Full-Stack AI Developer

H.W. Kaufman Group is building an AI Value Engineering capability inside Information Technology to engineer measurable business value across the enterprise. The AI Value Engineering team operates at the intersection of application development, RPA, data, business operations, and AI-enabled delivery. Its charter is to deliver high-impact solutions across quick-strike and deep-dive engagements, partner closely with business stakeholders, transition proven solutions to sustaining teams, and stop initiatives quickly when they are not proving value. The team is measured on portfolio impact, successful handoffs, quantified business value, disciplined focus, and the ability to avoid becoming a maintenance or production-support function. This role is for a hands-on, AI-enabled developer who can move across applications, automation, data, and business operations to identify high-impact opportunities, build working solutions, prove their work, and transition responsibly to sustaining teams. We are looking for developers for whom building software is more than a job. Strong candidates are resourceful, curious, disciplined, and energized by solving problems. They have opinions shaped by experience, reading, experimentation, and exposure to good engineering practices. They understand that AI changes the speed of software delivery, but not the need for judgment, craftsmanship, business understanding, and accountability. This role is best suited for a T-shaped or comb-shaped technologist broad enough to wire together platforms, data, APIs, automations, and user workflows; deep enough to make sound technical decisions and avoid fragile solutions. What Success Looks Like Take a loosely defined business problem, clarify the value hypothesis, and produce a working demonstration quicklyKnow when an AI agent’s recommendation is plausible, risky, over-engineered, or misaligned with enterprise supportabilityMove comfortably between front-end, back-end, integration, data, workflow automation, and platform configurationActively look for simpler, faster, more supportable paths rather than merely implementing the first technical answerProduce solutions that can be handed off cleanly; you do not create hidden dependencies on yourselfCommunicate tradeoffs clearly to technical and non-technical audiences Responsibilities Deliver quick-strike solutions in days or weeks where business value is clear and the path is knownContribute to deeper exploratory engagements over one to three months where the solution is uncertain, but the potential value is highBuild prototypes, automations, integrations, data-driven workflows, and application features across Salesforce, MuleSoft, .NET, RPA, AI/ML tooling, and related enterprise platformsUse AI development tools such as Claude, Codex, Gemini, Copilot, or similar agents to accelerate delivery while validating architectural fit, maintainability, security, and operational riskWork directly with underwriting, claims, operations, and IT stakeholders to understand workflows, pain points, value drivers, and practical adoption constraintsTranslate business problems into working software, measurable experiments, and clear handoff packagesDocument architecture, configuration, dependencies, known limitations, prompts, runbooks, and operational considerations for the receiving teamRecommend pivoting or stopping work when an initiative is not proving valuable, without treating that as failureShadow and learn business workflows so solutions are grounded in how work gets doneProfessional software development experience in enterprise environments with 5+ years of experienceFull-stack capability across application development, integrations, APIs, data access, workflow automation, and user-facing deliveryExperience with at least several of the following Salesforce, MuleSoft, .NET/C#, JavaScript/TypeScript, SQL, REST APIs, RPA/workflow tools, cloud services, CI/CD, or enterprise data platformsPractical experience using AI-assisted development tools or a demonstrated ability to adopt them quickly and responsiblyStrong debugging, problem decomposition, and self-directed learning skillsAbility to evaluate code quality, maintainability, patterns, security implications, and operational fitAbility to write clear technical documentation and conduct knowledge transfer with receiving teamsComfort working in timeboxed engagements with defined outcomes, checkpoints, and handoff expectationsExperience in insurance, underwriting, brokerage, claims, or other workflow-heavy business domains is a plusExposure to enterprise architecture patterns, design patterns, domain modeling, relational database design, integration patterns, or similar engineering disciplinesExperience building automations or AI-enabled solutions that combine applications, data, documents, and human review workflowsExperience with prompt engineering, LLM evaluation, retrieval-augmented generation, agentic development workflows, or AI governance practicesAbility to operate inside appropriate enterprise guardrails while still challenging assumptions and finding better approaches Complementary Strengths Because this team is intentionally built from generalists who can go deep, we value candidates who bring complementary strengths that broaden the team’s overall capability. Experience in any of the following areas is a plus, but not required. Information security — secure development practices, identity and access management, data protection, secrets management, vulnerability remediation, secure API design, or practical experience partnering with security teamsAzure and cloud services — Azure App Services, Azure Functions, Logic Apps, Azure SQL, Storage Accounts, Key Vault, Service Bus, Entra ID, Azure DevOps, or similar cloud-native servicesInfrastructure as Code / DevOps — Terraform, Bicep, ARM templates, CI/CD pipelines, environment configuration, deployment automation, observability, or release governanceEnterprise integration — API gateways, MuleSoft, event-driven integration, message queues, service orchestration, or integration monitoringAI governance and operationalization — prompt/version management, LLM evaluation, data leakage prevention, human-in-the-loop review, auditability, monitoring, or safe deployment of AI-assisted workflows About Our Company H.W. Kaufman Group is a powerful global network of companies dedicated to shaping the future of insurance. With thousands of dedicated professionals across an extensive network of over 60 offices around the world, we lead by offering innovative solutions that are at the forefront of the industry. We are privately owned and thus free from the influence of Wall Street. This allows us the ability to adapt to constantly fluctuating market conditions. From brokerage, underwriting, and real estate to claims, loss control and risk management services, our depth of services is unrivaled. Equal Opportunity Employer The H.W. Kaufman Group of companies is an equal opportunity employer. All employment decisions are based on business needs, job requirements and individual qualifications, without regard to race, color, religion, gender, gender identity, age, national origin, disability, veteran status, marital status, pregnancy, sexual orientation, genetic information or any other status or condition protected by the laws or regulations in the locations where we operate. In addition, Kaufman will make reasonable accommodations to known physical or mental limitations of an otherwise qualified person with a disability, unless the accommodation would impose an undue hardship on the operation of our business.