Top Software Engineer Jobs

The Technical Lead will oversee software architecture, mentoring teams and leading the design and implementation of AI-augmented enterprise software solutions.

The Principal Software Engineer will lead the design and build-out of an AI Context Layer, ensuring high-quality data for AI systems, while managing access control and developer interfaces, and leading cross-team projects.

As a Software Engineer in Frontier AI Infrastructure, you'll design secure systems for the public sector, improve engineering standards, and collaborate with cross-functional teams to meet government requirements. You'll also participate in customer engagements and contribute to the product strategy while ensuring compliance with federal regulations.

As a Staff Software Engineer, you'll design and deliver a core data platform, focusing on architecture, pipeline components, and AI integration. This hands-on role emphasizes creating production code and establishing technical standards within a small team.

Design, build, and maintain scalable enterprise full-stack applications using Java, Spring Boot, microservices, and modern front-end frameworks. Implement cloud-based solutions on AWS, contribute to CI/CD and DevOps automation, optimize performance and security, and integrate AI-driven capabilities using Python and orchestration tools like LangChain and LangGraph.

You will build agentic AI products across web, backend, and iOS, owning features end-to-end and mentoring junior teammates.

The HPC & AI Performance Engineer will execute benchmarking projects, analyze performance, and optimize HPC systems using scientific software and methods.

Lead design and rewrite of cloud-native core systems. Build scalable back-end services and front-end features, drive architecture and testing discussions, mentor engineers, and improve telemetry, performance, and reliability.

Build, operate, and scale cloud-native backend services and APIs for a high-volume vehicle marketplace. Embed AI-driven capabilities into features, use AI tools to accelerate development, participate in on-call rotations, improve reliability, and collaborate with Product, Data, Infrastructure, and SRE teams to deliver production-ready systems.

The Advisor Lab Automation Software Engineer will design and implement software integrations for lab automation, focusing on AI-driven processes, while providing technical leadership and mentoring.

As a Software Engineer at Paces, you will build AI automation solutions to expedite power development, working closely with industry experts and taking ownership of projects to enhance scalability and features.

Lead development and commercialization of Cloud Data solutions: design cloud data architectures, lead migrations and ETL/ELT, operationalize AI across clouds, support strategic sales pursuits, enable and train solution architects, secure partner co-investment, and provide steering‑committee oversight to mitigate delivery risk and drive practice growth.

Early-career full stack internship developing frontend and backend features under senior guidance. Integrate AI coding tools into workflows, translate product requirements to implementations, contribute across the product lifecycle, and suggest cross-team process improvements while learning full-stack practices.

Design, build, test and support batch and streaming data pipelines and curated datasets on a lakehouse/AI data platform. Work across ingestion, transformation, modeling, optimization, data quality and reconciliation; improve platform tooling and standards; collaborate with stakeholders and lead delivery and technical design for workstreams.

Build end-to-end AI integrations in a cybersecurity platform: gather contextual security data, call and optimize AI services, map responses to actionable UI (React), implement error/fallback handling, monitoring, caching, and user feedback loops while working directly with customers.

The AI Tools Architect/Tech Lead role involves designing AI personas, maintaining AI configuration artifacts, and leading impactful engineering teams. The candidate will innovate with AI coding tools, evaluate code review agents, and drive organizational change through documentation and collaboration across teams.

Build and maintain production AI-driven systems including call-scoring pipelines, multi-tenant Next.js/Supabase dashboards, a Velocify-replacement lead platform, AI voice agent integrations, Salesforce administration, and internal automation workflows. Ensure CI/CD, testing, security, and reliable real-time integrations for client-facing and internal compliance products.

Design and implement graph-based search services and scalable backend systems using Java and Spring Boot. Build GraphQL/REST APIs, integrate with AWS services and databases, ensure observability with New Relic and Coralogix, mentor engineers, and collaborate on search and recommendation features to deliver reliable, cloud-native solutions.

The role involves building and improving AI voice features, debugging issues, and collaborating with product teams to enhance user experience.

Design and implement high-performance backend C++ systems for defense autonomy products. Build scalable, reliable infrastructure for contested environments, collaborate with researchers and customers, own end-to-end delivery, and shape site engineering culture and standards in Ann Arbor.

Design and implement high-performance C++ backend systems for defense autonomy products. Build scalable, reliable infrastructure for contested environments, collaborate with researchers and customers, own architecture through deployment, and support Ann Arbor site growth while interfacing with DoD programs.

Design and implement high-performance C++ software for Axion, build and extend real-time simulation environments, develop scalable infrastructure for multi-domain autonomous operations, partner with researchers and defense customers to translate mission requirements, and own end-to-end engineering execution from architecture through deployment.

Build and productionize scalable backend services, APIs, and AI workflows to connect requirements, modeling, validation, and test data for autonomous vehicle programs. Implement traceability, versioning, dashboards, and KPIs, refactor prototypes into certifiable systems, and collaborate with systems engineering, safety, and autonomy teams to support compliance and validation at scale.

Lead design and implementation of a distributed simulation, modeling, and emulation environment for high-performance AI hardware. Define the simulation roadmap, build simulation infrastructure from scratch, integrate estimation tools, model training/inference workflows on heterogeneous GPU/CPU/accelerator clusters, and collaborate with internal teams and external partners.

Design, build, and deliver AI-enabled, cloud-native full-stack solutions for Lending platforms. Lead components, implement APIs, CI/CD, observability, and AI patterns (Prompt Engineering, RAG). Mentor engineers, collaborate with architects and business partners, ensure security/compliance, and produce operational documentation and production-ready code.