Top Artificial Intelligence Jobs

Build and deploy AI-powered products across the frontend, backend, APIs, databases, and model integrations. Own features end to end, design maintainable interfaces and data models, connect applications to LLMs and agents, use AI-assisted coding tools, write tests, review code, troubleshoot production systems, and mentor teammates.

Crafts strategic copy for email and scripted phone campaigns, develops call-center scripts and training materials, collaborates with strategists, designers, technology teams, clients, and legal reviewers, conducts creative testing and quality assurance, maintains brand voice, and uses AI to improve drafting and proofreading.

Supports AI governance projects by assessing risks and controls, documenting processes, gathering requirements, analyzing information, and synthesizing findings. Advises clients on regulatory compliance, risk management, internal controls, and governance improvements. The role involves applying AI/ML governance frameworks such as NIST and ISO, translating technical concepts for stakeholders, collaborating with diverse teams, and developing expertise in corporate governance and risk management.

Leads AI and data solution architecture for client transformation programs. Designs generative AI, data modernization, LLM, vector database, RAG, and LLMOps solutions; develops roadmaps and evaluation frameworks; advises executives; drives innovation; manages workstreams, client relationships, business growth, thought leadership, and team mentorship.

Leads client-focused generative AI and data modernization architecture, translating business needs into scalable solutions using Google Cloud, Vertex AI, LLMs, vector databases, and modern data platforms. Advises stakeholders, develops AI evaluation and guardrail practices, guides experimentation and deployment, presents technical recommendations, supports proposals, and coaches teams through complex transformation programs.

Leads the company’s AI-first enterprise and digital technology strategy, including AI governance, enterprise modernization, cloud, data platforms, software development, digital commerce, cybersecurity, and automation. Advises the CEO and board, oversees global technology teams and budgets, drives digital transformation and M&A integration, and builds scalable technology capabilities that improve innovation, productivity, consumer experiences, and profitable growth.

Lead HPC and AI benchmarking across CPU, GPU, networking, memory, and storage platforms. Analyze scientific, engineering, LLM, training, inference, and I/O workloads; identify bottlenecks; and optimize applications, frameworks, libraries, compilers, runtimes, and system software. Apply parallel computing, GPU acceleration, profiling, and memory and I/O optimization while translating findings into customer-focused recommendations.

Own access, identity, and integration work connecting the AI platform to business systems. Translate requests into API, authentication, account, scope, and permission requirements; coordinate IAM, SSO, OAuth apps, approvals, connector builds, testing, credential rotation, revocation, documentation, and troubleshooting across IT and engineering teams.

Lead research and thought leadership on data management and AI readiness, produce actionable insights, advise clients and sales, present at events, mentor analysts, and improve research processes to drive client outcomes.

Designs, develops, and deploys enterprise Generative AI and LLM applications. Builds RAG architectures, agentic AI workflows, vector search and retrieval pipelines, REST API integrations, and cloud-native Azure services. Works with stakeholders and engineering teams to deliver secure, scalable solutions, supporting testing, deployment, monitoring, troubleshooting, and optimization. Requires strong Python, AI application development, Azure, search, API, and software engineering skills.

Own regional revenue growth for Implicity’s cardiac remote monitoring platform across the Northeast. Responsibilities include prospecting and closing hospital and clinic accounts, managing consultative sales cycles, engaging clinical and executive stakeholders, supporting onboarding and expansion, analyzing pipeline and market data, and representing the company at industry events. The role may evolve into mentoring and recruiting sales team members.

Build and operate LLM-powered features, agentic workflows, NLP pipelines, and event-driven backend services for insurance claims. Responsibilities include designing evals and guardrails, implementing semantic search and structured outputs, modeling relational, document, and graph data, tracing model calls, enforcing privacy and security, writing technical designs, and participating in on-call support.

Owns the architecture, delivery, and operation of LLM-powered systems and agentic workflows for insurance customers. Responsibilities include designing NLP and retrieval pipelines, evals and guardrails, durable event-driven systems, tracing, auditing, privacy, security, and tenant isolation. The role also authors technical designs, reviews code, mentors engineers, manages production operations and on-call, and collaborates with product managers, data scientists, and customers.

Advise CIOs and CDOs at property and casualty insurance carriers and brokers on data and AI strategies. Responsibilities include establishing data governance, quality, and architecture foundations; sequencing initiatives for measurable business value; translating between business stakeholders and delivery teams; and partnering with account teams. The role requires deep P&C insurance expertise, hands-on data and AI program experience, CIO-level advisory credibility, and comfort in sales-adjacent client engagements.

Advises enterprise clients on digital experience and AI strategy, including maturity assessments, transformation roadmaps, platform selection, AI use cases, governance, and implementation planning. Leads executive workshops, presentations, pilots, and proof-of-concepts while maintaining trusted client relationships. Owns account growth, proposals, scoping, pricing, and business development. Contributes to consulting methodologies, thought leadership, team development, and AI delivery frameworks.

Design, implement, and support modern endpoint management across Microsoft and Apple environments. Manage Intune policies, security baselines, applications, provisioning, migrations, and Apple enrollment workflows. Develop PowerShell automation, version-controlled configurations, and CI/CD-aligned processes to improve operational consistency. Troubleshoot endpoint issues, document procedures, support escalations, provide technical guidance, and apply AI tools to improve service delivery and automation.

Create, review, and evaluate federal and military reporting materials, including WARs, SITREPs, after-action reports, and executive briefings. Develop reference documents, sample responses, evaluation rubrics, and AI-training guidelines while ensuring accuracy, clarity, compliance, and adherence to official reporting conventions. Provide structured feedback and expert input on reporting requirements and deliverable quality. The role requires federal or military reporting experience, strong writing and editing skills, attention to detail, and responsible handling of sensitive information.

Hands-on senior quality engineer building automation-first test frameworks across API, UI, integration, data, and end-to-end workflows. Use AI/GenAI tools to accelerate test design, triage, and coverage. Improve unit test strategy, CI/CD quality gates, observability, and resilience. Analyze defect patterns, create quality dashboards, and partner with engineering and product to increase automation coverage and reduce escaped defects in regulated wealth management systems.

Architect and build AI reasoning systems, agentic workflows, and multimodal intelligence pipelines for regulatory, financial, and spatial analysis. Develop production-grade LLM applications, integrate validation and evaluation frameworks, process scanned documents and schematics, and own AI-powered features across models, backend workflows, and customer-facing interfaces. The role emphasizes reliability, observability, autonomous ownership, and full-stack product development within a remote founding team.

Leads engineering for enterprise agentic AI and LLM platforms. Designs and deploys production-grade LLM services, RAG solutions, autonomous agents, APIs, and cloud-native AWS architectures. Provides technical leadership, architecture guidance, code reviews, MLOps, monitoring, governance, and operational excellence. Drives responsible AI practices and adoption of AI-assisted development across teams, emphasizing security, auditability, human oversight, scalability, and performance.

Leads software engineering initiatives within an agile banking technology team. Designs, develops, reviews, debugs, and troubleshoots secure production code; drives responsible AI-assisted development practices; improves automation and operational stability; evaluates architectures and vendors; and promotes modern engineering technologies. The role requires advanced programming, generative AI and machine learning familiarity, distributed systems, cloud platforms, microservices, APIs, databases, containerization, performance testing, and chaos engineering experience.

Develops AI-driven Celonis prototypes and proof-of-concept solutions using SQL, PQL, machine learning, and LLMs. Consults with customers to identify business challenges, presents value propositions, quantifies ROI, leads platform demonstrations, and builds trusted advisor relationships. Partners with sales, implementation, product, and engineering teams to deliver value realization and reusable best practices through the 12-month Orbit Program.

Supports enterprise growth through strategic market research, business analytics, account intelligence, and AI innovation. The intern will research companies and competitors, analyze market trends, prepare strategic presentations, and help design and test AI agents and intelligent workflows for automated research and reporting. The role collaborates with Sales and Marketing while identifying ways to improve productivity and decision-making using generative AI and emerging technologies.

Creates and manages content across social media, blogs, newsletters, executive communications, and marketing campaigns. Supports brand storytelling, thought leadership, industry positioning, and demand generation. Uses generative AI and automation tools to improve content workflows and productivity. Manages publishing schedules, researches trends, monitors engagement and campaign performance, collaborates with Sales, and ensures accurate, consistent brand messaging.

Develop and deploy machine learning algorithms for defense and commercial applications, working with images, text, graph data, NLP, computer vision, reinforcement learning, and large language models. Responsibilities include analyzing large datasets, building inference models, using cloud services for training and deployment, researching emerging methods, and preparing technical documentation. The role requires Python, machine learning experience, a relevant bachelor’s degree, at least two years of experience, and an active TS/SCI clearance with CI Poly.