Lead Software Engineer - Enterprise AI Services & Agents

Wellmark, Inc.•Des Moines, IA

20h•Hybrid

About The Position

As a Lead Software Engineer on Wellmark’s Enterprise AI Services & Agents team, you will lead the design and delivery of reusable enterprise assistants, agents, AI services, skills, and agentic workflows. This hands-on technical leadership role combines solution design, software engineering, customer engagement, and end-to-end accountability for secure, scalable, and supportable AI solutions. You will partner with engineers, customers, product leaders, architecture, security, and governance stakeholders to translate business needs into production-ready solutions. You will help establish enterprise blueprints and engineering standards for assistants, agents, agentic workflows, and AI evaluation, while building reusable frameworks and components that reduce duplication and accelerate governed AI delivery across Wellmark. The team builds business-facing AI capabilities once, hardens them for enterprise use, and makes them reusable across products, channels, portfolios, and business areas. The role leads system development and engineering for highly complex programs; coordinates preparation, coding, testing, and debugging of complex programs; and analyzes and develops workflows using emerging technology to meet Wellmark’s evolving business needs. It serves as a subject matter expert in innovative, cost-effective business solutions across applications and systems, provides leadership and guidance to others, and coordinates integration of products and processes. The position also contributes to proposals, estimates, proof-of-concept activities, enterprise standards, code reviews, and ongoing process and technology improvements.

Requirements

Bachelor’s degree in Computer Science, MIS, or a related field and at least 5 years of development experience (for example, Angular, NodeJS, TypeScript, C++, .NET, Java, or SQL), or 9 years of related and applicable experience.
Strong analytical problem-solving skills, accuracy, and attention to detail; experience troubleshooting and developing creative technical solutions and addressing complex issues.
Demonstrated experience in software development lifecycle methodologies.
Ability to communicate with and coach or mentor team members while maintaining a positive attitude, staying calm under pressure, being approachable and respectful, and taking responsibility for failures.
Ability to connect the value of the Wellmark as a Service (WaaS) strategy to company strategy when making design and development decisions.
Ability to gather information and conduct research for root-cause analysis, problem definition, solution recommendations, implementation, verification, and ongoing optimization, using data to support recommendations.
Ability to build relationships and communicate key information to appropriate stakeholders in a timely manner, adapting communication style to the audience.
Ability to thrive in a fast-paced environment with changing priorities; strong organization and time-management skills, including meeting timeframes with little direction while maintaining data and information integrity.
Eagerness to learn, stay current on industry trends, and maintain a continuous-learning mindset.
Ability to collaborate, work as a team, earn trust and respect, actively listen, and apply coaching feedback.
Ability to lead, support, and work within a diverse development team model, including global staffing and crowdsourcing.

Nice To Haves

Experience leading complex software-solution design and delivery while remaining hands-on with coding, testing, deployment, troubleshooting, and production support.
Production experience designing, building, deploying, and supporting generative AI applications, enterprise assistants, agents, agentic workflows, or reusable AI services at enterprise scale.
Experience with agent frameworks and orchestration technologies such as AWS Strands Agents, Amazon Bedrock Agents, LangGraph, or comparable frameworks.
Experience with Retrieval-Augmented Generation, enterprise or semantic search, knowledge retrieval, structured-data retrieval, document understanding, and tool-using AI solutions.
Experience designing multi-agent or supervisor-agent patterns, including delegation, tool selection, orchestration, context and state management, exception handling, and human escalation.
Experience integrating models, enterprise tools, data, and services through APIs or standards such as Model Context Protocol (MCP).
Experience developing AI evaluation frameworks using golden datasets, scenario-based testing, LLM-as-judge, and automated regression testing to measure groundedness, citation correctness, response quality, safety, latency, and cost.
Experience with AI observability and operations, including OpenTelemetry, distributed tracing, prompt and response telemetry, quality monitoring, regression detection, audit evidence, usage measurement, and cost tracking.
Strong experience building backend services, enterprise APIs, microservices, and distributed systems using RESTful, event-driven, or asynchronous patterns.
Experience designing cloud-native solutions using AWS services and infrastructure-as-code tools such as AWS CDK, Terraform, or CloudFormation.
Experience designing secure enterprise solutions that incorporate authentication, authorization, workload identity, data protection, audit logging, policy enforcement, guardrails, and appropriate human oversight.
Experience building reusable frameworks, SDKs, libraries, templates, service contracts, test harnesses, or infrastructure components that accelerate delivery across multiple teams.
Experience implementing automated unit, integration, contract, and end-to-end testing, along with CI/CD pipelines using GitHub Enterprise Actions or similar tools.
Experience engaging customers, translating ambiguous business needs into technical designs, communicating trade-offs, and influencing decisions across product, architecture, security, governance, and engineering teams.
Experience providing technical direction, conducting design and code reviews, mentoring engineers, and improving team engineering practices.
Experience delivering solutions in healthcare, health insurance, financial services, or another regulated industry, including familiarity with HIPAA, SOC 2, privacy, compliance, or responsible AI practices.
AWS certifications such as AWS Certified Developer, Solutions Architect, or Machine Learning Engineer.

Responsibilities

Lead the design and delivery of reusable enterprise assistants, agents, AI services, skills, and agentic workflows.
Translate business needs into production-ready solutions in partnership with engineers, customers, product leaders, architecture, security, and governance stakeholders.
Establish enterprise blueprints and engineering standards for assistants, agents, agentic workflows, and AI evaluation.
Build reusable frameworks and components that reduce duplication and accelerate governed AI delivery across Wellmark.
Lead system development and engineering for highly complex programs, including coordinating program preparation, coding, testing, debugging, and workflow analysis.
Serve as a subject matter expert in implementing innovative and cost-effective business solutions across multiple applications and systems.
Provide leadership, training, and guidance on research, root-cause analysis, problem definition, solution implementation, verification, and ongoing optimization.
Analyze defects to identify root causes and guide others in finding improvement opportunities.
Mentor and problem-solve with other technology areas on developing and implementing solutions, including use of new or enhanced software and applications.
Coordinate company resources to integrate products, processes, and complex solutions, providing timely and accurate results and customer service.
Consult with Wellmark leaders on business status, issues, process improvements, and technology enhancements or capabilities.
Participate in project proposals, estimates, and proof-of-concept activities as needed.
Maintain awareness of industry best practices and standards, participate in industry or knowledge reference groups, provide direction for enterprise standards, conduct code reviews, and monitor adherence to standards.
Perform other duties as assigned.