Top Artificial Intelligence Software Engineer Jobs

Develop software tools for molecule and protein visualization, machine learning model analysis, and chemical workflow management. Collaborate with machine learning engineers and medicinal chemists to productionize computational methods for molecular property prediction. Help scale infrastructure supporting massive datasets and parallel deep learning and molecular dynamics workloads while maintaining high code quality.

The Software Engineer will develop vertical workflows, implement scalable service architectures, ensure production-grade systems, evaluate AI performance, and collaborate cross-functionally to enhance engineering efficiency with AI tools.

Leads the design and development of JavaScript and TypeScript software solutions for commercial and government clients. Provides technical leadership, mentorship, code reviews, client collaboration, Agile guidance, architecture oversight, accessibility compliance, testing, and continuous improvement. Builds full-stack applications using Node.js and related frameworks while promoting secure coding, RESTful API design, and emerging technologies.

Administer and optimize Oracle databases in OCI, including Exadata, Autonomous Database, CDB/PDB environments, migrations, data transfers, performance tuning, backups, disaster recovery, patching, and federal security compliance. Execute legacy workload migrations using Data Pump, Transportable Tablespaces, and Zero Downtime Migration while maintaining high availability and protecting mission-critical DHS systems.

Conduct technical interviews for Power Platform specialists, assessing practical expertise in Power Apps, Power Automate, SharePoint Lists, Microsoft 365 integrations, security, and governance. Evaluate problem-solving, solution design, and business-requirement analysis skills. Provide structured candidate feedback, collaborate with recruiters on interview criteria, and refine technical assessments. The role also involves troubleshooting and maintaining Power Platform solutions, with interviewing or mentoring experience and Power BI knowledge preferred.

Build data lifecycle infrastructure for collecting, retaining, redacting, and deleting sensitive customer data. Responsibilities include PII and PHI detection, configurable retention policies, reliable deletion workflows, self-service APIs, LLM-backed anomaly detection, multimodal redaction, monitoring, auditability, and fault-tolerant systems at scale.

Lead and develop a software engineering team building Python-based healthcare revenue cycle automation. Responsibilities include people management, hiring, technical leadership, code reviews, agile delivery, architecture guidance, stakeholder collaboration, compliance oversight, process improvement, and delivery accountability. The role requires hands-on understanding of Python automation, Azure, healthcare data security, HIPAA, HITRUST, and engineering best practices.

Administer Microsoft SQL Server environments through monitoring, maintenance, patching, access control, performance tuning, backup and recovery, troubleshooting, and security remediation. Support data warehouse operations, schema changes, scheduled integrations, outage restoration, and recovery testing. Maintain operational documentation and runbooks while coordinating with architects, application teams, infrastructure, cybersecurity, data engineering, analytics, testing, and government stakeholders.

Lead a team of 4–6 engineers while spending 50–60% of your time building production systems. Own delivery, technical design, code quality, hiring, mentoring, and performance management. You’ll develop AI and agent products, integrate fragmented on-premise systems, improve scalability and caching, debug complex production issues, and collaborate directly with founders and customers. The role requires strong backend or full-stack engineering experience, cloud and distributed-systems expertise, and a willingness to work in person in San Francisco when based in the Bay Area.

Develop and sustain a cross-platform software test automation platform supporting mission requirements. Build Python and C++ applications, REST APIs, infrastructure automation, containerized workflows, and virtualized testing environments across Linux and Windows. Integrate DevOps, CI/CD, authentication, databases, and Infrastructure as Code tools. Troubleshoot systems, evaluate technical solutions, document implementations, and manage projects from requirements through deployment with minimal supervision.