Top AI Engineer Jobs

Design, build, and deploy autonomous AI agents using LLMs and agent frameworks; integrate agents into e-commerce and supply chain systems; implement multi-agent orchestration, memory and tool integrations; fine-tune models and apply RL concepts; and build safety, monitoring, and MLOps pipelines.

Design, build, and maintain scalable AI/ML systems and ETL pipelines for cloud operations. Develop AI agents, predictive models (drift and cost anomaly detection), and automations; integrate ML insights with AWS/GCP/Azure; optimize data storage (Snowflake) and querying (Athena); orchestrate workflows with Airflow; conduct code reviews, mentor teammates, and evaluate emerging AI technologies for operational improvements.

As a Founding AI Design Engineer, you will design visual assets and collaborate with engineers to create a platform that integrates AI with design workflows in pharma marketing.

Lead the technical vision and roadmap for the company's AI platform: design model-serving, feature stores, experiment tracking, CI/CD for ML, optimize GPU/compute, improve observability, ensure reliability, and mentor senior engineers to enable scalable, safe LLM inference in production.

Design and build data infrastructure and AI/ML systems—extracting, cleaning, moving, and storing data; develop, deploy, and monitor ML and LLM-based products; build APIs; collaborate with stakeholders and manage projects to meet business needs.

Design and implement robust bimanual manipulation algorithms and train learning-based robot policies (diffusion, imitation, RL). Build end-to-end autonomy connecting perception, semantic task understanding, and low-level control. Ship production-quality Python and C++ code, profile and scale the autonomy stack, and work with high-fidelity simulators for sim-to-real transfer.

Architect and implement robust bimanual manipulation algorithms and learning-based robot policies (diffusion, imitation, RL). Build end-to-end autonomy connecting perception to low-level control, write and maintain production Python/C++ code, and scale performance across a fleet in industrial environments.

Design and implement robust bimanual manipulation algorithms and learning-based robot policies. Build end-to-end autonomy connecting perception, task understanding, and low-level control. Ship production-grade Python and C++ code, optimize system performance, and scale deployments across an industrial robot fleet.

Design and build production-ready AI agents and infrastructure for hardware engineering workflows. Implement context management, indexing, and post-training; interpret and manipulate complex engineering design data; integrate with enterprise tools; collaborate with customers; prototype and ship solutions; influence architecture and engineering culture.

Design, build, and deploy AI-enabled production software for clients. Participate in client meetings, live prototyping, demos, requirements gathering, and own end-to-end product outcomes. Use AI development tools to accelerate engineering while validating and correcting generated code. Ship customer-facing projects, maintain integrations, hosting, and domain configurations, and collaborate in a hybrid team environment.

Build end-to-end AI integrations in a cybersecurity platform: gather contextual security data, call and optimize AI services, map responses to actionable UI (React), implement error/fallback handling, monitoring, caching, and user feedback loops while working directly with customers.

Own reliability, performance, and evolution of workplace technology across Microsoft 365, identity, and endpoints. Lead incident response, problem management, automation, and ITSM; design secure scalable services; drive strategy and Copilot/GenAI adoption; mentor engineers and influence cross-functional stakeholders to improve reliability and operational excellence.

As a System Software Engineer, you will design communication primitives for AI models, optimize performance for training workloads, and benchmark performance on clusters.

Design, build, and maintain FedRAMP-compliant platform services for cloud traffic, ingress/egress, identity, and cryptographic controls. Lead migrations, implement IAM (Okta, SAML/OIDC, RBAC), enforce FIPS-validated cryptography, harden Kubernetes and secrets management, automate compliance (NIST SP 800-53, ConMon), and mentor engineers while partnering with security teams for assessment readiness.

Design, build, and productionize LLM-based conversational and AI systems for enterprise coaching. Integrate structured and unstructured data, prototype end-to-end services, improve model behavior and observability, and collaborate with product and engineering to deploy scalable, reliable AI-driven coaching workflows.

Build and maintain production AI-driven systems including call-scoring pipelines, multi-tenant Next.js/Supabase dashboards, a Velocify-replacement lead platform, AI voice agent integrations, Salesforce administration, and internal automation workflows. Ensure CI/CD, testing, security, and reliable real-time integrations for client-facing and internal compliance products.

Lead design and scaling of production AI agent systems for Bee, architect Python services and agent workflows (PydanticAI, GCP), define prompt/response schemas and fallbacks, build evaluation/experimentation and observability, and partner across Product, Design, and Data to deliver responsible AI-driven product features.

Owner of the marketing intelligence stack: build warehouse-backed data models, integrate intelligence and CRM tooling, ship CEO-facing GTM dashboards, and design agentic LLM workflows (on Claude) for briefs, content, and account monitoring while ensuring compliance and observability.

Design, develop, and deploy generative AI models and AI-driven automation workflows. Integrate models via APIs, build inference pipelines, preprocess and manage training data, ensure data privacy, monitor and optimize model performance, collaborate with cross-functional teams, and document solutions.

The Software Engineer will develop ML models, software for embedded systems, and user interfaces, ensuring effective hardware integration and performance.

Build, configure, validate, and maintain AI/ML infrastructure and runtimes for internal developers. Support deployments, integrations, lightweight model fine-tuning, automation harnesses, and CI/CD/DevOps tooling while collaborating with stakeholders to prioritize work and educate users.

Design, develop, and operationalize ML and computer vision models for imagery analysis, focusing on detection of AI-generated or manipulated images. Preprocess and validate large datasets, evaluate and optimize model performance, containerize deployments, translate research into production workflows, and collaborate in secure, classified environments.

Design and implement graph-based search services and scalable backend systems using Java and Spring Boot. Build GraphQL/REST APIs, integrate with AWS services and databases, ensure observability with New Relic and Coralogix, mentor engineers, and collaborate on search and recommendation features to deliver reliable, cloud-native solutions.

The role involves building and improving AI voice features, debugging issues, and collaborating with product teams to enhance user experience.

Build end-to-end AI-powered product features: design agentic pipelines, RAG and LLM orchestration, backend services, and user-facing React UIs. Implement eval/observability systems, mitigate hallucinations, optimize production latency/cost, and work closely with founders, legal users, and product to ship and iterate customer-focused AI experiences.