Senior Software Engineer

Job Description

Job Description

Description:

At First Electronic Bank (FEB or Bank), we are driven by the purpose to make credit accessible to everyday Americans and their businesses. Partnering with some of the most innovative fintech companies in the nation, we offer a wide range of consumer and commercial credit and deposit products on a national basis. Offering deposit accounts and debit cards, revolving lines of credit, private-label credit cards, installment financing programs and more, FEB engages with strategic, collaborative partners, promoting services and products to provide the most beneficial consumer and commercial financing solutions. 

First Electronic Bank (FEB) is seeking a highly capable software engineer to independently lead ambiguous, high-impact initiatives that deliver FEB's internal applications, secure APIs and services, fintech integrations, and agent-based capabilities from problem definition through measurable production outcomes. We're looking for a senior engineer who builds real business applications, connects systems through APIs, and uses AI agents as a practical part of delivering software. This is not an AI research or prompt engineering role. Instead, we're seeking a hands-on builder who knows how to leverage AI to accelerate development while applying sound engineering judgment to validate outputs, manage context and handoffs, and ensure production-quality results.

In this role, you will build polished user interfaces and robust backend services that connect enterprise systems and orchestrate workflows across approved MCP servers. You'll own application design, development, release readiness, and operational outcomes while working within Engineering and Infrastructure standards and the bank's cloud control framework. You will also help transform successful solutions into reusable patterns, frameworks, and best practices for the broader team. This role is ideal for an experienced engineer who combines strong software engineering fundamentals with a pragmatic approach to AI-assisted development in production environments.

Representative work: Build and enhance internal applications with production-quality front-end and backend services; integrate fintech and enterprise platforms through secure APIs; prototype targeted AI-enabled workflows; and develop an extensible tool-routing layer that supports multiple approved MCP servers.

What You'll Do:

• Own complex application workstreams end to end: clarify the problem and success measures; design secure APIs, services, and data exchanges within established architecture; manage dependencies and risk; and drive delivery through adoption, production support, troubleshooting, and proactive improvement.
• Production accountability: Own application reliability, operational readiness, runbooks, model usage, and post-release remediation; partner with Infrastructure on environments, CI/CD guardrails, identity, networking, secrets, observability, capacity, incidents, and cloud costs.
• Agent workflows: Provide authoritative context, manage task state and handoffs, and configure multi-step workflows with sequencing, branching, retries, checkpoints, tracing, and approvals; route work to approved MCP servers and tools based on task and permissions.
• Agentic coding: Use GitHub Copilot or comparable coding agents to delegate work, supply repository context, review generated changes, and retain human ownership of quality, security, and release decisions.
• Verification and controls: Use tests, end-to-end verification, security review, evaluations, and monitoring; enforce sensitive-data handling, least privilege, audit evidence, rollback, and human approval before consequential actions.
• Applied prototyping: Periodically work with business users to prototype internal applications and workflows using approved data and tools, then retire, control, or productionize them based on value and risk.
• Partner across business, product, security, compliance, and Infrastructure; mentor through design and code reviews; and convert proven approaches into reusable components, templates, and playbooks that improve delivery across the team.

Requirements:

What We're Looking For

• 5+ years of software engineering experience (or equivalent scope) delivering production applications across interfaces, APIs, and integrations.
• Demonstrated success independently leading ambiguous, high-impact work from problem definition through sustained production use and measurable results, while mentoring engineers and improving team practices.
• Strong JavaScript or TypeScript and a modern web framework, plus proficiency in C#/.NET, Python, or Java for backend services, APIs, and integrations.
• Understanding of RESTful API and service design, OAuth2/OIDC, OpenAPI/Swagger, secure data exchange, and integration patterns for reliable distributed applications.
• Experience building cloud-hosted applications on Azure, AWS, or Google Cloud and partnering with Infrastructure on CI/CD, environment controls, security, monitoring, scaling, incident response, and cost management.
• Demonstrable use of GitHub Copilot, Claude Code, Codex, or comparable tools to coordinate agents, manage context and handoffs, verify changes, and deliver tested software; familiarity connecting agents to tools or MCP servers is expected, but building a custom platform is not.
• Practical knowledge of agent state, prompt-injection and data-leakage risks, least privilege, secrets, auditability, and recovery.
• Ability to turn an ambiguous business problem into a focused prototype and explain tradeoffs to non-technical users.
• Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or a related field.

Preferred Qualifications:

• Experience deploying applications or integrations in banking, fintech, payments, or another regulated environment; Federal Reserve payment, settlement, or reporting APIs are especially valuable.
• Cloud data and messaging services such as Fabric, Service Bus, Kafka, or equivalent.
• Microsoft 365 Copilot, Copilot Studio, Power Platform, or comparable enterprise automation tools.
• Managed AI/agent platforms such as Microsoft Foundry, Amazon Bedrock, or Google Cloud Vertex AI, including deployment, evaluation, and tracing.
• Experience building or integrating MCP servers, tool registries, or multi-server routing layers, and turning that work into reusable patterns adopted by other engineers or teams; Go, Python, TypeScript, or C#/.NET experience is valuable.
• Master’s degree in Computer Science, Software Engineering, Information Technology, or a related field.