Lead AI Software Engineer

We need to output HTML fragment with sections: h3 headings for sections present: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must only include sections that have real specific content. We need to parse the posting. We have details: Date posted, hiring org, position number, industry, job title, location, work model hybrid, shift, employment type temporary FT, duration 12 months, min hourly rate 80, max 85. Must have skills list. Experience desired list. Required minimum education Bachelor's. Job description includes required education/experience, required technical skills, required soft skills, summary of role, technical leadership & workflow optimization, influence across teams & champion developer experience, interaction with team, core software engineering. We need to produce sections: maybe "About the role" (summary), "Responsibilities" (list of duties), "Requirements" (must have skills/attributes, experience desired), "Qualifications" (education, maybe required technical skills?), "Skills" (maybe combine technical and soft skills?), "Benefits" (there's a Benefits line but just says "For information and details on employment benefits offered with this position, please visit here." That's not specific content; it's a placeholder. According to rule: never create Benefits section unless posting actually states them. It does not state actual benefits, just a link. So we should not include Benefits. Pay: we have min and max hourly rate. That is specific. So we can include Pay section with that info. Schedule: we have shift: 9:00 a.m. to 5 p.m, work model hybrid 2 days a week in office. That's schedule info. So include Schedule. We must not repeat job title as heading. Also not include Job ID/requisition numbers as headings; fold minor metadata into short p or drop it. So we can include a short p with date posted, hiring org, location, etc maybe. We need to preserve all substantive information; do not invent or summarize away detail. So we need to include all details from the posting, but we can organize into sections. We must not include boilerplate like EEO, E-Verify, etc. Remove those. We need to use

for section headings. Use

• for any list of duties/requirements/benefits. Use

  for prose. We need to decide sections. Potential sections: - About the role: could be summary of role (Summary Of Role paragraph). Could also include work model details? But schedule separate. - Responsibilities: list of duties from "Lead architectural designs and able to work across teams to come up with solutions." plus items under Summary Of Role, Technical Leadership & Workflow Optimization, Influence Across Teams & Champion Developer Experience, Interaction With Team, Core Software Engineering. Those are responsibilities. - Requirements: Must Have Skills/Attributes list, Experience Desired list, maybe also Required Minimum Education? But education could be Qualifications. - Qualifications: Required Minimum Education (Bachelor’s Degree), maybe also Required Education/Experience (Bachelor’s degree in Computer science or Electrical engineering or related field). Also maybe "Required Technical Skills" could be under Skills. - Skills: Could list technical skills (Java, API, AWS, LLM, Microservices, RAG, etc) plus soft skills. But we need to avoid duplication. The instruction: "Prefer a few substantive sections over many thin ones." So maybe we combine. We could have sections: About the role, Responsibilities, Requirements, Qualifications, Pay, Schedule. We need to include all substantive info. Let's extract details: Metadata: - Date Posted: 09/15/2026 - Hiring Organization: Rose International - Position Number: 507554 (drop as minor metadata) - Industry: Manufacturing - Job Title: Lead AI Software Engineer (not heading) - Job Location: Chicago, IL, USA, 60661 - Work Model: Hybrid Work Model Details: 2 days a week in office - Shift: 9:00 a.m. to 5 p.m - Employment Type: Temporary FT/PT: Full-Time - Estimated Duration (In months): 12 - Min Hourly Rate($): 80.00 - Max Hourly Rate($): 85.00 Must Have Skills/Attributes: AI, API, AWS, Java, LLM (Large Language Model), Microservices, RAG (Retrieval-Augmented Generation) Experience Desired: - Java Backend Development, Microservices & API Architecture (10+ yrs) - Software Architecture & Large-Scale Distributed Systems (8+ yrs) - AWS Cloud, Docker & Kubernetes (Cloud-Native Development) (8+ yrs) - Generative AI, LLMs, AI Agents, Prompt Engineering & RAG (LangChain/LangGraph/AutoGen/CrewAI) (3+ yrs) - Technical Leadership, Engineering Governance & Mentoring Multiple Teams (2+ yrs) Required Minimum Education: Bachelor’s Degree Job Description Required Education/Experience: Bachelor’s degree in Computer science or Electrical engineering or related field Required Technical Skills: - 8+ years of professional software engineering experience and 2+ years in a technical leadership role. - Proven experience designing and delivering large-scale distributed systems. - Strong expertise in software architecture, APIs, microservices, cloud-native applications, and modern engineering practices. - Experience influencing multiple engineering teams and leading organization-wide technical initiatives. - Strong communication, collaboration, and stakeholder management skills. - Demonstrated ability to mentor engineers and drive technical excellence. - Experience with Generative AI, AI agents, LLM-powered applications, or intelligent automation platforms. - Experience with AI development tools, coding assistants, and modern developer productivity platforms. - Knowledge of security architecture, application security, and cloud security best practices. - Experience establishing technical governance and engineering standards across multiple teams. Required Soft Skills: - Ability to work under pressure and within time constraints - Passion for technology and an eagerness to contribute to a team-oriented environment - Lead architectural designs and able to work across teams to come up with solutions. Summary Of Role: - Design and orchestrate multi-agent workflows and stateful AI systems using modern frameworks like LangChain, LangGraph, AutoGen, or CrewAI. - Integrate foundation models (e.g., Anthropic Claude, OpenAI GPT, Google Gemini) via secure API gateways, managing token limits, costs, and rate-limiting. - Architect data models optimized for AI-native structures, integrating relational databases with vector databases for semantic search and Retrieval-Augmented Generation (RAG). - Implement robust white-box testing and continuous evaluation metrics to monitor AI outputs for factual correctness, hallucinations, and safety compliance. - Champion secure, reliable, and scalable software solutions through architectural leadership, risk management, and continuous improvement of engineering practices. Technical Leadership & Workflow Optimization: - Mentor and scale an engineering team, establishing engineering standards, best practices and architectural governance for secure coding, continuous integration, and cloud-native deployment. - Drive AI-assisted engineering velocity by integrating next-gen development tools (e.g., Cursor, Claude Code, Windsurf) into the team's daily Software Development Life Cycle (SDLC). - Establish governance policies and coach developers on the responsible use of AI, focusing on input data sensitivity, license compliance, and security guardrails. - Evaluate existing systems, services, APIs, and data models to identify opportunities for modernization, scalability, and performance improvements. Influence Across Teams & Champion Developer Experience: - Facilitate technical leadership forums with Product Owners, Technical Leads, Architects, and Engineering Managers. - Drive conversations around architecture, engineering health, technical debt, AI adoption, and continuous improvement. - Mentor engineers and technical leaders on system design, software architecture, and engineering excellence. - Foster collaborative decision-making through architecture reviews, RFCs, and technical discussions. - Promote self-service engineering capabilities and platform enablement. - Drive automation initiatives that improve productivity and software quality. Interaction With Team: - Significant interaction required with Scrum team. - Interaction during all scrum ceremonies such as Daily Standups, Sprint Planning, Grooming, Retro, Demo etc - Also need to interact with team for PR Reviews, also need to engage with other teams as needed. Core Software Engineering: - Backend Systems: Deep proficiency in backend environments, microservices architectures, and API design using Java. - Cloud & DevOps: Extensive experience with containerization (Docker, Kubernetes) and public cloud infrastructure like AWS - AI & LLM Infrastructure Orchestration & Tooling: Hands-on experience with production-level AI agents, prompt engineering, and advanced Agentic PDLC patterns. - Vector Databases: Practical knowledge of vector technologies such as Pinecone, Milvus, Chroma, or pgvector. - AI Tool Fluency: Demonstrated mastery of AI coding assistants and a firm understanding of Model Context Protocol (MCP) to mediate agent connections with external databases. Benefits: just a link, not specific -> omit. Pay: min 80, max 85 hourly. Schedule: shift 9-5, hybrid 2 days in office. We also have employment type temporary FT, duration 12 months. Could include in About the role or maybe a separate section? Not listed as a heading option but we could include in About the role as prose. We must not invent sections like "Employment Type" unless we have heading for it; but we can include that info in About the role paragraph. Now produce HTML. We need to wrap content in appropriate tags. We'll start with a

  for metadata: maybe combine date posted, hiring org, location, industry, employment type, duration. Then sections. Let's craft:

  Posted 09/15/2026 by Rose International. Location: Chicago, IL 60661. Industry: Manufacturing. Employment type: Temporary Full‑Time (12‑month contract).

  Then

  About the role

  with a

  summarizing the role: maybe combine Summary Of Role and some high-level description. But we must not repeat job title as heading; we can still mention it in paragraph. We need to preserve all substantive info; we can't omit details. So we need to include all bullet points from responsibilities etc. We'll create

  Responsibilities

  with a
  containing each responsibility item. We need to break down into items. We have many responsibility statements; we can list them as
  • items. Let's compile responsibilities list: - Design and orchestrate multi-agent workflows and stateful AI systems using modern frameworks like LangChain, LangGraph, AutoGen, or CrewAI. - Integrate foundation models (e.g., Anthropic Claude, OpenAI GPT, Google Gemini) via secure API gateways, managing token limits, costs, and rate-limiting. - Architect data models optimized for AI-native structures, integrating relational databases with vector databases for semantic search and Retrieval-Augmented Generation (RAG). - Implement robust white-box testing and continuous evaluation metrics to monitor AI outputs for factual correctness, hallucinations, and safety compliance. - Champion secure, reliable, and scalable software solutions through architectural leadership, risk management, and continuous improvement of engineering practices. - Mentor and scale an engineering team, establishing engineering standards, best practices and architectural governance for secure coding, continuous integration, and cloud-native deployment. - Drive AI-assisted engineering velocity by integrating next-gen development tools (e.g., Cursor, Claude Code, Windsurf) into the team's daily Software Development Life Cycle (SDLC). - Establish governance policies and coach developers on the responsible use of AI, focusing on input data sensitivity, license compliance, and security guardrails. - Evaluate existing systems, services, APIs, and data models to identify opportunities for modernization, scalability, and performance improvements. - Facilitate technical leadership forums with Product Owners, Technical Leads, Architects, and Engineering Managers. - Drive conversations around architecture, engineering health, technical debt, AI adoption, and continuous improvement. - Mentor engineers and technical leaders on system design, software architecture, and engineering excellence. - Foster collaborative decision-making through architecture reviews, RFCs, and technical discussions. - Promote self-service engineering capabilities and platform enablement