Top AI Engineer Jobs

The AI Compiler Engineer will innovate in AI performance, optimize compiler processes, and collaborate on hardware/software co-design, advancing AI technologies for datacenter applications.

Leads technical developer relations and strategic software-account engagement for NVIDIA integrations across observability, security, and AI platforms. Builds demos, sample code, guides, APIs, SDK integrations, and technical enablement programs; advises developers and partners; drives adoption and co-innovation; delivers talks and workshops; coordinates with engineering, product, sales, legal, and marketing; and translates ecosystem trends and developer feedback into product and platform strategy.

Build integrations that discover, identify, and govern AI agents across third-party platforms such as Salesforce Agentforce, Microsoft, AWS, and Google Cloud. Retrieve native identity signals, integrate them with Delinea’s identity layer, and govern agents through provider APIs and attestation. Improve shared discovery capabilities while using connector patterns, OAuth, token exchange, and event-based ingestion. The role requires substantial backend engineering experience, strong integration skills, and familiarity with cloud, AI agent, security, or identity ecosystems.

Build scalable customer intelligence workflows using Python, SQL, automation, product usage analytics, customer health modeling, and applied AI. Develop Slack summaries, data pipelines, renewal prediction models, and LLM-driven synthesis workflows. Partner with Customer Success and Analytics Engineering to identify customer risk, expansion, and adoption signals, improve health scoring, and deliver actionable insights. The role is remote-first and intended for an early-career engineering or analytics professional.

Develop and deploy AI-enabled features, including LLM and RAG workflows, for ontology-based intelligence applications. Integrate data streams, migrate cloud platforms across AWS, OpenShift, and Kubernetes, and build secure, scalable software using Python, Java, and Scala. Participate in Agile/Scrum delivery, DevSecOps, testing, CI/CD, code hardening, and vulnerability remediation. Collaborate with infrastructure, security, and mission teams while supporting complex network deployments and mentoring junior developers.

Develop and support Python backend services, RESTful APIs, integrations, data pipelines, and AI/ML-enabled enterprise applications. The role includes testing, troubleshooting, cloud-native development, production support, and collaboration with Agile teams and risk, audit, compliance, DevOps, and infrastructure stakeholders.

Define the technical vision and architecture for enterprise AI products, including multi-agent systems, tool-use frameworks, NL-to-SQL engines, RAG, and LLM reliability infrastructure. Partner with Product, Engineering, and Research leadership to bring AI capabilities to production scale. Design reusable context-engineering patterns, mentor senior engineers, lead high-stakes technical initiatives, and drive experimentation and technical excellence.

Operate and improve enterprise AI/ML platforms across Palantir Foundry, AWS Bedrock, and Amazon SageMaker. Responsibilities include deployment, monitoring, observability, automation, governance, model lifecycle management, incident response, root cause analysis, CI/CD, infrastructure as code, and production reliability. The role provides technical leadership and mentorship while partnering with data, infrastructure, security, architecture, product, and engineering teams to support cloud-based AI workloads and Generative AI adoption.

Build and productionize a Palantir Foundry analytics and predictive platform, including data pipelines, ontology, applications, governance, observability, and AI agent logic. Partner with client business and product teams to run discovery, define measurable outcomes, shape the product roadmap, and train internal engineers. The role requires end-to-end ownership, customer-facing consulting, executive presentations, and hands-on development with Python, SQL, LLMs, and AI agents.

Build and operate production AI agent features for Plane, including agent workflows, MCP servers, retrieval systems, customer-facing interfaces, evaluation harnesses, tracing, permissions, and audit models. The role requires shipping reliable LLM-backed features to real users, managing tool calling and failure recovery, measuring quality and performance, and partnering with engineering and product teams to deliver production surfaces.

Build and maintain high-throughput, low-latency backend services for Life360’s AdServer and Exchange platform. Own projects from architecture and implementation through deployment, improve real-time bidding and auction logic, integrate advertising partners, and support observability, incident response, and reliability. Collaborate with architects and product teams, use AI coding tools daily, mentor junior engineers, and contribute to engineering standards.

Owns the integration and testing manufacturing line for AI satellite compute hardware. Responsibilities include managing test infrastructure, designing tooling, assessing manufacturability, integrating vehicles, optimizing test operations, and investigating non-conformances. The role requires collaboration with engineers and technicians, hands-on work in production environments, test planning, configuration management, and occasional travel to SpaceX sites.

Designs and commissions factory automation systems for satellite AI hardware manufacturing. Responsibilities include PLC programming, robotic and conveyor controls, HMI development, electrical system design, safety compliance, machine commissioning, production-rate validation, troubleshooting, and operational handoff. The engineer also develops schedules and budgets, supports electromechanical integration, and ensures compliance with industrial safety and electrical standards.

Lead the vision and strategy for BNY's developer-facing AI products, collaborating across teams to enhance the developer experience and innovation in software engineering.

Own the design-for-manufacturing software layer of the Matter Compiler CAM stack. Develop computational geometry algorithms, manufacturability constraints, layout and retention logic, physical process models, validation systems, and production knowledge bases. Collaborate with AI, modeling, design, and process engineering teams to translate manufacturing expertise into auditable, testable code and validate results against fab runs.

Design, build, and optimize Python backend services, APIs, integrations, and data pipelines supporting intelligent agent workflows. Implement LLM, embeddings, RAG, and vector database solutions using AI/ML frameworks and external APIs. Improve deployed agents through prompt engineering and fine-tuning, while contributing to testing, CI/CD, monitoring, architecture, documentation, and enterprise deployment reliability.

As an AI Software Engineer, you'll design, develop, and support AI applications, optimizing integrations and ensuring quality solutions aligned with business needs.

Evaluates emerging AI technologies, platforms, infrastructure, and vendors through technical assessments, proof-of-concepts, benchmarks, and pilot deployments. Assesses solutions for capability, cost, risk, scalability, and business value; recommends adoption strategies; supports customers and internal stakeholders; delivers technical presentations, workshops, and demonstrations; and monitors developments in LLMs, automation, and agentic workflows.

Develop and support enterprise RPA solutions, including unattended UiPath robots, workflow automation, API and REST integrations, Office 365 automation, OCR, Document Understanding, and AI Fabric implementations. Responsibilities include technical design, development, robot monitoring and support, customer collaboration, process analysis, documentation, and applying RPA development best practices.

Develop AI-driven automation for government and national security workflows. Build and evaluate machine learning, LLM, NLP, data pipeline, and agentic systems; analyze complex datasets; create evaluation frameworks; and productionize reliable AI capabilities. Collaborate with engineers, mission specialists, and government users to translate ambiguous requirements into measurable solutions, demonstrate capabilities, gather feedback, and improve mission outcomes.

Build and deploy production-grade AI products end-to-end, from problem framing and data pipelines through live deployment and iteration. Collaborate directly with city leaders and customers, lead technical scoping workshops, and develop agentic solutions involving predictive modeling, real-time decision-making, data consolidation, and LLM-powered experiences. Design scalable APIs and reliable backend and frontend systems while helping establish the technical culture of a new AI Labs team.

Build and ship production-grade AI products end-to-end, from problem framing and data pipelines through deployment and iteration. Develop agentic solutions, predictive models, real-time decision-making tools, and LLM-powered experiences. Design scalable APIs and backend systems, collaborate with product and operations teams, lead technical scoping with city leaders, and help establish AI Labs’ engineering culture.

Develop and maintain full-stack web applications, including React-based interfaces, backend services, RESTful APIs, and Oracle PL/SQL solutions. Lead application analysis, design, development, testing, deployment, troubleshooting, security, and operational support. Collaborate with technology teams and business stakeholders, apply Agile practices, use CI/CD tools, leverage AI coding assistants, assess risks, and mentor junior analysts while operating with limited supervision.

Build the AI runtime for trustworthy agents: design orchestration, entity resolution, context assembly, connector orchestration, evidence retrieval, permissions and action policies. Own end-to-end features, prototype rapidly, implement evaluation frameworks, and collaborate with Product, Design, and Customer teams to deliver production-grade agent capabilities.

The Senior AI Software Engineer will lead architectural decisions and drive the development of a scalable Risk Management System, collaborating with various teams to enhance claims management efficiency while implementing AI solutions.