Top Tech Jobs & Startup Jobs

Design, develop, and optimize Windchill Java customizations (services, listeners, processors, JSP/UI), extend data model via TAM, implement workflows and background processes, support upgrades and migrations, profile and tune performance, provide post-go-live support, maintain documentation, and mentor junior engineers.

Lead design and implementation of an enterprise data platform spanning ingestion, storage, processing, governance, and consumption. Define architecture standards (lakehouse, warehouse, streaming), design pipelines balancing latency/cost/reliability, integrate catalog/lineage/security, drive cost optimization and DR/HA strategies, mentor engineers, and produce architecture artifacts while partnering with ML, BI, and product teams.

Design, optimize, and deploy ML models for resource-constrained edge devices. Apply compression, quantization, pruning, and hardware-aware tuning. Build cross-platform inference runtimes, on-device update/versioning workflows, hybrid edge-cloud architectures, telemetry, security/integrity protections, benchmarking suites, and documentation. Collaborate with hardware, firmware, and product teams and drive responsible AI practices.

Design, deploy, and operate enterprise storage platforms (NetApp, Pure, Ceph) across block, file, and object storage. Implement SAN/NAS/object solutions for VMware, Kubernetes, and databases; automate with Ansible/Terraform/REST APIs; manage backups, replication, FabricPool/cloud tiering, performance, capacity, observability, and ransomware protection. Lead upgrades, firmware lifecycle, cost optimization, and troubleshooting across array, network, and host layers.

Design, build, and operate high-throughput, low-latency backend platforms and shared services (request routing, caching, event pipelines, async jobs). Drive multi-region, fault-tolerant designs, observability and SLOs, rate-limiting, and developer-facing SDKs. Lead incidents, mentor engineers, produce design docs and runbooks, and evaluate emerging platform technologies to raise organizational engineering standards.

Design, execute, and operationalize fine-tuning workflows for large language models (supervised, DPO, RLHF). Lead dataset curation, build scalable distributed training pipelines, tune hyperparameters, implement parameter-efficient methods (LoRA/QLoRA), run evaluations (automated and human), operate GPU cluster training, manage model artifacts, and mentor engineers while translating LLM research into production-ready solutions.

Design and implement high-performance backend services and cloud-native applications in Go. Build Kubernetes-native tooling (controllers, operators, CLIs), implement gRPC/REST APIs, integrate messaging and data stores, profile and optimize performance, and add observability. Lead code and design reviews, mentor engineers, produce tests and documentation, and contribute to shared platform libraries and operational runbooks.

Lead cross-team architecture and execution of large engineering initiatives. Define standards, mentor senior engineers, drive reliability and scalability improvements, lead incident response, author RFCs, contribute hands-on code, and partner with product and executives on technical roadmaps.

Design, develop, and operate end-to-end integration scenarios in SAP Integration Suite/CPI connecting S/4HANA and other systems. Build iFlows, adapters, Groovy/Java scripts, API Management, migration from PI/PO, performance tuning, monitoring, and provide post-go-live support and documentation.

Design, implement, and optimize high-performance CUDA kernels and libraries for AI/HPC workloads. Profile and tune GPU code, optimize multi-GPU training, integrate custom operators into ML frameworks, develop benchmarks and regression tests, and advise on GPU architecture adoption while mentoring engineers and documenting performance playbooks.