Lead the design and implementation of production-grade AI agent systems, including backend services, orchestration, retrieval, evaluation, observability, and deployment.
Own the technical design and implementation of AI agent systems
Build robust backend services, APIs, adapters, and connectors
Design agent workflows involving tool use, routing, state management, memory, retrieval, human-in-the-loop steps, and controlled multi-step execution
Develop retrieval and knowledge-grounding capabilities, including RAG pipelines, SQL-based agents, web search, reranking, citation, and context management
Define and implement evaluation strategies using representative datasets, golden tests, failure taxonomies, regression testing, human review, and production feedback
Requirements
Master’s degree in Computer Science, Software Engineering, or a related technical field
Own major components of a core execution system, covering its reliability, speed, resource use and measured results. The role suits an experienced software engineer with strong computer science fundamentals who wants to move into advanced automation work and collaborate closely with technical leadership.
Compensation
Salary: $180K - $330K
Responsibilities
Build core execution components such as tool invocation, state tracking across long sequences, failure recovery and context handling.
Improve latency and resource use, tracking cost per completed task and helping keep token usage within budgets.
Write robust, concurrent production code that interacts with desktop applications on restricted corporate machines.
Design reproducible, adversarial test suites based on real user scenarios rather than synthetic tasks.
Translate validated user scenarios into test cases and expand how many common steps the system completes end to end.
Requirements
highly ranked computer science program
Nice to have: desktop automation
Nice to have: programmatically controlling applications
Nice to have: hyper-growth startups
Nice to have: enterprise deployment constraints on locked-down corporate workstations
Lead the engineering function of a growing technology company, setting technical direction and architecture across the core platform and its supporting systems.
Compensation
Base salary: $350,000 to $500,000
Responsibilities
Set technical direction and architecture across the platform's core systems.
Recruit, hire and develop an engineering team as the organization grows.
Define engineering standards covering fundamentals, code quality, reliability and modern AI-assisted development.
Partner with executive and product leaders on roadmap choices and complex technical and scaling problems.
Stay close to the code to set the technical bar and guide implementation.
Computer Vision C++ Engineer to support the development of real-time perception capabilities for Shield AI's autonomous systems.
Compensation
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check.
Responsibilities
Design, develop, and integrate advanced computer vision algorithms into high-performance C++ software pipelines
Build custom perception capabilities from the ground up with emphasis on real-time performance, reliability, and deployment in edge compute environments
Support development of geometry-based computer vision pipelines including camera modelling, calibration, and spatial alignment
Requirements
Bachelor's degree in Computer Vision, Computer Science, Engineering, or related technical field
Nice to have: Master’s or PhD in Computer Science, Engineering, or related field
As an AI Engineer, you build customer-facing platform capabilities and AI-powered solutions that solve real business problems, working directly with Product Management, Customer Success, and enterprise customers.
Building customer-facing capabilities across our Enterprise Agent Platform, including agent orchestration, workflow execution, enterprise integrations, knowledge management, and administration.
Developing production-ready AI workflows and reusable platform services that power enterprise solutions across multiple industries.
Designing trusted AI capabilities including evaluation, verification, observability, provenance, and human-in-the-loop workflows.
Building intuitive developer and user experiences that simplify how enterprise customers create, configure, and operate AI agents.
Working directly with enterprise customers to understand their business problems, rapidly prototype solutions, and turn successful implementations into reusable platform capabilities.
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