Lead Backend Engineer

Role Description

The Lead Backend Engineer on the AI Platform team plays a critical role in building, evolving, and leading the backend systems and engineering practices that power internal products, customer-facing capabilities, AI-enabled workflows, and operational decision-making across the organization. This role combines hands-on backend engineering depth with technical leadership, delivery ownership, and mentorship for engineers working on business-critical systems.

This role contributes to the development and evolution of core backend capabilities, including:

• Service-oriented architecture
• APIs
• Workflow orchestration
• Event-driven integrations
• Identity and permissions
• Operational tooling

In addition, the Lead Backend Engineer will drive buildouts of:

• AI application infrastructure
• LLM-powered product capabilities
• Agentic workflows
• Retrieval-augmented systems
• Evaluation pipelines
• Shared platform patterns

Success requires strong technical judgment, sound systems thinking, and the ability to guide a team toward simple, scalable, and maintainable solutions in a cloud-based, regulated, high-stakes environment.

The Lead Backend Engineer is expected to operate effectively in a modern engineering environment, using:

• Automation
• Observability
• CI/CD
• Testing
• Infrastructure-as-code
• AI-assisted development practices

This is a fully remote position that offers a competitive salary range of $220,000 to $260,000 USD, plus an annual bonus. You'll also receive our excellent benefits package, which includes medical coverage starting on day one and a company-matched 401(k). Compensation may vary based on experience, location, and other job-related factors.

Qualifications

• 5-8+ years of experience building and operating production-grade backend systems, APIs, services, or distributed applications
• 2+ years of experience operating in a technical lead, team lead, staff-level project lead, engineering manager, or equivalent engineering leadership capacity
• Strong software engineering fundamentals, including data structures, algorithms, system design, debugging, testing, code quality, and pragmatic architecture decision-making
• Experience designing, building, maintaining, and debugging services that run in production and support real users or business-critical workflows
• Experience with modern backend programming languages such as Python, Go, C++, Rust, Java, Kotlin, Scala, TypeScript, or C#
• Experience with API design, service boundaries, event-driven or asynchronous architectures, relational data stores, and non-relational data stores
• Experience building transactional systems where correctness, idempotency, consistency, reconciliation, and auditability matter
• Experience deploying and operating backend services on major cloud platforms such as AWS, GCP, or Azure
• Experience building AI-enabled product capabilities on top of LLMs, foundation models, retrieval systems, embedding and search infrastructure, agent or tool-calling patterns, workflow orchestration, structured outputs, and human-in-the-loop review
• Experience integrating AI capabilities with backend systems, permissions, audit trails, document workflows, data pipelines, APIs, operational decisioning, and business-critical user experiences
• Demonstrated ability to use AI-assisted development tools to improve engineering velocity while maintaining code quality, security, review discipline, and accountability for technical decisions
• Strong SQL skills and comfort with application data modeling, schema evolution, migrations, query performance, and data access patterns
• Experience leading technical design, breaking down ambiguous problems, sequencing work, managing dependencies, and helping engineers make high-quality implementation decisions
• Experience mentoring engineers through design review, code review, debugging, production support, career development, and feedback
• Strong judgment in ambiguous environments where requirements evolve and systems must balance speed, reliability, security, compliance, and flexibility

Requirements

• Experience in fintech, mortgage, lending, payments, insurance, banking, capital markets, or other regulated domains
• Experience with queues, streaming, and event-driven platforms such as Kafka, Kinesis, SQS/SNS, Pub/Sub, RabbitMQ, or similar systems
• Experience building secure identity, access control, permissions, audit trail, policy, or compliance-oriented backend capabilities
• Experience building high-volume, low-latency, multi-tenant, B2B, enterprise, or internal platform systems
• Experience with AI platform components such as model APIs, prompt management, embeddings, vector databases, retrieval pipelines, function calling, model routing, evaluation harnesses, and AI observability tooling
• Experience improving system reliability, cost efficiency, developer productivity, team execution, and operational scalability as a platform grows

A Note to Candidates

You do not need prior fintech or finance experience to succeed in this role. If you are a strong backend engineering lead with solid technical judgment, a product mindset, and excitement for leading engineers through complex backend and AI-enabled systems problems, we would love to hear from you.

If your background does not line up perfectly with every bullet, but this role feels like the kind of work you want to do, please apply.

Bayview is an Equal Employment Opportunity employer. All aspects of consideration for employment and employment with the Company are governed on the basis of merit, competence and qualifications without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, or any other category protected by federal, state, or local law.