Top Tech Jobs & Startup Jobs

Own quality for AI agent systems by building test frameworks, evaluation harnesses, regression suites, simulators, CI/CD quality gates, and API, integration, performance, and reliability tests. Conduct exploratory, manual, red-team, and release testing; evaluate agent traces, safety, reasoning, and task completion; manage labeled datasets and quality metrics; investigate failures; define release criteria; and mentor engineers on testing probabilistic systems.

Own quality for AI agent systems through automated test frameworks, evaluation harnesses, regression suites, CI/CD quality gates, simulators, and API, integration, performance, and reliability testing. Perform exploratory testing, trace review, manual red-teaming, release verification, and UAT support. Build datasets, metrics, rubrics, dashboards, and release criteria while investigating failures and mentoring engineers on testing probabilistic LLM systems.

Manage technical project execution across Applied AI and Core Engineering teams. Own project decomposition, estimation, timelines, dependencies, risk tracking, and status reporting. Coordinate engineering, DevOps, testing, and client delivery teams; identify blockers and support technical triage across AI agents, infrastructure automation, workflow orchestration, CI/CD, and platform architecture. Drive prioritization, communication, iterative delivery, and execution against shared business goals.

Own product design across Nexxa’s AI platform, creating polished UX/UI for complex industrial workflows, dashboards, command centers, AI agents, recommendations, approvals, and automation. Develop interaction patterns, prototypes, motion, transitions, and responsive experiences while simplifying dense information. Collaborate with product, engineering, AI, and leadership, contribute to the design system, and take concepts through production. Strong visual taste, systems thinking, UX expertise, and comfort with ambiguity are essential.

Own and evolve cloud, on-premises, and edge infrastructure supporting AI, data, and product workloads. Design Kubernetes platforms with GPU scheduling, CI/CD pipelines, infrastructure-as-code, observability, security, and reliability practices. Lead infrastructure projects, incident response, roadmap strategy, and platform development while balancing cost, latency, resilience, and developer velocity. Mentor engineers and support machine learning training, inference, data pipelines, and industrial system integrations.

Own and evolve cloud, on-premises, and edge infrastructure supporting AI, data, and product workloads. Design Kubernetes platforms, GPU scheduling, CI/CD pipelines, infrastructure-as-code, observability, security, and reliability practices. Lead infrastructure projects, incident response, platform strategy, and developer enablement while balancing cost, latency, reliability, and velocity. Mentor engineers and provide technical direction for scalable, production-grade ML and industrial systems.

Own Nexxa’s SOC 2 and ISO 27001 compliance programs while securing multi-account AWS and GCP environments. Responsibilities include cloud and infrastructure remediation, IAM administration, identity lifecycle management, endpoint and SaaS operations, auditor and customer reviews, CI/CD and software supply-chain hardening, production troubleshooting, and security documentation. The role builds automated controls, manages findings, supports internal IT, and establishes scalable security and AI governance processes.

Design, train, evaluate, and deploy production computer vision and vision-language systems for industrial applications. Build pipelines for detection, segmentation, OCR, tracking, multimodal reasoning, and real-time edge or cloud inference. Develop data and evaluation workflows, fine-tune foundation models, and optimize deployments through quantization, pruning, and hardware acceleration. Collaborate across AI, engineering, research, and product teams to deliver scalable, robust visual AI solutions.

Own SOC 2 Type 2 and ISO 27001 compliance programs while securing AWS, GCP, SaaS, infrastructure, identity, CI/CD, and software supply chains. Triage and remediate security findings, administer access and endpoints, support IT operations, manage auditors and customer reviews, debug cloud production issues, and build automated security guardrails, documentation, and postmortems.

Design and operate production backend services and AI infrastructure, including model-serving pipelines, inference services, data pipelines, RAG systems, vector stores, APIs, and microservices. Build scalable real-time and batch systems, integrate LLM, computer vision, and machine learning models, and manage deployment, observability, reliability, and performance. Collaborate with ML, product, and field engineering teams, document architectures, and mentor engineers.