Go AI Jobs

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Design and deliver production-grade AI agents that are highly performant, reliable, and intuitive, driving revenue directly to Sierra's growth. Take complete ownership of the Agent Development Life Cycle (ADLC) from initial pilot through deployment and continuous iteration, including building, tuning, and evolving AI agents in production environments while defining best practices. Partner directly with leaders of large enterprises and cutting-edge startups to understand business challenges and build AI agents that transform operations at scale. Work with customers to guide the evolution of Sierra's core platform by surfacing unmet needs, prototyping new tools and features, and collaborating with research, product, and platform teams to shape the future of AI agent development and Sierra's product.

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Design and deliver production-grade AI agents that are highly performant, reliable, and intuitive, running in production environments across industries like finance, healthcare, and commerce. Drive the Agent Development Life Cycle (ADLC) with complete ownership and autonomy from pilot through deployment and continuous iteration, building, tuning, and evolving AI agents in production and defining ADLC best practices. Partner with large enterprises and startups to understand business challenges and build AI agents that transform operations at scale. Build the future of Sierra's platform by surfacing unmet needs, prototyping new tools and features, and collaborating with research, product, and platform teams to shape AI agent development and product evolution.

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The Staff Software Engineer is responsible for architecting, designing, and developing the intelligence layer that controls GPU node assignment, monetization, and management within Crusoe's fleet. They will be among the first engineers on the Virtual Pool Service and Capacity Management Intelligence systems, shaping implementation and making key design decisions, building foundational cloud platform infrastructure. Responsibilities include building the Virtual Pool Service as the source of truth for GPU node states and history, designing the Capacity Management Intelligence automation layer to handle allocation and automated node lifecycle transitions, collaborating cross-functionally to architect and implement physical infrastructure management systems, championing system reliability, scalability, and security, streamlining cloud deployment and operations using technologies such as Go, gRPC, NATS event streaming, PostgreSQL on Kubernetes, and Netbox, and mentoring engineers while contributing to team growth in collaboration with engineering management.

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Debug and fix issues in the Arize platform and ship pull requests with fixes. Build internal tools and copilots powered by generative AI to enhance the team's productivity. Rapidly prototype proof-of-concepts for customer use cases. Collaborate across Engineering, Product, and Solutions teams to unblock customers and advance AI adoption.

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Debug and fix issues in the platform and ship pull requests with fixes. Build internal tools and copilots powered by generative AI to enhance the team. Rapidly prototype proof-of-concept solutions for customer use cases. Collaborate across Engineering, Product, and Solutions teams to unblock customers and push the boundaries of AI adoption.

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Design and build extensible backend systems supporting flexible configurations for different customers and content types. Develop infrastructure interfacing with LLMs to enable prompt engineering, context injection, and modular evaluation workflows. Build tooling and platforms for fast iteration by AI engineers and analysts, including declarative pipelines, parameterized jobs, and reproducible experiments. Prioritize ease of deployment, integration, and testing for internal teams and external partners. Collaborate closely with product, data, and policy teams to translate nuanced safety needs into scalable, maintainable software systems.

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Design and deliver production-grade AI agents that are highly performant, reliable, and intuitive, running in production environments across industries like finance, healthcare, and commerce. Own and drive the entire Agent Development Life Cycle (ADLC) from initial pilot through deployment and continuous iteration, building, tuning, and evolving AI agents in production environments and defining best practices for ADLC. Partner directly with leaders at large enterprises and cutting-edge startups to understand their business challenges and build AI agents that transform their operations at scale. Collaborate with customers to guide the evolution of Sierra's core platform by surfacing unmet needs, prototyping new tools and features, and working with research, product, and platform teams to shape the future of AI agent development and Sierra's product.

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As a Staff Software Engineer in the Foundations department, responsibilities include leading the design and implementation of highly scalable systems for the Managed AI offerings, driving the long-term technical roadmap for the Foundations team to support growth and evolving AI workloads, working cross-functionally with Cloud Engineering to align technical goals and solve integration challenges, leading by example through high-quality code contributions and mentoring Senior and Staff-level engineers, championing reliability, observability, and performance by identifying and resolving systemic bottlenecks, and staying current with AI infrastructure trends to ensure efficient and powerful tools are utilized.

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The AI Engineer will design and develop intelligent agents powered by large language models (LLMs) using tool calling, orchestration frameworks, and advanced context management to enable reasoning, planning, and autonomous decision-making across complex workflows. Responsibilities include working hands-on with modern agentic stacks such as LangGraph and Autogen, implementing asynchronous and streaming architectures, and ensuring production-grade observability to build scalable real-world AI systems.

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Lead and scale Horizon3.ai's Offensive Engineering organization, overseeing teams responsible for exploit development, offensive content, and attack automation within the NodeZero platform. Set clear technical and product direction for how NodeZero identifies, exploits, and validates vulnerabilities across large, complex environments. Partner with Product, Precision Defense, and Platform teams to define and deliver offensive capabilities that influence the roadmap and enhance customer outcomes. Drive execution from proof-of-concept through production to transform cutting-edge attack research into scalable, productized features. Stay hands-on to guide architectural decisions and evaluate exploit and automation approaches, mentoring technical leads in building resilient, modular systems. Build, mentor, and scale diverse teams of software engineers, exploit developers, and offensive researchers, fostering a culture of collaboration, creativity, and engineering excellence that bridges offensive and product software development. Collaborate across engineering, product, and GTM teams to align offensive innovation with business priorities and ensure delivery of impactful capabilities for customers. This role is central to the mission of delivering continuous, autonomous security testing at scale.