Senior Software Engineer II – Enterprise AI Consulting & Embedded Experts
About the role
We’re looking for a Senior Software Engineer II to join our AI Enablement product family within the Consulting & Embedded Experts team. In this role, you will operate as a trusted technical advisor and hands-on engineer, partnering directly with product and business teams to accelerate the safe, secure, and scalable adoption of AI across the enterprise.
Responsibilities
- Partner with product and business teams to identify and deliver high-impact AI use cases aligned to enterprise priorities
- Translate ambiguous business problems into practical, production-ready AI solutions
- Focus on delivering value aligned to measurable outcomes and ROI
- Embed with teams as a Technical Expert
- Bridge the gap between central AI enablement capabilities and domain-specific business needs
- Collaborate in a federated operating model, enabling teams while maintaining enterprise standards
- Build & Scale Reusable AI Capabilities
- Create reusable patterns (e.g., RAG architectures, evaluation frameworks, guardrails) that reduce time-to-market and cost
- Ensure safe, secure, and sustainable AI design
- Implement guardrails, evaluation strategies, and monitoring to ensure trusted AI outcomes and customer protection
- Champion sustainable engineering practices including reusability, scalability, and governance alignment
- Shape Technical Direction & Capability Maturity
- Assess emerging AI technologies and guide teams on when and how to adopt them responsibly
- Influence architecture decisions that enable long-term transformation, not just short-term delivery
- Enable & Elevate Others
- Mentor engineers and product teams on AI best practices, architecture, and delivery approaches
- Contribute to internal knowledge sharing, playbooks, and AI community building (e.g., demos, patterns, guidance)
Requirements
- Associate's or Bachelor's degree (preference in a science, technology, engineering, or math) or equivalent work experience
- 8+ years of engineering experience, including building and scaling distributed systems
- 5+ years of experience working with cloud platforms is required (AWS preferred but open to others)
- 5+ years of experience of working with modern data/AI architectures is required
- Strong ability to operate in ambiguity and move between strategy and hands-on delivery
- Prominent ability to influence without authority and drive adoption across teams
- Excellent communication skills—able to translate between technical and business audiences
Qualifications
- Experience building AI/ML or GenAI solutions in production environments
- Familiarity with LLMOps, MLOps, evaluation frameworks, and AI guardrails
- Experience with cloud platforms (e.g., AWS) and modern data/AI architectures
- Background in solution architecture, consulting, or platform engineering
- Experience building reusable frameworks, accelerators, or internal platforms
Skills
- Experience building AI/ML or GenAI solutions in production environments
- Familiarity with LLMOps, MLOps, evaluation frameworks, and AI guardrails
- Experience with cloud platforms (e.g., AWS) and modern data/AI architectures
- Background in solution architecture, consulting, or platform engineering
- Experience building reusable frameworks, accelerators, or internal platforms
Benefits
Salary Range Information: Salary ranges below reflect targeted base salaries. Non-sales positions have the opportunity to participate in a bonus program. Sales positions are eligible for sales incentives, and in some instances a bonus plan, whereby total compensation may far exceed base salary depending on individual performance.
Pay
$127,000 - $152,000 / year
Schedule
This role will partner with our global teams and has an expectation for flexibility in your work schedule to have a regular start time around 7:30-8:00 am CST a few days a week.
Work Environment
This role offers in-office and hybrid (blending at least three office days in a typical workweek), in Des Moines, IA or Charlotte, NC. You’ll work with your leader to figure out which option may align best based on several factors.