• Design and build internal platform services and shared infrastructure that hundreds of engineers depend on every day, with explicit focus on developer experience and operational ergonomics. • Architect high-throughput, latency-sensitive backend platforms capable of sustaining very high request volumes with predictable, well-bounded tail latency. • Build durable, replayable event-processing pipelines and asynchronous job execution platforms that other product teams compose to ship features faster. • Design and operate caching, rate-limiting, and request-shaping layers that protect upstream systems and enable safe scaling under bursty workloads. • Develop platform abstractions, SDKs, and paved-road libraries that codify best practices and let product teams consume capabilities without re-implementing them. • Establish robust observability, SLOs, and capacity-planning practices for platform services, raising the operational bar across the organization. • Drive multi-region, fault-tolerant, and geo-distributed designs with rigorous attention to availability, durability, and graceful degradation under failure. • Lead incident response for high-impact platform issues, conduct blameless post-mortems, and drive durable engineering improvements that prevent recurrence. • Define and enforce platform-wide standards around API design, schema evolution, deployment, and backward-compatibility guarantees. • Optimize platform performance through careful profiling, data-driven tuning, and algorithmic improvements that move the needle on throughput and cost. • Partner with infrastructure, security, and SRE teams to ensure platform services meet enterprise reliability, compliance, and security obligations. • Mentor mid-level engineers and lead architectural discussions across teams, helping the broader organization grow in distributed-systems maturity. • Produce clear technical design documents, decision records, and operational runbooks that make the platform legible to future maintainers. • Continuously evaluate emerging platform technologies, open-source projects, and architectural patterns for strategic adoption.

• Design and implement performant backend services and APIs in Go, with strong attention to concurrency, error handling, and resource management. • Build cloud-native applications using Go and Kubernetes-native libraries, applying idiomatic Go patterns, well-defined module boundaries, and operational hooks that make the resulting services easy to deploy and run. • Develop CLI tools, Kubernetes controllers, and custom operators for internal platforms, designing clear command surfaces, robust error handling, and reconciliation logic that operates safely in long-running environments. • Implement gRPC and REST APIs with appropriate observability and security. • Profile and optimize Go applications for memory, GC, and goroutine behavior, applying systematic measurement, targeted improvements, and data-driven validation to deliver quantifiable gains in throughput, latency, or resource efficiency. • Integrate with messaging systems (Kafka, NATS) and data stores (PostgreSQL, Redis, etcd). • Build comprehensive automated tests, including unit, integration, and benchmark tests. • Implement structured logging, metrics emission, and distributed tracing throughout services so that operators and on-call engineers have the signals they need to diagnose issues and reason about system behavior. • Lead code reviews and uphold engineering standards in Go projects. • Mentor and coach junior and mid-level engineers through code review, design review, pair programming, and structured knowledge sharing, helping the broader team grow in technical maturity and confidence over time. • Contribute meaningfully to internal Go libraries, shared platform tooling, and reusable patterns that accelerate development across multiple engineering teams and codify hard-won best practices. • Maintain comprehensive, current technical documentation — including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures — so that the system remains supportable, auditable, and easy to onboard new engineers onto over time. • Continuously evaluate Go ecosystem evolution and contribute to internal patterns.

• Design and develop advanced Java customizations within Windchill, including custom services, listeners, processors, validators, and helpers. • Extend the Windchill data model with custom types, attributes, and relationships using Type and Attribute Management (TAM). • Build custom JSP and HTML extensions, including custom tables, actions, and wizard pages. • Develop custom queues and background processes for asynchronous Windchill tasks. • Implement complex workflow expressions and robot delegates in Java, applying disciplined engineering practices and partnering closely with stakeholders to ensure outcomes are durable, well-documented, and aligned with broader team and platform standards. • Optimize performance of Java customizations, including profiling, query tuning, and caching strategies. • Adhere strictly to PTC customization best practices, ensuring upgrade-friendly customizations. • Lead migration efforts to retire legacy customizations to modern PTC-supported patterns, planning phased cutovers, building backward-compatibility shims where needed, and ensuring each migration step is reversible and well-monitored. • Conduct code reviews and uphold internal engineering standards, applying disciplined engineering practices and partnering closely with stakeholders to ensure outcomes are durable, well-documented, and aligned with broader team and platform standards. • Collaborate closely with functional consultants to translate complex requirements into clean Java designs. • Provide hands-on post-go-live and hypercare support, working closely with operations teams to triage incidents quickly, identify root causes, and drive durable fixes that improve long-term system stability. • Maintain comprehensive, current technical documentation — including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures — so that the system remains supportable, auditable, and easy to onboard new engineers onto over time. • Mentor and coach junior and mid-level engineers through code review, design review, pair programming, and structured knowledge sharing, helping the broader team grow in technical maturity and confidence over time.

• Design and implement large-scale distributed backend systems using Java, Go, Scala, or similar high-performance languages • Architect data partitioning, replication, and consistency strategies appropriate to each workload’s requirements • Build resilient APIs and event-driven services with strong observability, idempotency, and graceful degradation patterns • Optimize systems for latency, throughput, and cost, using profiling, benchmarking, and load testing • Lead detailed architecture reviews, technical design discussions, and trade-off analyses • Implement robust failure-handling patterns including retries, timeouts, circuit breakers, bulkheads, and saga workflows • Design and operate data stores at scale, including relational, key-value, document, and search engines • Build comprehensive observability into services with structured logs, metrics, and distributed tracing • Drive incident response and post-incident learning for critical backend services • Mentor mid-level engineers and lead by example in code quality, design, and operational rigor • Partner with SRE and platform teams to drive reliability improvements and reduce operational toil • Contribute to long-term architecture and platform strategy, helping shape multi-year technical roadmaps and ensuring near-term execution remains aligned with the broader engineering direction • Maintain comprehensive, current technical documentation — including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures