Top AI Engineer Jobs

Partner with client firms to discover and automate high-value workflows using Intapp Celeste. Map workflows to agents, playbooks, and semantic layers; codify firm methods; drive adoption through training and onboarding; enable scalable expansion and inform product strategy with real-world experience.

Design, build, test, and deploy enterprise .NET web applications; integrate generative AI features using AWS Bedrock and Anthropic Claude; use AI-assisted coding tools; maintain CI/CD pipelines in Azure DevOps/TFS; optimize backend/data access and collaborate with architects, PMs, and analysts on solution delivery.

Build and scale full-stack features for the Insights practice management platform using ReactJS, Python, and PostgreSQL. Improve reliability, observability, performance, and availability; collaborate with infra, backend, product, and design; own multi-month projects, conduct code reviews, and drive architectural improvements to support thousands of practices.

Lead architecture and development of large-scale agentic systems integrating LLMs into production applications. Define LLM integration strategy, drive cognitive automation roadmap, establish org-wide engineering standards for scalable, observable distributed ML systems, and provide technical leadership across teams and executives.

Develop and prototype AI/ML-driven automation for ASIC/SoC design and implementation, collaborating with academia and cross-functional teams to apply GenAI, RL, GNNs and CNNs to VLSI CAD flows, pilot solutions on real designs, and improve power, performance, area, and quality.

The role involves engaging with AI-native companies to optimize their AI platforms using NVIDIA technologies, focusing on architecture, model performance, and collaboration with technical teams.

Build and maintain scalable ML and generative AI platforms and backend infrastructure; deploy and manage production applications; create services exposing ML/AI products; implement RAG solutions and vector databases; integrate LLM orchestration and foundation model APIs; collaborate cross-functionally and mentor teammates.

Lead and deliver Java-based microservices and LLM/AI agent solutions, architect for reliability and security, define operational KPIs/SLIs, optimize CI/CD and SRE practices, mentor and manage a small engineering team, and ensure test-driven, observable, and secure production systems.

Build and productionize state-of-the-art computer vision and multimodal AI systems for messy construction blueprints. Rapidly prototype, iterate from user feedback, and own intelligence-layer development for cost estimation and permit automation.

As a Senior AI Engineer, you will build and scale the AI Agent platform, handling customer interactions across multiple channels, while collaborating with cross-functional teams to deliver effective solutions.

Embed with clients to gather requirements and design AI-driven solutions for fraud and fincrime. Architect, train, evaluate, and deploy custom AI agents and workflows, optimize model performance, establish risk metrics and evaluation pipelines, and collaborate with engineering/product teams to scale into production.

The AI Developer designs and develops software solutions for business functions, collaborates with teams to meet business needs, and maintains applications.

As an AI Engineer, you'll develop and optimize LLMs, collaborating closely with cross-functional teams to enhance detection engineering capabilities and drive new AI initiatives.

In this role, you will design and implement advanced agentic systems for web experiences, optimize AI integration, and lead architectural decisions to shape Flint's technical vision.

Design and build AI agent workflows, focusing on orchestration, reliability, and product metrics. Collaborate with product/design to innovate and improve LLM-powered features.

Design, build, and deploy agentic, customer-facing AI products using AWS-native services. Architect multi-agent systems with tool use, memory, and orchestration. Own full AI feature lifecycle from prompt engineering through deployment and monitoring. Collaborate cross-functionally to ensure accuracy and regulatory compliance, write high-quality code, and instrument production observability.

Design, build, and deploy agentic, customer-facing AI products on AWS. Architect multi-agent systems with tool use, memory, and orchestration. Own full AI feature lifecycle from prompt engineering to monitoring, collaborate cross-functionally, and ensure accuracy and compliance in production.

As an AI Engineer, you will develop and optimize AI systems, focusing on LLM integration, vector databases, and RAG pipelines, collaborating with various teams to ensure cutting-edge performance.

The AI Enablement Engineer leads programs for engineering teams to integrate AI, teaches best practices, and develops scalable learning models.

As an Applied AI Engineer, you'll develop AI-first software for enterprise clients, contributing to a rapidly growing startup with a strong engineering team.

The research engineer will build and enhance Sapien's AI systems for finance, focusing on agent architecture, data parsing, and performance benchmarking, while developing new intelligent solutions for complex financial workflows.

The AI Engineer will develop, evaluate, and improve LLM-powered features from prototypes to production, ensuring quality and effectiveness for user deployment.

Drive business growth by serving as a trusted advisor to enterprise brands, providing technical guidance and strategic insights for AI-driven marketing solutions.

Build and evolve AI systems to enhance investment insights, integrating models and optimizing outputs for professional investors in a fast-paced environment.

Develop robust AI/ML solutions for manufacturing, collaborating with scientists to build scalable infrastructure, optimizing ML systems, and ensuring code quality.