Top Engineering Jobs

Build end-to-end product features from design through delivery, lead projects and product areas, shape technical systems and engineering practices, make pragmatic scalability decisions, and mentor teammates. The role requires strong frontend or backend expertise with the ability to work across the stack, product intuition, cross-functional communication, and ownership in a growing, mission-driven team.

Build and operate Benchling’s AWS cloud infrastructure, including Kubernetes, networking, secrets, observability, infrastructure-as-code, and cost governance. Develop internal APIs, automation, CLIs, serverless tools, and AI assistants. Own complex projects from design through production, establish technical standards, support incident response and on-call operations, and collaborate across engineering teams to improve secure, reliable, and cost-effective platform delivery.

Build and operate a scalable data platform supporting warehousing, orchestration, business intelligence, governance, and agentic workflows. Develop Python services, Terraform infrastructure, and developer tools for petabyte-scale data. Partner with data practitioners and product teams, establish security and reliability patterns, set technical direction, improve engineering standards, and mentor engineers.

Own and improve AWS production infrastructure, Kubernetes workloads, Terraform-based infrastructure, CI/CD pipelines, observability, security, incident response, and disaster recovery. Partner with engineers to improve development and deployment workflows, reliability, capacity, and cloud costs. Participate in on-call and deliver measurable platform improvements.

Leads Information Systems and Helpdesk teams while owning enterprise infrastructure across Microsoft systems, Microsoft 365, hybrid cloud, virtualization, storage, communications, and endpoint security. Oversees high-availability platforms supporting trading operations, including deployments, migrations, patching, monitoring, incident response, lifecycle management, security, compliance, and capacity planning. Serves as the senior escalation point and partners with network, security, and leadership teams on infrastructure strategy and technology roadmaps.

Design, build, and operate hybrid/multi-cloud and on-prem platform infrastructure. Lead cross-team initiatives, automate via IaC/CI-CD, apply AI tools for operations, implement observability and security best practices, provide tier-3 support and on-call coverage, and create reusable platform patterns and self-service capabilities for data and analytics workloads.

Industrial Engineering Interns will optimize warehouse workflows, analyze material flow, labor standards, equipment utilization, and performance data, and support lean process improvements. Responsibilities include developing recommendations for productivity, safety, quality, cost reduction, and throughput; collaborating with distribution center teams; conducting root cause analysis, time studies, planning, and performance reporting. The role requires hands-on work in distribution center environments and physical activity, including lifting and movement.

An early-career software engineering resident will build and deploy production services, use AI tools to accelerate development, improve system performance, and collaborate with product, design, and engineering teams. The 18-week program requires full-time, in-office work in New York City and offers potential full-time employment after completion. Residents are expected to ship a real contribution, apply strong computer science fundamentals, and work effectively in a fast-paced environment.

Build a greenfield, low-latency algorithmic execution platform in C++. Responsibilities include developing FIX gateways, exchange market data feed handlers, venue connectivity, pre-trade risk controls, platform infrastructure, audit logging, and algorithmic strategy migration. The role requires optimizing critical paths for microsecond-level performance while integrating U.S. exchanges and dark venues. Future work includes multi-asset execution, research and backtesting, and international market expansion.

Build and maintain reproducible research infrastructure for evaluating digital-twin and large language model systems. Responsibilities include automating experiments, implementing deterministic measurement pipelines, managing versioned datasets and human-participant data, maintaining research-production alignment, monitoring evaluation validity and compute costs, and supporting documented coding workflows. The role requires strong Python, data pipeline, cloud, concurrency, machine learning, and software engineering skills, with preferred experience in LLM systems, model fine-tuning, inference serving, experiment tracking, and generative agents.