Open to All Onshore Vendors
Strong Preference for Denver Englewood Hub - Hybrid 3 days per week.
Would consider Minneapolis
Max rate of ***
Title: AI Enablement and Modernization Engineer
AI enablement for engineering teams
Enable effective use of approved AI-assisted development tools such as enterprise copilots, internal GenAI tooling, and approved LLM platforms.
Develop and maintain reusable prompt patterns, agent workflows, and repository-level guidance to standardize AI-assisted development across teams.
Partner with internal AI governance and architecture groups to pre-align use cases, reduce approval friction, and avoid rework.
Legacy analysis and modernization acceleration
Apply AI-assisted techniques to analyze legacy codebases, extract business rules, and document undocumented behavior.
Support decomposition of monolithic applications into domain-aligned, API-first architectures using AI-driven dependency analysis.
Assist teams modernizing legacy stacks including mainframe, batch, and large Java-based systems.
Testing and quality acceleration
Enable AI-assisted generation of unit, integration, contract, and regression tests.
Help integrate AI-generated tests into existing CI/CD pipelines without compromising quality, compliance, or auditability.
Improve test coverage and reduce manual testing toil across modernization programs.
Education and cross-training
Act as a hands-on coach for engineers and tech leads on compliant, effective AI usage.
Create lightweight training materials, examples, and playbooks tailored to real delivery scenarios.
Embed with teams temporarily to drive adoption, not just documentation.
Governance and risk alignment
Ensure AI usage aligns with security, data privacy, PCI, and internal risk requirements.
Work closely with architecture, security, and risk partners early in the lifecycle to avoid late-stage blockers.
Required qualifications
Practical experience using AI tools for code analysis, generation, documentation, or testing.
Experience in Java and Spring Boot development.
Strong knowledge of microservices architecture and API design principles.
Experience with RESTful services, JSON, and YAML.
Familiarity with CI/CD pipelines (Jenkins, Maven, Git).
Understanding of security best practices and performance tuning.
Proven ability to operate effectively in regulated, risk-driven enterprise environments.
Strong communication skills and the ability to teach and influence without formal authority.
Preferred qualifications
Strong background in software engineering with hands-on experience modernizing large, legacy systems.
Experience modernizing Java-based monoliths into Spring Boot or similar API architectures.
Experience with COBOL, mainframe environments, or large-scale batch processing systems.
Familiarity with containerized or cloud-based deployment models.
Knowledge of PCI, model risk governance (MRM), and banking compliance controls.
Observability stack experience.
Success measures
Reduced time spent by teams on legacy analysis, documentation, and test creation.
Increased, compliant adoption of AI-assisted development practices.
Faster modernization throughput without increased production or compliance risk.
Clear evidence of reusable patterns, prompts, and workflows adopted by multiple teams.
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EEO:
Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.