Top Artificial Intelligence Jobs

Develop AI-powered software applications for Blue Origin’s New Glenn launch vehicle. Responsibilities include building agentic workflows, integrating LLMs and machine learning models, developing backend services and prototypes, processing engineering data, managing AI API integrations, and supporting AI adoption across aerospace engineering teams. The role also involves debugging, deployment, reliability improvements, and collaboration with senior engineers.

Leads enterprise sales and strategic customer relationships across utilities, power distribution, infrastructure, and data centers. Develops new business, manages pipelines, leads proposals and onboarding, and partners with operations, product, marketing, and leadership teams. Advises customers on workforce, contractor, outage, maintenance, and project needs while shaping go-to-market strategies and scalable sector processes. Mentors account team members and provides market insights to improve offerings and growth.

Build and launch internal tools, workflow systems, operations software, and AI-enabled automations across affordable housing operations. Translate business processes into scalable technical solutions, prioritize a product roadmap, and measure business outcomes. Responsibilities span maintenance optimization, expense reconciliation, vendor-payment anomaly detection, resident-renewal analytics, and operational efficiency. The role requires hands-on product and BizOps experience, rapid iteration, technical fluency, and practical use of AI, LLMs, data, dashboards, and SQL.

Build and optimize production AI inference systems for transformer and multimodal models. Responsibilities include extending inference frameworks, improving batching, decoding, caching, quantization, and multi-GPU serving, profiling GPU workloads, benchmarking performance, supporting new model architectures, and contributing to production operations. The role requires strong Python and C++ skills, GPU performance expertise, and experience modifying inference frameworks such as vLLM, SGLang, or TensorRT-LLM.

Strategically sources and recruits specialized AI, data, analytics, technology, and innovation talent. Advises senior leaders on workforce needs, talent strategies, market conditions, compensation, and hiring decisions. Builds diverse pipelines, engages passive candidates, manages complex searches, delivers a strong candidate experience, and uses recruiting data and technology to improve efficiency.

Conduct original AI/ML research across search, recommendations, NLP, and agentic workflows. Prototype and productionize AI systems, address AI and analytics UX challenges, and contribute to scalable infrastructure for model experimentation, training, and evaluation. The role requires a current AI/ML PhD student with strong machine learning knowledge and an understanding of the end-to-end ML lifecycle, including data curation, training, deployment, and monitoring.

Own the carrier conversion funnel for a freight marketplace, improving auctions, bidding, negotiation, matching, and booking experiences. Partner with data science, operations, trust, fraud, and engineering teams to develop pricing and matching mechanisms. Define success metrics, prioritize initiatives, manage experimentation amid incomplete data, and lead products from problem definition through launch and impact assessment.

Develops and leads communications strategy for Anthropic’s Safeguards and product safety work. Responsibilities include translating complex AI and safety topics for broad audiences, managing crisis communications, coordinating messaging across research, product, policy, legal, and safeguards teams, building media relationships, crafting announcements, and overseeing executive interviews and speaking engagements.

Serves as a hands-on technical lead building, deploying, and operating governed agentic AI and LLM solutions on Databricks. Develops RAG and multi-agent systems, MCP integrations, secure tools, prompt and context engineering, AI Gateway controls, identity authorization, observability, CI/CD, testing, and monitoring. Partners with business, security, risk, compliance, and data teams to deliver measurable outcomes in a regulated banking environment, while establishing governance standards and mentoring engineers.

Develops, tests, deploys, and supports enterprise AI applications, including LLM solutions, AI agents, RAG systems, workflow automations, integrations, and retrieval services. The role also supports model evaluation, monitoring, optimization, data preparation, governance, security, compliance, documentation, and operational reporting within a regulated banking environment.

Leads architecture and hands-on implementation of scalable AI Defense systems that detect, validate, and stop threats to AI applications, agents, and foundation models. Owns high-performance platform services, LLM inference and model-hosting strategy, secure enterprise deployments, and production delivery. Partners with Product, Threat Research, and Operations while mentoring engineers and guiding technical strategy across teams.

Develops and evaluates AI-powered software, automation scripts, prototypes, and enterprise solutions using programming languages, LLMs, APIs, and AI-assisted coding tools. Collaborates with engineers, architects, and business development teams on technical research, federal proposals, workflow automation, and solution documentation. The role also assesses AI-generated code for quality, security, performance, and maintainability while supporting adoption of approved AI technologies.

Build and operate production AI infrastructure for multi-agent systems across customer clouds. Develop Python or Go tooling, CLIs, controllers, and services; deploy and optimize LLM inference with Kubernetes and vLLM; manage MLOps, model releases, observability, CI/CD, GitOps, security, and multi-cloud platform reliability. The role also involves Kubernetes operators, Terraform, GPU scheduling, agent runtimes, evaluation pipelines, and developer self-service automation.

Conduct intelligence research and assessments to identify mission needs, capability gaps, analytic challenges, and future requirements. Evaluate intelligence processes, tools, data sources, workflows, and interoperability. Develop DOTMLPF-P recommendations, technical documentation, decision-support products, briefings, and requirements for emerging technologies such as artificial intelligence, machine learning, automation, and advanced analytics. Coordinate with analysts, collection managers, technical experts, operational users, and senior stakeholders supporting Army and Joint intelligence capability development.

Lead full-stack development of agentic AI workflows and a payroll platform using React, TypeScript, .NET, event-driven systems, and Azure. Design secure, scalable architectures; supervise AI-generated code; establish prompts, evaluations, guardrails, and testing practices; deliver frontend and backend features; own automated unit, integration, and end-to-end testing; and mentor engineers while influencing technical direction and business outcomes.

Designs, develops, and maintains AI-enabled business system solutions, automation pipelines, enterprise integrations, analytics, and reusable application components. Partners with stakeholders and platform owners to translate business needs into secure, scalable solutions across Oracle, Salesforce, Foundry, and low-code platforms. Supports AI governance, data protection, compliance, data lineage, architecture, documentation, and operational procedures.

Design and build production AI infrastructure that automates financial reporting, reconciliation, variance analysis, and narrative generation. Develop AI agents, data pipelines, retrieval systems, and workflow orchestration with strong reliability, auditability, governance, and human review controls. Partner with Finance, Data Platform, Security, Risk, Audit, and Compliance teams; establish applied AI standards; evaluate tooling and models; mentor engineers; and translate between technical and financial requirements.

Architect and build Verizon’s enterprise AI control plane, integrating AI developer platforms with governance hubs. Develop APIs, CI/CD governance pipelines, responsible AI and security guardrails, agent simulation, observability telemetry, IAM, and secure routing for autonomous workflows. Collaborate with platform engineering, DevOps, DataOps, data science, and AI product teams to operationalize LLMs and agentic systems at enterprise scale.

Develop AI-powered cyber defense applications, full-stack interfaces, backend services, APIs, agent workflows, and secure integrations. Connect security telemetry, machine learning models, inference services, and response tools while implementing controlled autonomy, access controls, audit trails, testing sandboxes, and monitoring. Evaluate agent behavior and support production infrastructure through troubleshooting, maintenance, documentation, and collaboration with cybersecurity and infrastructure specialists.

Lead product marketing for Aladdin Studio, defining positioning, market strategy, launches, adoption programs, thought leadership, and technical enablement. Translate APIs, data workflows, platform architecture, and AI capabilities into compelling narratives for technical and business audiences. Partner with product, engineering, sales, solutions, and client teams to drive adoption, quantify ROI, influence roadmaps, and scale global go-to-market impact.

Build and deploy applied AI solutions for legal and business workflows. Partner with attorneys and operational leaders to identify use cases, design AI applications, orchestrate agentic workflows, engineer prompts, integrate solutions with enterprise systems and APIs, validate outcomes with stakeholders, document delivery, and monitor emerging AI technologies. The role requires software solution delivery experience, hands-on AI building, prompt engineering, API integration, cloud knowledge, and strong communication skills.

Own the full QA lifecycle for AI-powered legal solutions, including unit, integration, system, regression, performance, scalability, and security testing. Partner with analysts and engineers to generate edge-case tests, validate AI outputs, integrate automated test suites into Azure DevOps CI/CD pipelines, track defects, maintain documentation, and report quality metrics. The role also promotes quality practices across the development workflow and evaluates solution reliability under real-world conditions.

Lead enterprise workforce AI initiatives using Microsoft 365 Copilot, Copilot Studio, Azure AI services, and Power Platform. Guide AI governance, security, compliance, responsible adoption, and scalable productivity solutions. Partner with business and technology teams, mentor engineers and citizen developers, troubleshoot outages, conduct capacity planning, coordinate third-party support, and lead service restoration. The role requires after-hours maintenance and participation in an on-call rotation.

Leads SAP Next Gen’s AI-enabled go-to-market strategy, cross-functional project execution, influencer initiatives, career-site updates, and executive reporting. Supports AI process optimization, knowledge sharing, and structured PMO delivery for AI initiatives. Designs qualitative feedback mechanisms for students and early talent, synthesizes findings with quantitative data, and provides actionable insights to improve programming and demonstrate community impact.

Conducts research, development, and demonstrations for modernizing nuclear power plant instrumentation and control systems. Develops digital architectures, mathematical models, testbeds, requirements, designs, and validation processes; coordinates with industry, government, academia, vendors, and regulators; ensures compliance with nuclear standards; publishes findings; prepares proposals; supports technology transfer; and mentors junior staff.