Top AI Engineer Jobs

Seeking a Principal Software Engineer to build developer products for LLM applications, ensuring high-quality tools and APIs while leading engineering practices and collaborating across teams.

The Staff Engineer in Applied AI is responsible for designing, building, and deploying production-ready AI systems, collaborating with teams to enhance customer experiences and automating workflows.

Build infrastructure for AI applications, improve efficiency of distributed AI workloads, and collaborate with cross-functional teams at Databricks.

Develop and deploy full-stack applications using modern technologies, optimize for performance, mentor engineers, and leverage AI tools.

As a Senior QA Engineer, you'll develop and automate test cases, leverage AI for enhanced QA processes, and collaborate cross-functionally to ensure quality standards in product development.

The Principal Solution Engineer will provide AI/ML technical guidance, collaborate on data architecture, engage with customers, and support sales cycles for Snowflake's Cloud Data Platform.

Build and scale responsive, data-heavy frontend dashboards and human-in-the-loop interfaces using TypeScript/React. Own product lifecycle from discovery to production, ensure system reliability, collaborate on AI feature integration, and mentor teammates while working closely with founders in San Francisco.

Design and build AI-driven, agentic automation for cloud infrastructure, CI/CD, incident response, cost optimization, security/compliance, and observability across AWS/GCP/Azure. Modernize legacy systems, leverage LLM-powered assistants for IaC and Kubernetes, and create self-service platforms with automated remediation and human oversight.

Lead design and development of Snowflake's Internal Marketplace and Data Collaboration systems. Build secure, highly available distributed platforms, manage data product lifecycle (curation, discovery, governance, policy, publishing, observability), and ensure operational readiness, reliability, and performance.

Build and maintain the hybrid-cloud AI platform and internal developer platform: containerize research code, define IaC specs, deploy workflow orchestration, manage vector/graph databases, deploy model serving and cloud AI agents, and collaborate with IT on Kubernetes-based compute and security integrations.

Design and implement workflows using large language models to automate processes, lead integration efforts, and evaluate new technologies.

Design, develop, and deploy generative AI and integration solutions for Visa's VAS platform. Build APIs, implement NLP and ML components, modernize platform technology, automate CI/CD, ensure security and reliability, and collaborate with cross-functional teams to deliver scalable, client-focused services.

Partner with prospects to assess needs, perform technical discovery, deliver tailored demos and lead POCs/RFIs. Provide strategic AI-powered knowledge solutions, address technical/security questions, and build trusted stakeholder relationships while supporting sales.

Design and build scalable AI/ML-powered full‑stack applications, operationalize models in production, create conversational AI, drive network automation and telemetry-driven insights, and implement CI/CD and containerized deployments.

Build production-ready AI solutions by writing Python code, tuning LLMs and prompts, implementing data pipelines and ETL, integrating APIs, and working directly with clients to ensure successful deployments.

Build and deploy LLM-based chatbots and machine learning models, integrate agents with enterprise databases and APIs, perform data preprocessing and model evaluation, automate data pipelines, and collaborate with internal teams and clients.

Develop and deploy AI-powered solutions, collaborating with data scientists and engineers on data pipelines, APIs, and models. Stay current with AI advancements.

Lead the development of AI solutions and data engineering strategies. Implement AI data pipelines, collaborate with teams, and ensure the reliability of data systems.

The AI and ML Engineer will develop and maintain AI/ML models, collaborate with teams to deliver solutions for national security, and apply algorithms.

As a Senior Verification Engineer, you'll perform functional verification of AI SoCs, develop verification plans, and collaborate across teams to debug and ensure product correctness.

The Senior Verification Engineer will lead functional verification of ASIC designs, develop verification plans, and collaborate with design teams to ensure quality AI SoC products.

Lead a development team in Python and AI technologies at Allstate, focusing on architecture, Agile practices, and team mentorship.

Lead design and scalability of Java-based backend services for a multi-tenant platform. Architect high-throughput, low-latency systems, integrate core data stores, modernize legacy Java components, improve observability and CI/CD, and mentor engineers while driving platform strategy and reliability.

Work with sales and partners to demonstrate Snowflake, run proofs-of-concept, design solutions, and close large enterprise deals. Present to technical and executive audiences, collaborate with product and engineering, and maintain deep competitive and industry knowledge.

Design and implement an end-to-end ML compiler targeting a novel AI accelerator. Collaborate with hardware architects to co-design ISA-driven optimizations, build MLIR/LLVM-based lowering and backend codegen, develop profiling and analysis tools, and map high-level model graphs (ONNX/JAX/PyTorch) to hardware-efficient kernels and schedules.