Top Software Engineer Jobs

Design, build, and maintain scalable, resilient distributed systems and customer-facing technology platforms. Collaborate across the software lifecycle, participate in architecture sessions and code reviews, improve engineering practices, define products, and support reliability, security, monitoring, cloud infrastructure, DevOps, and application deployment. The role requires experience with modern programming languages, cloud services, microservices, databases, and generative AI or LLM-based applications.

The role involves building AI systems for customer support, creating automated insights, and operationalizing AI in workflows while collaborating with engineering and customer solutions teams.

As a Senior Software Architect, you will set the technical direction for client products, lead the integration of AI in development workflows, ensure system scalability and security, and mentor teams while aligning architecture with product strategies.

The Software Engineer will build AI-powered chatbot workflows, own features end-to-end, and collaborate in a fast-paced environment. Ideal candidates have a strong engineering foundation and experience with AI development tools, focusing on enhancing software processes.

Leads Snowflake’s AI Developer Experience engineering team, setting the roadmap for transforming software development and delivery through AI. Responsibilities include managing and developing engineers, improving code review latency, enabling access to modern AI tools and models, establishing agentic development pathways, and maintaining operational excellence through on-call management, incident response, postmortems, and support prioritization. The role requires strong technical judgment, cross-functional communication, measurable customer impact, and experience modernizing developer productivity and CI/test workflows.

Evaluate AI coding-agent interactions for usefulness, correctness, engineering judgment, reasoning quality, and developer trust. Provide clear, opinionated feedback, distinguish response-quality levels, and help define standards for excellent interactions with tools such as OpenAI Codex, Claude Code, and Cursor. This contract role requires staff- or principal-level software engineering experience and familiarity with modern AI-assisted development workflows.

Evaluate AI coding-agent interactions for usefulness, correctness, engineering judgment, reasoning quality, and user trust. Provide rigorous, opinionated feedback distinguishing response quality levels and help define best practices for tools such as OpenAI Codex, Claude Code, and Cursor. This contract role requires strong software engineering expertise, familiarity with AI-assisted development workflows, and the ability to assess code and explanations without deeply reviewing or executing every line.

Principal Software Engineer serving as a technical authority for backend, data, and AI platform architecture. Responsibilities include designing large-scale distributed data platforms, streaming systems, APIs, data models, and production AI systems using LLMs, RAG, vector search, and agent orchestration. The role establishes architectural standards, governance, observability, security, and cost controls; contributes high-impact production code; guides modernization; partners with product and engineering leaders; and mentors senior engineers.

The Conversion Engineering-Global Content Consultant role focuses on consulting Global Data Conversion Software Engineering, improving processes, and implementing AI solutions. Responsibilities include supporting offshore teams, driving project completion, and creating documentation for standards.

As a Founding AI Backend Engineer at Pakket, you'll enhance backend systems, debug the CV pipeline, and deploy services across warehouses, ensuring operational reliability and rapid feature deployment.

The role involves developing AI-driven compiler technologies, optimizing workflows, integrating learning systems, and collaborating on next-gen compiler capabilities for improved performance.

Lead AI software resiliency development, implementing features for reliability and fault tolerance in large-scale AI supercomputers, requiring hands-on coding and collaboration.

The Enterprise Data Architect develops and optimizes database solutions, migrating data, conducting tests, and ensuring information system functionality.

As a Cloudera Solutions Engineer, you will create customer-centric solutions, lead cross-functional collaborations, and transform customer feedback into product improvements.

Design, build, test, and deploy enterprise workflow automations and SaaS integrations. Develop REST API integrations, custom automation logic, event-driven workflows, and browser-based automations. Analyze business processes, create reusable templates, document solutions, follow governance and release practices, and collaborate with security, IT, architecture, business stakeholders, and users.

Leads and develops a software engineering team building Libra Solutions’ platforms in an AI-native, agentic delivery model. Owns delivery commitments, technical quality, architecture, code reviews, engineering standards, CI/CD, technical debt, and AI-assisted development practices. Partners with Product, Engineering, and business stakeholders while tracking delivery and system health metrics. Coaches engineers, supports hiring and retention, and establishes responsible AI, prompt engineering, and output-review standards.

Lead developer enablement for firmwide developer tools: run demos, workshops, and office hours; create reusable examples and guidance; drive responsible adoption of AI coding tools; gather feedback for platform/product teams; advocate for developers across risk, tooling, and leadership; and help shape adoption strategy and enablement content.

Build low-level device runtime software for OpenAI custom AI accelerators. Responsibilities include kernel scheduling, command submission, queueing, device memory management, synchronization, hardware-software interfaces, simulation-based validation, performance tuning, debugging, testing, tracing, and profiling. Collaborate with compiler, kernel, architecture, verification, firmware, and silicon teams to improve accelerator execution and co-design.

Lead design and delivery of SMAC workflow methodology and infrastructure to keep system specifications and manufacturing test specs aligned. Build production-grade Python pipelines, automated checks, CI gates, and agent-ready tooling that detect spec drift pre-silicon. Integrate workflows into program milestones, drive cross-org adoption across design, operations, and DFX, and apply AI where appropriate while ensuring reviewable, auditable artifacts.

Build and own full-stack AI applications, data APIs, dashboards, and cloud-native services. Develop Python and Node.js backends, React frontends, AI/ML integrations, RAG pipelines, authentication, API management, testing, CI/CD, and performance improvements. Collaborate with AI/ML engineers, data scientists, product, and design teams to deliver scalable, reliable, intuitive, and responsible AI experiences.

Develop custom ServiceNow applications for work order management, scheduling, and dispatch. Collaborate with stakeholders and technical SMEs, enhance event rules and CMDB binding, build REST integrations and user interfaces, and configure Discovery, Service Mapping, MID Servers, Service Graph Connectors, and multisource CMDB. The role also involves creating discovery patterns, preventing duplicate CIs, configuring identification rules, migrating patterns across environments, and supporting multi-tier service discovery.

Lead the design and delivery of Salesforce Agentforce and AI-powered solutions, including agents, topics, instructions, actions, automations, code, deployment methods, and data structures. Collaborate with clients, project managers, architects, developers, and designers to translate business needs into technical solutions. Oversee projects from design through development, testing, and deployment while staying current with Salesforce capabilities.

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.

Design, integrate, validate, and optimize large-scale AI networking infrastructure. Lead Layer 3/4 and RDMA-based fabric architecture, performance characterization, congestion management, packet-level debugging, telemetry, automation, and deployment for hyperscale AI training and inference clusters.