Top AI Engineer Jobs

The AI Platform Engineer builds and operates an enterprise AI platform, focusing on core services for LLMs and RAG systems, automates onboarding processes, and ensures compliance and operational excellence within the platform team.

Design, develop, test, document, and deploy state-of-the-art AI/ML applications (LLMs, deep learning, CV, sensor/data fusion). Collaborate with cross-functional teams to integrate solutions into development and production, create software and test requirements, and perform rapid prototyping and proofs-of-concept while following software engineering best practices.

Lead technical direction and hands-on development of ML and AI Context systems for HubSpot CRM: model development, productionization, retrieval, embeddings, evaluation, monitoring, and cross-team architectural leadership to deliver measurable product and business impact.

Build and evolve Ridgeline's AI data platform: design secure API integrations and MCPs, implement RAG pipelines and vector database solutions, scale distributed systems, enforce data lineage/access controls, and mentor peers while shaping AI platform strategy.

Lead and execute Generative AI strategy for Global Markets Regulatory Reporting. Define engineering approach, design scalable GenAI solutions, set technology stack, oversee cross-team design and testing, integrate GenAI tools, and drive implementation for multi-tier, microservices-based platforms to deliver business outcomes.

Design, develop, test, and maintain AI-enabled enterprise software and integrations. Build AI-powered features using LLMs, prompts, and retrieval approaches; develop APIs, cloud components, CI/CD pipelines, and tests; troubleshoot, optimize, and support production systems while following secure development and Agile practices.

Build and ship internal AI enablement tools, workflows, and guardrails to help engineers use coding agents and LLMs safely and productively. Evaluate models and agents, partner with engineering teams, measure adoption and impact, and provide documentation, training, and hands-on support to increase engineering velocity and quality.

Designs, ships, evaluates, secures, and supports AI-native production systems and agentic AI tooling. Uses AI coding assistants across the SDLC, leads design and requirements, performs technical and code reviews, manages on-call and monitoring, owns change requests and enhancements, and coordinates vendor evaluations and cross-team integration.

Designs, builds, evaluates, secures, and supports production AI-native software and agentic systems. Uses AI coding assistants across the SDLC; performs model evaluation, testing, integration, production support, and stakeholder-driven requirements analysis while enforcing secure, privacy-aware practices.

Design, optimize, and deploy ML and LLM capabilities for resource-constrained heterogeneous edge platforms. Build efficient inference pipelines, RAG/semantic search, distributed inference orchestration, model optimization (quantization/pruning/distillation), monitoring, evaluation, and AI governance. Integrate models into production software, support multimodal and sensor analytics experiments, document results, and assist with customer demonstrations and prototypes.

Owns the company-wide IT and cybersecurity program, including SOC 2 compliance, cloud security, penetration-test remediation, business continuity testing, endpoint management, access controls, onboarding and offboarding, AI security governance, vendor reviews, security training, incident response, and employee IT support. The role partners with engineering, HR, Finance, leadership, auditors, and healthcare customers while managing security across AWS, Heroku, Cloudflare, Google Workspace, GitHub, and related tools.

Own and operate Baseten's internal AI stack, build and deploy custom AI agents and LLM-powered tools, evaluate third-party AI developer tools, instrument usage and measure impact on engineering productivity, and support engineering teams in adopting AI workflows.

Develop and deploy end-to-end Generative AI proof-of-concepts on Azure and AWS Bedrock. Build full-stack web applications, integrate AI models/APIs, manage CI/CD and containerized deployments, prototype rapidly, collaborate with cross-functional teams, and ensure security, compliance, and ethical AI practices.

Partner with business stakeholders and IT delivery teams to design, implement, and deploy AI-enabled production applications, integrations, and data pipelines. Focus on solution feasibility, deployment, operationalization, and driving adoption. Support benchmarking and internal development across divisions (travel up to 50%).

Design, build, and operate cloud-scale, multi-tenant services for Microsoft Edge and Copilot App management. Lead architecture, cross-team integrations, reliability, security, and production operations. Mentor engineers, drive technical direction, and use telemetry and customer feedback to improve enterprise management and AI-powered productivity experiences.

Develop, test, deploy, and maintain .NET-centric web applications using C#, Angular 17+, and Azure. Build and consume REST APIs, work with SQL Server, source control, CI/CD pipelines, and collaborate on code reviews, debugging, performance optimization, and third-party integrations.

As an AI Algorithm Developer, you'll design and implement machine learning solutions for semiconductor processing, focusing on predictive models and data analysis.

Develop and validate system-level software for neuromorphic accelerator platforms, including device-driver interfaces, OS integration, runtime APIs, simulation environments, and tooling for profiling, debugging, benchmarking, and validation. Collaborate with hardware, architecture, and application teams to enable platform features, improve performance, and ensure robust functionality for production deployments.

Design and build scalable enterprise applications in C#/.NET (APIs, microservices) and integrate AI capabilities (Python, LLMs, RAG, vector DBs, agentic frameworks). Own CI/CD, Azure DevOps workflows, containerized deployments, and collaborate across teams to deliver AI-enabled operational automation and agent integrations.

Deploy, integrate, test, and operationalize AI prototypes in cloud-native environments (primarily Databricks). Coordinate with data engineering, validate model performance, ensure CI/CD, security compliance, and operational readiness while supporting documentation and stakeholder readiness.

Design, develop, and optimize prompts for LLMs, collaborate with domain experts, integrate LLM solutions into applications, build reusable prompt frameworks, gather user feedback, and document best practices.

The role involves developing advanced AI solutions for e-commerce scenarios, designing algorithms, optimizing ML systems, and collaborating cross-functionally to drive innovations that enhance user experience.

As a Staff Software Engineer, you will significantly enhance platform development and experimentation, focusing on AI integration and efficient software workflows. You'll manage end-to-end processes, develop core infrastructure, and employ AI coding agents to refine engineering practices, ultimately improving velocity and output quality.

Lead design and implementation of Generative AI features and RAG solutions, integrate LLMs with internal systems, build APIs and workflows, mentor engineers, ensure enterprise SDLC, security, and responsible AI practices.

Define, implement, and enforce enterprise-wide engineering and operational standards for AI/ML development. Lead and mentor teams to ensure reliable, scalable, and compliant Databricks-based workflows, MLOps, CI/CD, and model lifecycle governance. Build templates, audit processes, documentation, and automated quality checks to standardize notebooks, models, and pipelines across the program.