Staff Software Engineer

About Blackhawk Network

Today, through BHN’s single global platform, businesses of all kinds can tap into the world’s largest network of branded payment solutions. BHN helps businesses grow revenue, increase loyalty, motivate and reward their teams, disburse funds and engage consumers. Branded payment solutions include the issuance and distribution of gift cards, egifts, corporate payouts and rewards, along with the technology to deliver these products in seamless, integrated ways. BHN’s network spans the globe with more than 400,000 consumer touchpoints. Learn more at BHN.com.

Overview

We are looking for a Staff Software Engineer to provide deep technical leadership for our Core Services Enablement team within Core Systems.

This team is focused on improving production reliability, observability, security posture, upgrade readiness, automation, and operational excellence across multiple critical backend platforms.

A major part of this role is to operate with an AI-first engineering mindset. We are looking for someone who can go beyond using AI tools for personal productivity and instead build reusable AI-enabled workflows, skills, automations, and engineering accelerators that help multiple engineers and teams move faster.

This is a hands-on Staff-level role for someone who can combine strong software development expertise with production engineering, platform thinking, and practical AI-led engineering transformation.

 

 

Responsibilities

 

•  Provide hands-on technical leadership across reliability, modernization, observability, security, and automation initiatives for Core Systems.

•  Build reusable AI-assisted engineering workflows, skills, scripts, prompts, and automation assets to accelerate upgrades, remediation, debugging, testing, and documentation.

•  Design and implement scalable backend solutions using Java, Spring Boot, and modern engineering practices.

•  Lead complex KTLO work, including production issue analysis, root-cause fixes, application upgrades, dependency modernization, and vulnerability remediation.

•  Define and improve observability standards across services using New Relic, Splunk, Grafana, and OpenTelemetry.

•  Drive adoption of AI-first engineering practices across the team while maintaining strong review, quality, security, and validation discipline.

•  Partner with application, platform, security, and architecture teams to improve reliability, release safety, PCI readiness, and operational maturity.

•  Mentor engineers and create repeatable playbooks that help teams solve similar problems faster and with better quality.

Qualifications

• Strong hands-on software engineering experience with Java and Spring Boot
• Proven experience designing, building, and operating production-grade backend systems
• Strong working knowledge of AI-assisted development tools such as GitHub Copilot, Claude Code, ChatGPT, Claude, or similar LLM-based engineering tools
• Ability to build reusable AI-assisted engineering workflows, skills, templates, scripts, or automation patterns
• Ability to drive AI adoption across engineers and teams through enablement, examples, guardrails, and measurable outcomes
• Deep understanding of distributed systems fundamentals, including retries, timeouts, idempotency, resiliency, scalability, and API design
• Strong experience with production debugging, incident analysis, and root-cause remediation
• Hands-on experience with observability and telemetry tools such as New Relic, Splunk, Grafana, and OpenTelemetry
• Experience leading application upgrades, dependency modernization, platform hardening, or vulnerability remediation initiatives
• Strong cross-team influence, communication, and technical leadership skills

Nice to Have

• Experience building AI agents, coding assistants, internal developer tools, or LLM-based engineering workflows
• Experience with MCP-style integrations, tool calling, workflow automation, or agentic engineering patterns
• Experience with PCI, regulated environments, or audit-driven engineering controls
• Experience with canary releases, feature flags, SLOs, error budgets, or release safety frameworks

We seek candidates who not only demonstrate curiosity and adaptability in emerging technologies but have also successfully implemented and utilized AI tools to enhance their work, improve processes, or deliver measurable results.  Our teams embrace continuous learning and the thoughtful integration of AI to create meaningful impact – for our employees and the future of work.