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Senior AI Application Developer

Silgan · Brookfield, WI · Full time

Posted Sep 2, 2026 · We last checked this listing on Oct 5, 2026

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Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

About your past

Tell me about a production AI application you designed, built and supported after launch. What broke once real users got it?

What they are checking: Whether they have shipped and maintained real AI systems, not just demos, and learned from what went wrong.

Part of this role is building AI engineering skills across the wider development team. How have you helped other developers get up to speed?

What they are checking: Whether they can mentor and set patterns others follow, since the posting wants durable team expertise.

Tell me about a time an AI feature gave users a confidently wrong answer. How did you find it and fix it?

What they are checking: Whether they take hallucination seriously and build ways to catch and reduce it in production.

What would you do

We already have an AI platform in pre-production. What would you look at first to decide what needs hardening before it goes live?

What they are checking: Whether they think about security, evaluation, monitoring and failure modes before adding new features.

A plant manager asks for an AI tool that you think would be unreliable for their problem. How do you handle that conversation?

What they are checking: Whether they can push back honestly and steer toward something that works instead of building what's asked blindly.

About the work

How would you design a knowledge retrieval system so plant employees get accurate answers from manuals, SOPs and enterprise data?

What they are checking: Whether they understand chunking, retrieval quality, grounding and citations well enough to keep answers trustworthy.

How do you evaluate whether a retrieval or agent workflow is actually getting better from one version to the next?

What they are checking: Whether they build test sets and measurable checks instead of judging quality by a few hand-picked examples.

Walk me through how you'd build an agentic workflow that takes actions in an enterprise system like an ERP. What guardrails would you put in?

What they are checking: Whether they limit what an agent can do, add human approval where it matters and log every action.

How do you handle access control so an AI assistant doesn't show someone data they aren't allowed to see?

What they are checking: Whether they carry user permissions through retrieval, which is a common and serious gap in enterprise AI.

What does responsible AI governance look like to you in day-to-day engineering work?

What they are checking: Whether they turn governance into concrete practices like logging, review and data handling, not just policy talk.

How do you keep costs and latency under control when an application calls large language models many times per request?

What they are checking: Whether they think about caching, model choice and call design, which matters at global manufacturing scale.

Practice this interview out loud.

Offer builds a real interview for this exact role at Silgan from your resume and this job description, asks the questions one at a time, and tells you what landed. The first one is free.

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The full job description

As published by Silgan.

Senior AI Application Developer Waukesha, Wisconsin * Applicants must be legally authorized to work in the United States on a permanent basis. The Company is unable to provide employment visa sponsorship for this position now or in the future. Build the AI Applications Shaping the Future of Manufacturing Silgan is seeking a Senior AI Application Developer to help advance our enterprise AI transformation across a global manufacturing organization. This is a hands-on engineering role for an experienced developer who can design, build, deploy, and support production-grade AI applications that connect employees to the data, knowledge, and insights they need to make faster, better decisions. You will work across intelligent knowledge retrieval, agentic workflow automation, enterprise system integration, and responsible AI governance. A working AI platform is already in pre-production, giving you the opportunity to expand and harden real capabilities from day one while helping build durable AI engineering expertise across the broader development team. Why Join Silgan? At Silgan, employees are part of a financially strong, global packaging leader supporting many of the world’s most recognized consumer brands. Our Business Technology team is investing meaningfully in AI, creating an opportunity to apply emerging technology to real operational challenges across production, supply chain, quality, finance, and other enterprise functions. What We Offer • Competitive compensation based on experience, skills, education, and market conditions • Comprehensive medical, dental, vision, life, disability, and AD&D coverage • Telemedicine access and supplemental employee benefit programs • 401(k) with employer match after the eligibility period • Generous paid time off plus company-paid holidays • Tuition reimbursement and support for certifications and continuing education • A collaborative environment with opportunities to influence Silgan’s evolving AI strategy • The stability of a global, publicly traded organization with long-term career potential What You’ll Do As the Senior AI Application Developer, you will build and operationalize AI-powered applications while partnering with development, data, infrastructure, security, compliance, and business teams. You will help move AI capabilities from prototype through production with the controls, monitoring, and engineering discipline required in a complex enterprise environment. Key Responsibilities AI Application Development • Architect and develop production-grade AI applications, including agentic systems, intelligent search, automated reporting, and operational decision-support tools • Build AI agents capable of multi-step reasoning, tool use, function calling, and workflow execution across enterprise systems • Develop retrieval-backed AI capabilities and RAG pipelines that connect structured data, documents, technical content, and operational knowledge • Build hybrid solutions that combine deterministic data processing with AI-generated analysis, narrative, and anomaly detection Enterprise Integration & Full-Stack Engineering • Integrate AI capabilities with ERP platforms, data warehouses, production systems, and business applications using secure, reliable API and connector patterns • Develop across a multi-language platform spanning Python, C#/.NET, and TypeScript and contribute across backend services, agent runtimes, and modern web interfaces • Apply strong SQL and relational data skills to AI-driven analysis of large operational databases • Design integrations with enterprise authentication and identity controls, including OAuth2/OIDC, JWT, Active Directory, and least-privilege access patterns Responsible AI, LLMOps & Production Operations • Design and enforce AI guardrails including access controls, output validation, prompt safety, data protection, hallucination mitigation, and human approval gates • Implement LLMOps practices such as prompt versioning, model and quality evaluation, token and cost optimization, monitoring, structured logging, and regression testing • Manage phased deployments from proof of concept through pilot and full organizational rollout with appropriate scope and access controls • Partner with security, compliance, and legal stakeholders to support responsible, auditable AI deployments and contribute to Silgan’s AI governance framework Team Capability & Collaboration • Mentor and upskill developers on AI engineering concepts, frameworks, patterns, and modern AI-assisted development practices • Evaluate emerging AI frameworks, model capabilities, orchestration patterns, and tooling and identify approaches that are genuinely useful for Silgan • Translate complex AI concepts for business stakeholders and convert ambiguous business needs into clear technical requirements What You Bring The ideal candidate combines strong production software engineering experience with hands-on expertise building LLM-powered applications. You are comfortable working across the technology stack, understand where AI adds value and where deterministic approaches are more appropriate, and can build systems that are secure, reliable, maintainable, and auditable. Qualifications • Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience • 5+ years of professional software development experience with a track record of shipping production applications to real users at scale • Hands-on experience building and deploying LLM-powered applications and designing systems around model limitations and reliability considerations • Experience designing and deploying AI agents using tool calls, function calling, or similar orchestration patterns in production environments • Professional-level development skills in at least two of Python, C#/.NET, and TypeScript, with the ability to work across all three • Strong SQL skills including relational data modeling, query analysis, stored procedures, and performance awareness • Experience building retrieval-backed AI features such as search, RAG, or structured data catalogs and evaluating retrieval quality • Experience integrating enterprise services through REST APIs and modern authentication patterns • Working knowledge of cloud platforms; Azure experience is preferred, with AWS experience also relevant Preferred Qualifications • Experience with AI orchestration frameworks such as LangGraph, LangChain, Semantic Kernel, Microsoft Agent Framework, LlamaIndex, or equivalent • Experience developing Model Context Protocol (MCP) servers or clients • Experience building end-to-end RAG pipelines, including chunking, embeddings, vector search, and retrieval evaluation • Experience with modern web frontends and real-time or streaming AI interfaces using technologies such as React/Next.js, Blazor, Angular, SSE, SignalR, or WebSockets • Experience implementing AI safety controls, output evaluation pipelines, and LLMOps monitoring or regression-testing practices • Experience deploying and operating applications on Windows Server infrastructure and supporting CI/CD pipelines • Experience in enterprise environments with formal security, compliance, change management, and audit requirements • Manufacturing, supply chain, industrial operations, ERP, or process-intensive industry experience • Experience mentoring developers or supporting cross-functional adoption of new AI/ML capabilities • Proficiency with AI-assisted development tools such as GitHub Copilot, Claude Code, Cursor, Aider, or similar tools Why This Role Stands Out This is an opportunity to join Silgan’s AI transformation at an early and meaningful stage. You will work on production applications tied to real manufacturing and business challenges, influence the technical patterns and governance practices that shape future AI adoption, and help establish internal capability that can scale across the organization. The role combines hands-on engineering with enterprise visibility and the opportunity to help define how AI is responsibly applied across a stable, global manufacturing company. Ready to Apply? If you are an experienced software engineer who enjoys turning emerging AI capabilities into reliable, production-ready enterprise applications, apply today to learn more about joining Silgan Holdings and helping shape the future of AI in manufacturing.

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