Guardrails: Experience testing and evaluating AI-powered features, and building in the guardrails that keep them reliable and safe for internal users.
- Deep-Tech Background: Prior experience at a hardware, semiconductor, or deep-tech company, or another environment with highly technical, non-software users.
We need to preserve exactly.
Now Pay: Salary range: $150,000 - $192,000
We can put as
Salary range: $150,000 - $192,000
underPay
. We must not include Benefits or Schedule. Now ensure we removed boilerplate: "Note To Recruiters Principals only..." etc. Also EEO statement. Also "Remuneration for recruiting activities..." etc. Also "Ayar Labs is an Equal Opportunity Employer..." etc. Also "Veterans are more than welcome..." etc. All removed. Now output HTML fragment. Let's construct:Location: San Jose, CA (On-site)
About the role
Ayar Labs is shattering AI data bottlenecks by moving data at the speed of light. As pioneers of co-packaged optics (CPO), we are using light instead of electricity to move data faster, further, and with a fraction of the energy needed to fuel the explosive growth of AI models. Backed by industry giants like NVIDIA, AMD, Mediatek and Intel and manufactured in partnership with the world’s leading semiconductor ecosystem, Ayar Labs’ co-packaged optics solution is key to unleashing next-generation AI scale-up architectures. This AI Application Engineer is a builder who turns AI into tools our Ayar Labs employees actually use. You will design, build, and deploy tools that put AI directly into the hands of engineering, operations, and business teams who know their own work, but aren't software or AI specialists. This is a self-motivated individual contributor role for someone with hands-on experience who can take a vague request and turn it into a working, reliable tool. You will partner closely with stakeholders across the business, and with the rest of IT, to build AI-powered tools that will actually move the needle. Beyond building, you will help shape the standards, processes, and infrastructure this new AI function uses to grow, leveraging modern DevOps tool