Top Software Engineer Jobs

Own customer integrations for AI agent evaluations from scoping through delivery. Read API documentation, manage credentials, build custom integrations, run evaluations, assess AIUC-1 compliance, communicate technical results, and surface failure modes. Collaborate with customers, sales, delivery, standards, and core engineering teams while turning recurring field solutions into reusable product capabilities.

Senior individual-contributor owning cost and AI-enablement for a petabyte-scale analytics platform. Build and operate data warehouse, ingestion pipeline, and Airflow; deliver cost-attribution, forecast-driven autoscaling, and production Gen AI (NLP-to-SQL/RAG) systems. Hands-on coding (~70%) plus technical coordination and on-call production support.

Leads and develops a customer-facing Forward Deployed Engineering team that accelerates adoption of Target’s AI platforms. Provides architecture guidance, technical onboarding, prototyping, implementation support, and developer enablement. Partners with platform, product, security, responsible AI, and business teams to create scalable AI solutions and reusable engineering patterns. Oversees governance, support channels, platform adoption, documentation, and continuous improvements while remaining involved in architecture, code reviews, and complex technical problem-solving.

As a Forward Deployed Engineer, you will develop AI agents and automation workflows, collaborate with teams, and ensure secure, reliable solutions integrating with various systems.

Join Raft to innovate national defense technology. Collaborate on AI, machine learning, and UX/UI design to create impactful defense solutions.

Lead end-to-end product builds by orchestrating AI coding agents to create applications, automations, and agents. Translate customer needs into deployable solutions, instrument and iterate on outcomes, validate AI outputs for security and quality, engage with customers to find automation opportunities, and document prompts and patterns for the team.

Lead full-stack development in AI-native solutions, design responsive features, ensure system quality, and collaborate on product iterations.

Leads the design, development, and deployment of scalable, reliable software and infrastructure solutions. Builds AI agents, automation workflows, observability integrations, and monitoring systems using technologies including C++, Python, Java, Claude, Codex, BigPanda, ITMP, and Prometheus. Collaborates across teams, drives engineering standards, mentors junior engineers, and manages complex end-to-end projects.

The Senior Machine Learning Engineer will develop NLP solutions, manage datasets, optimize performance metrics, and work on ML applications for healthcare.

Build the enterprise platform for an AI creative product, including workspaces, permissions, SSO, audit logs, usage-based billing, invoicing, payment integrations, and security foundations. Develop backend services, APIs, and polished React/Next.js administrative interfaces for multi-tenant customers. Collaborate with founders, sales, and customers to define and ship enterprise features while taking increasing ownership of platform surfaces.

Build the enterprise platform for an AI creative product, including workspaces, roles, permissions, SSO, audit logging, usage-based billing, invoicing, and payment infrastructure. Design scalable APIs and multi-tenant architectures, strengthen security and reliability, and create React/Next.js administrative experiences. Partner with founders, sales, and customers to deliver enterprise requirements, establish engineering practices, and help shape the enterprise engineering team.

Design and operate scalable, event-driven backend systems in Python to power agentic AI workflows and real-time financial infrastructure. Own APIs, data architecture, reliability primitives, and platform foundations while partnering with ML and product teams to productionize AI-native financial systems.

Design and operate scalable, event-driven backend systems in Python for AI-native financial products. Build typed APIs (FastAPI + Pydantic), own data and ledger architectures, develop reliability primitives, partner with ML teams to productionize models, and ship platform foundations for audited, high-throughput financial workflows.

As a Knowledge Development Engineer, you'll architect and deploy AI-driven production systems, reverse-engineer existing systems, and guide product development. You'll synthesize customer feedback and lead experiments to connect technical development with business outcomes.

The Knowledge Development Engineer leverages AI agents to solve customer problems by building applications and automating workflows, focusing on delivery speed and quality.

Responsible for developing and enhancing an AI SDK, ensuring high performance and integration with deployment platforms, while collaborating with cross-functional teams and engaging with the open-source community.

Leads multiple product engineering teams across Savvy’s product lines, including its advisor-facing AI platform. Owns engineering strategy, execution, architecture, organizational design, staffing, technical quality, and delivery accountability. Partners with Product and Design to prioritize investments, guide system design, resolve dependencies, and connect engineering decisions to customer and business outcomes. Provides hands-on technical leadership through code reviews, prototypes, debugging, and AI implementation guidance while developing engineering leaders and scaling the organization.

Build OpenArt’s enterprise AI platform for teams and organizations. Responsibilities include developing workspaces, RBAC, SSO/SAML, audit logging, usage-based billing, invoicing, payment integrations, scalable APIs, multi-tenant architecture, and polished React/Next.js administration experiences. The role also involves improving security, data isolation, reliability, and SOC 2 groundwork; partnering with founders, sales, and customers; making infrastructure decisions; and establishing enterprise engineering practices as the first hire.

The role involves leading AI networking system transformations, collaborating with teams on product features, and managing customer engagements for innovative networking solutions.

Develop and maintain reliable, secure, and high-performance GPU cluster infrastructure for AI researchers. Design solutions for cluster validation, monitoring, operations, reliability, and performance at scale. Research and apply AIOps and Agentic AI to reduce operational toil, support self-service improvements, and participate in on-call operations. The role also involves software development on Linux, container orchestration, automated deployments, and potentially full-stack platform development and Slurm scheduling.

Lead architecture, bring-up, validation, optimization, and deployment of networking infrastructure for large-scale AI training and inference. Define networking requirements, design Layer 3/4 and RDMA/AI fabric solutions, develop validation and observability tooling, perform packet-level debugging and root-cause analysis, and collaborate across silicon, firmware, software, and Azure teams to ensure performance, scalability, and reliability of hyperscale AI clusters.

Leads Cisco’s Customer Engineering organization, establishing its operating model, escalation processes, SLAs, and global team. Oversees high-stakes enterprise production incidents, root-cause analyses, AI-driven diagnostic automation, engineering rotations, and product feedback. Partners with core engineering, product management, customer experience, and sales to improve reliability and reduce resolution times. Recruits and develops customer-facing engineering leaders while managing operational metrics, hotfix governance, runbooks, and customer outcomes.

Designs and delivers AI-augmented enterprise integration platforms, API ecosystems, and autonomous workflows. Responsibilities include developing event-driven distributed systems, integrating SAP and SaaS applications, managing API lifecycles, supporting EDI deployments, implementing secure identity and access controls, and building CI/CD and observability capabilities. The role uses agentic AI, workflow automation, and intelligent monitoring to enable self-healing, adaptive integration across cloud and enterprise environments.

The Senior Application Engineer will develop cloud-native applications and APIs, focusing on AI products, utilizing AWS technologies, and engaging in Agile project cycles.

Lead engineering team to develop AIPerf, an open-source benchmarking tool for LLM inference performance, while overseeing technical direction and mentoring engineers.