Top Software Engineer Jobs

Designs and owns full-stack AI developer productivity products and platforms, including desktop applications, backend APIs, data pipelines, dashboards, telemetry, integrations, and developer tools. Leads technical design for scalable AI coding tool integrations, translates ambiguous requirements into production software, and manages reliability, observability, performance, security, and supportability. Evaluates human- and AI-generated code and advances prompt engineering and system-context practices for reliable AI-assisted development.

Builds end-to-end AI Copilot experiences across voice, vision, text, and action. Owns features from concept through scalable production, collaborates with applied AI researchers, rapidly ships experiments, analyzes usage, and iterates on products used by millions. The role requires full-stack frontend and backend expertise, scalable web API development, strong Python skills, and comfort working in ambiguous, fast-moving environments.

Lead the design and development of software applications, collaborate with teams, mentor developers, and improve codebases to meet business goals.

Own product and engineering as a technical co-founder, writing production code and leading architecture, reliability, observability, AI delivery infrastructure, unit economics, roadmap, customer-facing technical work, and founding-team recruitment. Harden the AI voice front desk for production, scale managed AI worker delivery, balance quality and cost, support legal privacy requirements, and expand the platform into additional AI staff roles.

Own the technical direction and product engineering for an AI legal front desk platform. Build production-grade voice and workflow systems, reliability and observability infrastructure, managed AI delivery capabilities, and scalable multi-tenant architecture. Balance AI quality with cost-per-call economics, support customer and investor conversations, convert pilots into paying customers, recruit the founding engineering team, and expand into additional AI staff roles and self-hosted models.

Own product and engineering as a technical co-founder, writing production code and setting technical direction. Build reliable voice and workflow systems, internal AI delivery infrastructure, observability, audit trails, and secure multi-tenant SaaS. Balance AI quality with cost-per-call economics, support customer and investor discussions, expand the AI workforce roadmap, recruit the founding engineering team, and develop self-hosted model capabilities for legal and privacy needs.

Design, develop, and operate secure, scalable, AI-enabled enterprise applications and integrations using .NET, React/Next.js, Azure, distributed systems, and modern architecture patterns. Build cloud-native services, APIs, microservices, observability tooling, AI workflows, and secure integrations for regulated business processes. Contribute to architectural strategy, mentor engineering teams, promote secure SDLC practices, and collaborate across product, business, implementation, and client-facing teams.

Design and build scalable enterprise applications in C#/.NET (APIs, microservices) and integrate AI capabilities (Python, LLMs, RAG, vector DBs, agentic frameworks). Own CI/CD, Azure DevOps workflows, containerized deployments, and collaborate across teams to deliver AI-enabled operational automation and agent integrations.

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.