Top Software Engineer Jobs

Develop and sustain cloud software and distributed systems supporting cyber intelligence and AI/ML capabilities. Responsibilities include requirements analysis, Java software development, cloud deployment, integration, testing, RESTful services, analytics, Hadoop ecosystems, Linux systems, and technical documentation. The role requires AWS expertise, Kubernetes, infrastructure as code, CI/CD, microservices, large-scale data processing, and active TS/SCI clearance with polygraph.

Develop and sustain cloud software supporting cyber intelligence and AI/ML capabilities on large-scale compute clusters and AWS infrastructure. Responsibilities include requirements analysis, software development, integration, testing, validation, deployment, maintenance, monitoring, and issue resolution. The role uses distributed NoSQL technologies, big-data frameworks, cloud services, AI/ML algorithms, LLMs, RAG, and agentic workflows to support national security missions.

Develop and maintain cloud software supporting AI/ML and national security missions. Responsibilities include requirements analysis, software development, AWS cloud integration, distributed systems engineering, microservices, testing, troubleshooting, and sustainment. The role uses Java, Linux, Kubernetes, infrastructure-as-code, CI/CD, big-data technologies, RESTful services, and AI/ML frameworks including LLMs and RAG. An active TS/SCI clearance with polygraph is required.

Develop and sustain cloud software supporting cyber intelligence and AI/ML capabilities on large-scale compute clusters and AWS infrastructure. Responsibilities include requirements analysis, software development, integration, testing, validation, deployment, enhancement, monitoring, and issue resolution. The role uses distributed NoSQL and big-data technologies, cloud architecture, AI/ML tools, microservices, containers, and infrastructure-as-code. Candidates must have at least two years of relevant software engineering experience and an active TS/SCI clearance with polygraph.

Develop and integrate cloud software supporting cyber intelligence and AI/ML capabilities on AWS and large-scale compute clusters. Responsibilities include requirements analysis, Java development, RESTful services, distributed systems, cloud deployment, DevOps, container orchestration, testing, integration, Linux scripting, and troubleshooting. The role also involves big-data technologies, Hadoop ecosystems, LLMs, RAG, analytics, and secure software engineering for national security missions.

Lead the transformation of Java full-stack engineering teams to AI-native development. Define strategy, tooling, workflows, governance, quality gates, and adoption roadmaps for AI agents across the SDLC. Build an AI engineering center of excellence, train developers, integrate coding and testing assistants with CI/CD and DevSecOps, establish security and IP controls, measure outcomes, and scale practices across client engagements.

Build the enterprise platform for an AI creative product, including workspaces, roles and permissions, SSO, audit logs, usage-based billing, invoicing, payment integrations, and security foundations. Develop backend services and APIs for multi-tenant usage patterns alongside polished React/Next.js administration and billing experiences. Collaborate with founders, sales, and customers to convert requirements into production features while taking increasing ownership of enterprise platform surfaces.

Design and build NVIDIA’s enterprise AI agent platform, including agent blueprints, runtime safety and policy enforcement, multi-agent orchestration, credential brokering, checkpointing, observability, evaluation, and self-improvement loops. Deploy reliable long-running services at scale, integrate enterprise systems, support secure execution, and participate in on-call operations. The role requires extensive distributed systems or infrastructure experience and hands-on agent development.

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.

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.