Top Software Engineer Jobs

The Senior Software Engineer will explore AI solutions in healthcare, having experience in full-stack/backend development and startup culture.

As a Senior Software Engineer at Whatnot, you'll build AI tooling for internal use, developing workflows and infrastructure to enhance software delivery. You'll collaborate across teams to gather feedback and prioritize features in a rapidly evolving landscape.

Build and maintain scalable full-stack web applications across front-end and back-end systems. Develop RESTful APIs, integrate AI and machine-learning models using Python, manage SQL and NoSQL databases, and create GitHub Actions CI/CD pipelines. Collaborate with data scientists, troubleshoot and improve existing software, participate in code reviews, and apply modern DevOps, cloud, containerization, and microservices practices.

Build internal software and AI-powered systems that connect Product, Engineering, Sales, Marketing, Programs, and Operations. Responsibilities include integrating SaaS tools, APIs, databases, LLMs, and AI agents; automating workflows; creating systems that translate product specifications into engineering work; maintaining synchronized documentation; supporting controlled government proposal workflows; and improving how employees and agents collaborate.

Build and own mobile experiences for clinicians using Flutter, Swift/iOS, and Kotlin/Android. Develop AI-native workflows involving real-time transcription, ambient documentation, multimodal inputs, offline functionality, and intelligent recommendations. Collaborate with clinicians, product, design, AI, and backend teams from discovery through launch. Ensure performance, accessibility, reliability, analytics, testing, observability, and release readiness while contributing to mobile strategy and mentoring engineers.

Designs and maintains AI-powered full-stack applications using React, TypeScript, Python, and FastAPI on Azure. Builds cloud-native, containerized solutions, data pipelines, CI/CD workflows, Terraform infrastructure, dashboards, and secure production systems. Integrates LLMs, AI agents, and machine learning models while partnering with data scientists and business stakeholders. Provides technical leadership, establishes engineering standards, mentors team members, and manages the full software development lifecycle.

Develop and support unattended RPA robots in an enterprise environment using UiPath, Office 365, APIs, AI Fabric, Document Understanding, and OCR. Responsibilities include technical design, workflow automation, robot monitoring, operational support, customer collaboration, process analysis, technical documentation, and deadline management. The role also requires strong communication, analytical, and problem-solving skills, with web development experience and UiPath Advanced RPA Developer certification preferred.

Designs, develops, and scales enterprise process automation, custom applications, APIs, integrations, AI agents, and intelligent workflows. Partners with architects and business stakeholders to translate requirements into scalable Microsoft-based solutions. Responsibilities include integrating ERP, CRM, CPQ, databases, and cloud platforms; troubleshooting and optimizing software; participating in architecture reviews; documenting solutions; evaluating emerging technologies; and supporting governance, security, and compliance.

Build and maintain scalable Python-based AI applications under senior guidance. Assist with requirements, feature implementation, data modeling using Pydantic, code reviews, troubleshooting, testing, and CI/CD. The role requires collaboration, communication, and willingness to learn modern Python tools, frameworks, and libraries. Candidates should understand object-oriented programming, REST APIs, large language models, and AI coding tools. The position is fully remote within the United States.

Lead architecture and development of custom business applications that automate legacy workflows for SMB clients. Translate business processes into scalable CRM, project-management, integration, and operational software using AI-assisted development through Replit. Ensure application security, reliability, infrastructure stability, and performance. Design integrations with legacy systems such as Sage 300, and eventually recruit and mentor a development team while establishing AI-augmented engineering practices.

Own end-to-end development of AI product demos, including React and TypeScript interfaces, streaming chat and agent workspaces, backend-for-frontend services, database schemas, deployment, observability, and on-call. Partner on app-builder tooling, design systems, agent-facing CLI and deployment experiences, accessibility, localization, audit trails, and enterprise readiness. Debug across backend and Kubernetes infrastructure while delivering reliable, AI-native product experiences.

Own the AI inference and runtime platform, including open-weight model serving, Kubernetes operators and autoscaling, GPU infrastructure, stateful vector and graph stores, and secure microVM-based agent sandboxing. Build Rust, Python, and Kubernetes control-plane services; manage infrastructure as code, observability, metering, lifecycle operations, upgrades, backups, and failover. Establish security controls, open-source standards, and reliable production operations across cloud and managed GPU environments.

Design, implement, test, and maintain full‑stack software across backend and frontend. Participate in full product lifecycle, review peer code, create documentation, collaborate globally, and help drive strategic goals.

Design, build and maintain backend services and data pipelines; drive technical design and implementation; ensure product and technical excellence through testing, performance tuning, instrumentation, and automation; collaborate across global teams and lead projects in distributed, large-scale systems.

As a Senior Staff Machine Learning Engineer, you will drive AI product development, collaborate with cross-functional teams, and enhance ML models at scale.

Lead Unity architecture and build persistent, multi-user spatial systems for mobile and wearables. Design spatial persistence, synchronization, AI-assisted content pipelines, and define long-term platform direction as a founding technical contributor.

Design and build the distributed systems layer powering a spatial computing platform: real-time coordination, persistent world state, APIs, AI platform infrastructure (vector search, retrieval, agent orchestration), and scalable services to support many concurrent users and third-party developers.

You will tackle AI challenges, develop scalable software and collaborate with teams to enhance healthcare navigation using AI solutions.

Build and scale backend and full‑stack systems powering patient booking, clinician routing, logistics, and device integrations. Ship end-to-end features, design APIs and data models, solve scheduling/dispatch challenges, integrate with external health systems and medical devices, and own projects from 0→1 while collaborating with product, data, ops, and clinical teams.

Build and scale backend and full-stack systems powering patient booking, clinician routing, logistics, and device integrations. Own 0->1 projects, design APIs and data models, solve scheduling and dispatch challenges, integrate external health systems, and collaborate with product, data, ops, and clinical teams.

Tenure-track Computer Science faculty to teach in an ABET-accredited undergraduate program, conduct and publish research, advise majors, serve on committees, and teach across modalities (face-to-face, online, hybrid). Responsibilities include developing and delivering courses, mentoring students, and contributing to departmental service and scholarship.

Design and build end-to-end software primitives for AI infrastructure: domain modeling of power/datacenters/chips, authorization, audit, orchestration, vendor data ingestion (KMZ/BIM/Revit), and agent integration to enable safe, auditable agent operators. Ship production-quality systems and work across ambiguity to turn unstructured data into durable, composable entities.

Design, develop, and enhance secure, scalable software applications using modern programming languages and cloud-native technologies. Collaborate with product, design, and engineering across the SDLC, apply Agile and DevOps practices, and leverage automation and AI-driven tools to improve productivity and code quality.

Lead org-wide developer experience and AI-enabled developer workflows. Identify and solve high-leverage bottlenecks across build systems, monorepo tooling, CI/CD, and test reliability. Drive standards, enable monolith-to-modular migration, embed with product teams, mentor engineers, and deliver AI-native developer tooling and adoption at scale.

Build and maintain Go-based backend services and APIs on AWS for agentic AI workflows, including metadata suggestions, automated ownership reassignment, system deprecation, and agent/MCP inventory. Design database schemas and queries in PostgreSQL and MongoDB, integrate asset discovery tooling, map dependencies and user journeys, and refactor legacy code safely. Deliver tested features through Agile/Scrum while collaborating with program and customer teams.