Beckett is the trusted authority in sports card and collectibles grading, pricing, and marketplace services. Our platform is mid-transformation: a new generation of NestJS/TypeScript microservices and Next.js frontends is actively replacing a prior generation of Java/Spring Boot services, while two large legacy PHP monoliths still power critical grading and e-commerce workflows. Getting this migration right — without disrupting the business — is the defining technical challenge of the next few years.

As a Staff Software Engineer, your influence extends beyond your team to the technology organization. You have expertise in the entirety of your team's products and services — how they interact and how data flows between them — and you're building the same understanding of adjacent systems. You lead projects of moderate-to-significant scope over one-to-two-quarter horizons, design for the platform's future rather than just the next feature, and are recognized by peers and leaders as an authority in your domain.

• Own the architecture of your team's domain end to end: services, data flows, integration points, and failure modes across the full portfolio (e.g., NestJS services, their Postgres/MySQL data stores, the legacy systems they front, and the frontends they serve).

• Design products and services that allow for iterative, autonomous development and future scaling, deliberately reducing the friction of future changes — service boundaries, contract design, data ownership, and migration paths.

• Lead high-stakes modernization work: defining strangler patterns around the PHP monolith, sequencing Java11 service replacements, and ensuring byte-compatible, low-risk cutovers.

• Build a working understanding of adjacent systems and products across the org — grading, marketplace, CRM, payments, identity, data/ETL — and use it to catch cross-system risks early.

• Set the bar for security, testing, observability, and operational excellence, and use operational data to drive stability and performance improvements.

• Lead the adoption of AI-assisted engineering across the tech org: establish standards and guardrails for AI coding tools (code review expectations, testing requirements, security and IP hygiene), identify where AI agents can accelerate the modernization effort (legacy code comprehension, test generation, migration scaffolding), and measure the impact.

• Successfully lead projects of moderate scope and/or complexity spanning 12 quarters, coordinating engineers, stakeholders, and dependencies to a predictable landing.

• Plan and develop using an explicit value-vs-cost framework, so urgency and prioritization are easily understood by both the team and stakeholders.

• Identify and communicate blockers and delays within your team to the right stakeholders before they become surprises.

• Foster a culture of knowledge sharing and documentation within your team and with business stakeholders 1 initiate and facilitate meaningful discussions around complex issues.

• Build strong relationships with teammates, your manager, business stakeholders, and senior engineers across the organization.

• Mentor senior and mid-level engineers through design reviews, pairing, and feedback; foster a culture where feedback is sought out and used as a tool for growth.

• Raise the org's collective AI fluency: share proven workflows, prompts, and agent configurations; coach engineers on when AI tooling helps and when it misleads; and keep the team current as the tooling landscape evolves.

• 8+ years of professional software engineering experience, including demonstrated technical leadership of multi-engineer, multi-quarter projects.

• Expert-level backend engineering in TypeScript/Node.js and/or Java, with the range to be effective across our polyglot estate (TypeScript, Java 21, PHP, Python, C#).

• Full-stack range: hands-on production experience across the entire stack 1 modern React/Next.js frontends, API and service layers, relational data stores, and the infrastructure they run on 1 with the judgment to design and review at every layer, even where others do the bulk of the implementation.

• Proven experience modernizing legacy systems: strangler-fig migrations, service extraction from monoliths, or platform re-architecture under live traffic.

• Deep relational database expertise (PostgreSQL, MySQL): data modeling, migrations, performance, and the realities of shared-database coupling between services.

• Strong distributed-systems fundamentals: service boundaries, API/contract design (REST, GraphQL, gRPC), messaging (SQS), idempotency, and failure handling.

• Production AWS depth 1 ECS, Lambda, networking, IAM 1 and infrastructure-as-code fluency (AWS CDK and/or Terraform).

• A track record of raising engineering standards: testing strategy, observability, documentation, and incident response.

• Strong, hands-on background in AI tooling and usage: daily fluency with AI coding assistants and agentic tools (Claude Code, Copilot, Cursor, or similar), experience integrating them into team workflows (CI, code review, documentation), and mature judgment about verification, security, and the limits of AI-generated code.

• Excellent written and verbal communication with technical and business audiences alike.

• Experience with frontend architecture at scale (design systems, micro-frontends, performance budgets) or mobile (React Native/Expo).

• Experience with e-commerce, marketplace, payments, or high-traffic consumer platforms.

• Data platform exposure (Snowflake, ETL pipelines, dimensional modeling) or applied ML (computer vision).

• Experience building LLM-powered features or platforms: LLM API integration (Anthropic/OpenAI), retrieval-augmented generation, evals, or agent frameworks (e.g., MCP) 1 and shipping them to production responsibly.

• Interest in sports cards, gaming, or collectibles!

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