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Lead the design and delivery of AI/ML systems, owning architecture decisions and driving solutions from research through production at scale.
Lead end-to-end delivery of enterprise-grade AI agents, defining behavior, running evals, and shipping production solutions in 30–45 days using AWS AI services and modern agentic frameworks.
Lead end-to-end AI product delivery for enterprise GenAI and agentic AI engagements, defining agent behavior, running evals, and shipping production-grade solutions in 30–45 days.
Lead end-to-end architecture for cloud, data, and AI systems, designing scalable, secure solutions and mentoring teams to ship production-ready AI in 30–45 days.
Lead platform engineering for multi-environment cloud systems, defining DevSecOps standards and Kubernetes infrastructure to deploy and scale AI/ML workloads rapidly.
Lead end-to-end UX/UI design for AI-powered enterprise products, owning design systems, research strategy, and mentoring teams to ship human-centered AI workflows.
Lead the design of cloud, data, and AI systems for enterprise clients, setting technical direction and mentoring teams to ship production-ready AI in 30–45 days.
Deploys and maintains GenAI agents in client cloud environments (Azure/AWS), focusing on containerized model-serving APIs, CI/CD pipelines, and observability. Works cross-functionally with data scientists to ship production-grade AI systems for enterprise clients.
Hands-on technical lead who designs, builds, and scales production-grade AI systems: defining architecture, leading ML/LLMOps implementation (RAG, agentic orchestration, inference pipelines, AWS), and mentoring engineers. Requires 5+ years in AI/ML engineering with strong Python and distributed systems experience.
Design and deliver cloud, data, and AI/ML systems as a Senior Cloud Architect, building microservices, serverless and containerized workloads, implementing IaC and CI/CD pipelines, and shaping data and model deployment architectures using Python and modern AI tools.
You will adversarially red-team Generative AI models for cyber-CBRNE risks: designing jailbreaks, multi-turn attack scenarios, and evaluations that test whether LLMs can be manipulated into enabling high-consequence attacks on critical infrastructure, ICS/OT systems, and labs. Requires deep cybersecurity, red-team, and CBRNE domain expertise.
Forward-deployed AI & data engineer at Global M who builds production solutions for real customer problems while helping shape the core product — splitting time roughly 40% with customers and 40% building. Core technologies are Python, SQL, data engineering, and production systems experience.
A Technical Program Manager at Cohere oversees AI delivery projects, bridging customer needs with engineering teams to deploy enterprise AI solutions. Core focus: LLM-based product development, cross-functional alignment, and ensuring timely, high-quality delivery for strategic clients.
Staff DevOps Developer builds and maintains the cloud infrastructure, AI integration layer, and RAG retrieval services that power Visier's Workforce Intelligence platform, using Python, Terraform, AWS/Azure, and MCP servers.
Lead cross-functional programs to scale Cohere’s AI model infrastructure, coordinating inference, serving, and endpoints while improving engineering best practices and incident response.
Design and optimize enterprise cloud apps using C#/.NET and Azure, lead DevOps/IaC, and integrate AI tools like GitHub Copilot to boost development efficiency.
Technical Program Manager bridging Cohere’s AI models with Canadian public sector and defence clients, managing complex deployments with strict security/compliance needs.
Designs and automates end-to-end manufacturing tests for integrated AI compute racks, validating power, cooling, networking, and firmware at scale.
C3 AI is hiring a Federal Security Engineer in Tysons, VA to own per-release security-gate evidence, Continuous Monitoring (ConMon) automation, and the FedRAMP/ATO engineering interface for federal deployments. Day-to-day work spans SCAP/STIG scanning, CVE/vulnerability triage, FIPS/SBOM evidence, and hardened container registries using Linux, Python, Shell, and JavaScript.
Design and maintain Gusto’s AI-native design system, Workbench, by creating coded components, token architecture, and LLM-readable documentation while collaborating with engineers to integrate AI tooling.
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