Software Gigs

The AI Architect will lead the design, development, and deployment of enterprise-scale generative AI solutions across Azure and AWS, partnering with business and engineering leaders to define AI strategy and architecture standards. The role requires deep expertise in modern LLMs (Claude, Gemini, OpenAI), multi-cloud AI platforms, and enterprise architecture, with 10+ years in software/cloud architecture and 5+ years architecting AI/ML solutions. Key responsibilities include designing end-to-end GenAI solutions leveraging RAG, agentic AI, and multi-agent systems; establishing cloud-native deployment patterns; and defining governance, compliance, and responsible AI frameworks. The ideal candidate will serve as a trusted technical advisor to executives, mentor engineering teams, and drive AI adoption through reusable frameworks and reference architectures.

Staff engineer role focused on integrating autonomy software across Shield AI's Hivemind platform, spanning simulation, hardware-in-the-loop, and flight systems. Responsibilities include developing deep expertise in the autonomy stack, configuring and deploying multi-agent systems, integrating new autonomy capabilities, enabling platform bring-up on new robotic hardware, architecting integration tooling and deployment infrastructure, ensuring cross-platform compatibility, diagnosing integration defects via telemetry analysis, and optimizing CI/CD workflows. The role bridges engineering development and real-world autonomous applications, requiring systems integration expertise, robotics platform knowledge, and hands-on proficiency with sensor drivers, middleware, and deployment frameworks.

Lead technical delivery of complex autonomy capabilities for Shield AI's V-BAT and X-BAT unmanned aircraft platforms, spanning mission autonomy, payload integration, flight-control interfaces, and multi-agent behaviors. Own end-to-end integration from architecture through field deployment, coordinate across Aircraft, Autonomy Capabilities, Perception, and GCS teams, and drive mission readiness for customer releases. Mentor engineers, improve engineering practices, and serve as primary technical partner to the Aircraft team on integration approaches and interface design. Requires 7+ years of relevant experience, expert C++ and Linux development, and deep expertise in complex autonomy systems or embedded systems integration.

This intermediate-level role develops AI-enhanced decision systems for government sponsors, applying machine learning, large language models, and decision science to mission-critical problems. You will design, prototype, and evaluate AI solutions in cross-functional teams, lead R&D initiatives, and work hands-on with modern AI techniques including deep learning, reinforcement learning, generative AI, and multi-agent systems. The role requires 2+ years of hands-on ML experience (or 1 year with a Master's degree) and proficiency in Python and/or C++, with the ability to communicate complex technical concepts to both technical and non-technical audiences.

As a Mission Software Engineer, you will own software solutions deployed to autonomous systems customers, developing capabilities across networking, autonomy, systems integration, and robotics. You'll troubleshoot live deployments, create performance metrics for debugging, and collaborate with multidisciplinary teams and end-users to translate operational needs into mission-ready features. The role requires 3+ years of C++, Python, or Rust experience in Linux environments, with a strong engineering background and ability to navigate complex codebases quickly. You must be a U.S. citizen eligible for security clearance and based in or willing to relocate to San Diego.

Senior Applied AI Engineer at West Health will design, build, and deploy production-quality AI-powered tools and workflows using large language models, multi-agent architectures, and orchestration platforms. The role involves building intelligent automation pipelines with tools like n8n, LangChain/LangGraph, and Microsoft Copilot Studio, integrating AI capabilities with existing data infrastructure (Snowflake, Python), and conducting data analysis to identify high-impact AI opportunities. The ideal candidate combines deep practical expertise in applied AI with the ability to rapidly move from concept to fully working, well-documented applications that create measurable value for healthcare delivery and senior care initiatives.