Top AI Engineer Jobs

Design, build, and ship production AI agents and ML systems for retail merchandising, document understanding, retrieval/ranking, and evaluation. Own full model lifecycle from research to production, build evaluation/observability, and collaborate with engineers, PMs, and store owners to drive measurable merchant impact.

Lead technical architecture and delivery of end-to-end AI solutions across the Workday ecosystem. Design data flows, integrations, security and RAG/LLM patterns; advise executive stakeholders; lead technical workstreams; collaborate with Product and Engineering; ensure privacy, ethical AI, and scalable deployments for complex global customers.

Lead developer advocacy for AI and agentic security: advise security companies, accelerate NVIDIA stack adoption, guide partner integrations, map ecosystems, collaborate cross-functionally, run community events, and feed product teams with field insights.

Design, develop, and deploy autonomous AI agents and ML models to automate cybersecurity use cases (incident investigation, vulnerability prioritization). Integrate LLMs, build data pipelines with vector databases, implement MLOps and cloud AI deployments, enforce safety/compliance guardrails, and optimize workflows for automated remediation.

Lead the security architecture and implementation for an enterprise AI platform: secure cloud infrastructure, data protection, IAM, tenant isolation, and GenAI workflows. Embed security into CI/CD, IaC, containers, secrets management, and operations. Design secure customer deployment patterns, support enterprise security reviews, and partner on compliance (SOC 2, ISO 27001, SSPA) while personally implementing critical security capabilities and guiding cross-functional engineering teams.

Design, build, and maintain scalable enterprise full-stack applications using Java, Spring Boot, microservices, and modern front-end frameworks. Implement cloud-based solutions on AWS, contribute to CI/CD and DevOps automation, optimize performance and security, and integrate AI-driven capabilities using Python and orchestration tools like LangChain and LangGraph.

Build and deploy machine-learning prototypes and tools for AI security; analyze large cybersecurity datasets; support AI red teaming and adversarial ML; collaborate with researchers to translate research into operational capabilities.

Design and implement ML-based prototypes, tools, and systems for AI security. Collaborate with researchers to execute experiments, analyze large cybersecurity datasets, support adversarial ML and red teaming, and translate research into deployable, maintainable software solutions.

You will build agentic AI products across web, backend, and iOS, owning features end-to-end and mentoring junior teammates.

Define, document, and validate low-level technical requirements for AI-enabled enterprise software. Work with customers, systems engineers, and developers to translate requirements into Jira stories, participate in Agile delivery, perform functional testing, and recommend AI approaches for integration and deployment on cloud-based microservices (AWS).

Design and ship features enforcing enterprise security policies for MCP access and usage. Improve deterministic and LLM-based risk policies. Deepen integrations with identity providers and strengthen the platforms security posture. Collaborate across product and engineering, participate in on-call rotation, and own features from design through production and support.

Design, build, and ship production AI systems and platform infrastructure across distributed compute, data pipelines, backends, frontends, and observability. Develop and improve multi-agent systems, inference infrastructure, benchmarks, verification pipelines, and feedback loops to improve agent quality, cost, latency, and robustness for drug-discovery workflows.

Designs, deploys, and optimizes AI-driven security workflows and agents (using Microsoft Copilot tools) to automate threat detection, incident response, and alert enrichment. Develops prompts and automations for threat hunting, triage, compliance reporting, creates dashboards (Splunk, Sentinel), maintains runbooks/SOPs, participates in on-call rotations, and collaborates with SOC, engineering, and GRC teams.

Build and improve production AI systems that extract structured data from legal documents into a household knowledge graph. Own and design evaluation suites, improve agent orchestration and tooling, create human-review workflows, and ship dependable, scalable changes to production while collaborating with domain experts and product.

Lead design, development, integration, and deployment of end-to-end AI/ML solutions for clinical settings. Collaborate with multidisciplinary teams, build CI/CD and MLOps pipelines, ensure regulatory-quality engineering, mentor junior engineers, define evaluation metrics, and translate technical results into actionable guidance for clinicians and stakeholders.

Lead design and rewrite of cloud-native core systems. Build scalable back-end services and front-end features, drive architecture and testing discussions, mentor engineers, and improve telemetry, performance, and reliability.

Build, operate, and scale cloud-native backend services and APIs for a high-volume vehicle marketplace. Embed AI-driven capabilities into features, use AI tools to accelerate development, participate in on-call rotations, improve reliability, and collaborate with Product, Data, Infrastructure, and SRE teams to deliver production-ready systems.

Lead enterprise strategy and engineering to defend against AI-powered threats. Design detection, prevention, and response architecture for adversarial AI, integrate controls into cyber tooling, build threat models, prototype defensive AI, and mentor teams while influencing leadership and vendor selection.

Lead the security design, architecture, and implementation for an enterprise AI platform. Define secure deployment patterns, embed security into CI/CD and operations, secure GenAI workflows, and lead customer security reviews and compliance activities for Fortune 1000 deployments.

Design, build, and deploy AI/ML capabilities (LLMs, RAG, embeddings, vector search) into secure cloud environments to accelerate cyber analyst workflows. Integrate models with APIs, monitor performance and drift, support retraining, perform experiments/AoAs, and provide stakeholder training and operational guidance in government settings.

Build and ship security features for an AI control plane: enforce enterprise policies, improve risk policy systems (deterministic and LLM-judged), integrate identity providers, and harden platform security. Collaborate across product and engineering, participate in on-call rotations, and own features from design through production and support.

Designs and implements secure, fully automated CI/CD pipelines and identity controls for cloud deployments. Builds infrastructure-as-code (Ansible, Terraform, Packer), integrates identity and auth (AWS IAM, Azure/Entra ID, SailPoint, OAuth/OIDC/SAML/SCIM), and automates guardrails for non-human identities and agent workloads. Partners with architecture, InfoSec, and engineering to ensure compliance, observability, and scalable, secure deployments.

Design, build, and operate secure cloud CI/CD pipelines and automation (infrastructure as code) to support cloud deployments. Partner with InfoSec, architecture, and engineering to enforce identity and non-human identity governance, implement IAM integrations, secrets management, and automated guardrails. Troubleshoot production pipeline issues, develop tools to reduce errors, and research technologies to improve DevSecOps effectiveness.

Research and develop machine learning algorithms and software prototypes for sponsor problems. Perform data collection, modeling, fusion, visualization, statistical analysis, and present technical reports. Collaborate with staff, supervise junior personnel and students, and integrate ML prototypes into research and pre-production environments.

As a Product Engineer, you'll implement AI features, collaborate with teams, prototype workflows, and improve developer processes at Vori.