Sr Software Engineer

Topgolf•Dallas, TX

About The Position

The Senior Software Engineer is a full-lifecycle contributor responsible for designing, building, and operating high-quality software across customer-facing and internal products. Go is the primary language for this role, with Python used across scripting, automation, and data-adjacent work. The ideal candidate brings breadth across the stack — from backend services and system design to APIs, data, and front-end integration. You will take ownership of complex engineering problems end-to-end — from requirements through design, implementation, testing, and production operation. We practice Spec Driven Development and embrace AI-augmented engineering workflows as standard practice. The ideal candidate writes clean, maintainable Go, makes sound architectural decisions, and raises the technical bar for the engineers around them.

Requirements

7+ years of professional software engineering experience
4+ years of experience writing production Go; idiomatic, well-tested, and maintainable code is a baseline expectation.
Working proficiency in Python for scripting, automation, or tooling
Strong software design instincts — experience with multiple architectural patterns (microservices, monoliths, event-driven) and knowing when to apply each
Solid experience building APIs and integrations (REST, gRPC, event-driven, or otherwise) with attention to versioning, contracts, and consumer impact
Practical understanding of distributed systems and backend fundamentals — consistency, availability, latency tradeoffs, failure modes, and operational realities
Experience with synchronous and asynchronous communication patterns (HTTP/gRPC, messaging systems)
Experience working with relational and/or NoSQL databases in a service-oriented architecture
Experience building front-end applications with Vue.js, including component architecture, state management, and integration with REST or event-driven backends
Strong debugging, performance tuning, and production support experience
Strong problem-solving skills and architectural judgment, including knowing how and when to leverage AI tooling effectively and responsibly
Excellent communication skills and collaborative mindset
Strong sense of ownership and accountability
Demonstrated ability to mentor engineers and elevate team technical capability
Hands-on experience with AI-assisted development tools (Claude Code, Codex, or similar) and comfort applying them across the SDLC

Nice To Haves

Experience with event streaming platforms (Kafka, Pub/Sub, NATS)
Experience with serverless compute, particularly AWS Lambda — event-driven invocation patterns, cold start management, and integration with API Gateway or messaging services
Experience with API gateways and service meshes
Experience implementing authentication and authorization (OAuth2, JWT, SSO)
Familiarity with domain-driven design (DDD) principles
Experience working in Agile/Scrum environments with AI-augmented planning and delivery practices
Experience with Spec Driven Development or similar structured pre-implementation design practices
Familiarity with MCP (Model Context Protocol) integrations or AI-to-toolchain automation in development environments

Responsibilities

Design and develop high-quality software in Go, applying engineering fundamentals and setting patterns the team can build on
Drive features through a Spec Driven Development process — author and iterate on detailed specs before writing code, using AI tooling to validate, accelerate, and pressure-test the approach
Contribute to system and software architecture decisions, balancing reliability, scalability, maintainability, and delivery speed
Design and implement APIs, integrations, and inter-service communication patterns appropriate to the problem at hand
Work across the data layer — design schemas, write efficient queries, and reason about data ownership and consistency
Build and maintain responsive front-end components using Vue.js, consuming backend services and APIs
Build software that is observable, testable, and operable — logging, monitoring, alerting, and graceful failure handling are first-class concerns
Leverage AI coding tools (e.g., Claude Code, Codex) as a standard part of the development workflow — for code generation, refactoring, test scaffolding, and documentation — while maintaining full accountability for the output
Help establish and evolve team norms around AI-assisted development — what good looks like for spec quality, prompt discipline, AI-generated code review, and responsible use
Lead code reviews, mentor engineers across experience levels, and champion engineering best practices organization-wide
Partner cross-functionally with DevOps, QA, product, and design teams; serve as a technical liaison and contribute to roadmap and architecture decisions
Document decisions, APIs, and operational runbooks in a way that reduces bus factor and scales knowledge across the team