Top Entry Level Software Engineer Jobs in San Francisco Bay Area, CA

Build full-stack, agent-driven software for SOX control testing and internal audit workflows. Design reliable and observable LLM agent systems, create structured audit deliverables, own end-to-end technical workstreams, and collaborate with product, design, auditors, and domain experts. Engineers will help shape agentic architecture, AI tooling, evaluation practices, and product direction while working on ambiguous 0-to-1 initiatives.

Build high-scale internal observability systems covering metrics, logs, traces, cost attribution, chargeback, compliance, and auditing. Partner with backend and platform teams to instrument services, evaluate observability infrastructure, and scale systems for Vercel’s production traffic. The role requires TypeScript, production experience with Go, Rust, or Zig, distributed systems expertise, cloud infrastructure knowledge, and familiarity with observability tooling.

Build and ship production software across Superhuman’s AI-powered productivity products. Develop features using modern web frameworks, large language models, natural language processing, and intelligent automation. Contribute to scalable distributed systems, testing, deployment, and system design while collaborating with product, design, and engineering teams. The role emphasizes mentorship, rapid growth, independent execution, and delivering reliable user experiences to millions of users.

Design and own secure, scalable wallet infrastructure for custody, key management, transaction signing, authorization, recovery, and multichain systems. Architect support for MPC, HSMs, secure enclaves, TEEs, smart contract wallets, account abstraction, and emerging cryptographic approaches. Define security boundaries, policy engines, secrets management, authentication, and programmable authorization while making foundational build-versus-buy decisions and guiding systems from first principles through production.

Build and operate scalable Twitch data platform capabilities, including data warehouses, pipelines, storage, transformation, and data movement tools. Improve reliability, flexibility, and scalability across high-volume distributed systems, collaborate with engineering peers, contribute to technical vision, and enhance workflows using AI coding tools.

Build and operate customer-facing product experiences for Cartesia’s real-time voice and multimodal AI models. Own work from discovery and prototyping through implementation, launch, analytics, experimentation, and iteration across frontend, backend, APIs, and operational concerns. Improve model evaluation, configuration, integration, usability, and developer experience while partnering with product and design teams.

Build and own backend infrastructure, MCP gateway features, enterprise deployments, connectors, and agentic systems end to end. The role emphasizes secure architecture, permissions, trust boundaries, auditability, production reliability, and rapid product iteration. Engineers work across the stack using AI coding agents, make product and UX decisions, support customer deployments, and address security-sensitive issues. The company hires across experience levels and values shipping ability, judgment, range, and fast learning.

Develop and improve Temporal Proxy, an extensible open-source solution for Temporal Cloud and customers. Implement request handling, configuration, authentication and authorization integrations, encryption hooks, observability, testing, documentation, and production debugging. Collaborate with security, infrastructure, server, and engineering teams to deliver reliable proxy capabilities and improve developer experience.

Early-career software engineer designing, developing, and maintaining software across systems, infrastructure, machine learning, inference, and user-facing products. Responsibilities include collaborating cross-functionally, owning projects, participating in code reviews, debugging, optimizing performance, and contributing to technical direction. Candidates should have strong computer science fundamentals, hands-on development experience, Git proficiency, creative problem-solving ability, and effective communication skills.

Deploy across portfolio companies to understand challenges, solve technical problems, and deliver business-impacting software solutions. Build shared technology services and value-creation playbooks, use AI coding tools to accelerate development, and provide technical leadership and mentorship. The role requires adapting to diverse codebases and technology stacks while combining strong software engineering, strategic thinking, commercial awareness, communication, and hands-on problem-solving.

Looking for a Founding Software Engineer to develop and implement software products for industrial automation, focusing on modern technology integration with manufacturing processes.

Build and own core systems for an agentic integration platform, including multi-agent orchestration, integration runtime infrastructure, durable execution, self-healing systems, and knowledge management. Work directly with founders, establish engineering patterns, make architectural decisions, and ship production software continuously using TypeScript, React, Bun, Effect-TS, PostgreSQL, Kubernetes, and AWS.

Build and operate Kubernetes-based controllers, distributed services, APIs, and provisioning systems for OpenAI’s global GPU compute infrastructure. Manage machine and cluster lifecycles across hardware platforms and providers, including network boot, firmware, operating-system images, drivers, configuration, upgrades, recovery, and decommissioning. Improve reliability, concurrency, throughput, latency, and reconciliation while handling partial failures. Integrate new sites and GPU hardware generations and collaborate with hardware, networking, data-center, and infrastructure teams.

Dragonfly is seeking Software Engineers for various portfolio companies, focusing on crypto technologies. Engineers of all experience levels are needed across multiple stacks.

Build internal fullstack products and human-robot interfaces for operating, monitoring, debugging, and deploying robots. Responsibilities include realtime video and robot-state systems, safety-focused UX, on-device and cloud architecture, fleet versioning, observability, workflow measurement, and direct user-driven product development. The role partners with researchers, operators, and roboticists across lab, warehouse, and field environments.

Build and operate highly reliable card-issuing software and tooling across authorization, clearing, settlement, certification, and network integrations. Serve as a technical expert on card-network specifications, protocols, mandates, and production behavior. Lead complex cross-team engineering work, debug protocol-level issues, influence network requirements, mentor engineers, improve platform reliability, and participate in on-call support for critical financial systems.

Build full-stack research tools for creating, reviewing, submitting, and monitoring reinforcement-learning environments and tasks. Own review and acceptance workflows, rollout and transcript inspection, quality signals, versioning, catalog experiences, and self-service authoring interfaces. Collaborate with researchers, vendors, and domain experts to improve training-data quality and accelerate the path from task ideas to trusted training data.

Build backend infrastructure for a real-time blockchain trading platform, including risk and liquidation engines, state machines, distributed services, market-data pipelines, trading-venue integrations, REST and WebSocket APIs, and deployment automation. Optimize asynchronous Rust systems for high throughput and low latency, while implementing databases, monitoring, alerting, and reliable production operations.

Develop customer-facing ChatGPT and OpenAI API features end-to-end, collaborate with engineering, research, product, design, and operations teams, talk with users to solve problems, and optimize applications for speed, scale, safety, and reliability.

Design, build, and maintain core platform products and systems. Collaborate with product managers and engineers to deliver high-quality experiences. Participate in technical blueprinting, code reviews, and documentation while owning tasks and understanding customer and business needs.

Build product features end-to-end, improve performance and reliability, and create internal tools. Collaborate cross-functionally, work on web UI and backend components, and iterate based on user impact and metrics.

Build and operate scalable backend infrastructure powering ChatGPT image generation and editing. Responsibilities include developing APIs, services, orchestration systems, storage platforms, and distributed infrastructure; optimizing reliability, latency, throughput, and cost; productionizing AI research; making architecture decisions; collaborating with product, research, mobile, web, and platform teams; and contributing through technical leadership, mentorship, and operational excellence.

Build and maintain AI-driven workflows, agentic systems, automated operations tooling, cloud infrastructure, and CI/CD pipelines. Handle monitoring, incident triage, backend production issues, and field-operations support. Contribute across the full stack, communicate technical decisions to non-engineering stakeholders, and improve manual processes through automation. Required capabilities include cloud infrastructure, LLM and MCP development, Linux, CI/CD, full-stack engineering, and strong communication.

Software Engineers are matched confidentially with Dragonfly portfolio companies hiring across crypto and blockchain. Roles may span backend, frontend, full-stack, mobile, infrastructure, data, security, machine learning, and DevOps. Candidates should have software engineering experience and an interest in crypto, blockchain, or open-source technologies. Startup or crypto-native project experience is preferred. Opportunities may be remote, hybrid, or in-person worldwide.

Build and ship product features across user-facing interfaces and backend systems for AI coding products. New graduates will own work end to end, improve product quality, prototype ideas, fix bugs, and collaborate with a small, high-ownership engineering team. Candidates should demonstrate strong engineering fundamentals, sound judgment using AI tools, fast learning, and an exceptional technical project or shipped product.