As passionate about our people as we are about our mission.
Why Join Q2?
Q2 is a leading provider of digital banking and lending solutions to banks, credit unions, alternative finance companies, and fintechs in the U.S. and internationally. Our mission is simple: build strong and diverse communities through innovative financial technology—and we do that by empowering our people to help create success for our customers.
What Makes Q2 Special?
Being as passionate about our people as we are about our mission. We celebrate our employees in many ways, including our “Circle of Awesomeness” award ceremony and day of employee celebration among others! We invest in the growth and development of our team members through ongoing learning opportunities, mentorship programs, internal mobility, and meaningful leadership relationships. We also know that nothing builds trust and collaboration like having fun. We hold an annual Dodgeball for Charity event at our Q2 Stadium in Austin, inviting other local companies to play, and community organizations we support to raise money and awareness together.
Senior Software Engineer
Role Overview
This role plays a key technical role within the
AI Producer Team
, responsible for building and operating Q2’s agentic AI ecosystem (AI agents, reusable AI framework, shared data connectors, and governance-aligned delivery). This role focuses on implementing scalable agentic workflows, RAG pipelines, and backend systems that meet enterprise production standards.
The engineer will work within the established AI framework and contribute to evolving shared components while partnering with Staff and Senior Staff engineers on design and execution.
Key Responsibilities
Build & Productionize AI Agents
Implement agentic workflows using planner–executor or tool-calling architectures.
Develop RAG pipelines integrating enterprise data sources.
Implement chunking, embedding pipelines, metadata filtering, and retrieval logic.
Integrate agents with internal systems (GitLab, Snowflake, logs, documentation systems, monitoring tools, etc.).
Convert POCs into stable, scalable, production-ready services.
Ensure Production-Grade Engineering
Implement observability (metrics, tracing, logging) for AI agents.
Add guardrails and fallback mechanisms to reduce hallucination and failure impact.
Support evaluation frameworks (offline + online).
Optimize latency, token usage, and cost efficiency.
Ensure security, privacy, and data handling standards are followed.
Contribute to Shared AI Platform
Build reusable utilities and modules within the shared AI framework.
Participate in architecture and design discussions.
Improve retrieval quality using metrics like precision, recall, and grounding confidence.
Identify and mitigate common RAG failure modes.
Collaboration & Continuous Improvement
Work with domain teams to refine production requirements.
Incorporate user feedback post-launch.
Participate in code reviews and technical documentation.
Required Qualifications
Education & Experience
A four-year bachelor’s degree in computer science, Software Engineering, Information Technology, or a related technical field.
5–8 years of experience developing backend or distributed systems in production environments.
Practical experience building or integrating LLM-based systems (e.g., RAG pipelines, vector search integrations, agent workflows).
Experience implementing observability, testing, and reliability improvements in production systems.
Proven track record delivering high-quality features or services at scale.
AI / Agentic Systems
Hands-on experience implementing LLM-based systems in production or near-production environments.
Strong understanding of RAG fundamentals:
Embedding pipelines
Vector search integration
Chunking strategies
Context window management
Familiarity with agentic patterns (tool-calling, orchestration, multi-step workflows).
Understanding of hallucination risks and grounding strategies.
Exposure to evaluation and regression testing for prompts/agents.
Backend Engineering
Strong experience building scalable backend services.
Experience with APIs, async systems, and distributed service patterns.
Knowledge of caching, rate limiting, idempotency, and resiliency patterns.
Experience working with Python or equivalent backend stack.
Infrastructure
Experience with containerization and Kubernetes.
Familiarity with CI/CD workflows.
Basic understanding of monitoring and production support practices.
Level Distinction
Owns feature-level or subsystem-level delivery.
Operates within defined architecture.
Contributes to design but does not set cross-org standards.
Responsible for quality of implementation and reliability.
This position requires fluent written and oral communication in English.
Health & Wellness
Hybrid Work Opportunities
Flexible Time Off
Career Development & Mentoring Programs
Health & Wellness Benefits, including competitive health insurance offerings and generous paid parental leave for eligible new parents
Community Volunteering & Company Philanthropy Programs
Employee Peer Recognition Programs – “You Earned it”
Click
here
to find out more about the benefits we offer.
Our Culture & Commitment:
We’re proud to foster a supportive, inclusive environment where career growth, collaboration, and wellness are prioritized. And our benefits go beyond healthcare—offering resources for physical, mental, and professional well-being. Click here to find out more about the benefits we offer. Q2 employees are encouraged to give back through volunteer work and nonprofit support through our Spark Program (
see more
). We believe in making an impact—in the industry and in the community.
We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, or veteran status.
