Top Artificial Intelligence Jobs

Performs advanced risk analytics, reporting, data management, visualization, and modeling to identify portfolio trends, risks, control gaps, and business opportunities. Develops SQL-based datasets, dashboards, and executive reporting; investigates data quality and control issues; supports regulatory requirements; and partners with senior stakeholders on strategic initiatives. Uses automation and approved AI tools to improve analytical efficiency, process effectiveness, and risk-management outcomes.

Lead development of AI retrieval and agent infrastructure, including RAG, hybrid search, content ingestion, evaluation, observability, and orchestration tooling. Own initiatives from architecture through production, improve answer quality and system reliability, establish performance benchmarks, participate in incident response, and mentor engineers. Partner with product and engineering leadership to shape roadmaps and deliver scalable LLM-powered enterprise software.

Leads advanced analytics and insights initiatives within Fidelity’s Brokerage business to inform strategy, improve customer experiences, and drive measurable outcomes. Develops measurement frameworks, benchmarks, performance metrics, experimentation, and customer behavior analyses using diverse datasets. Translates complex business questions into actionable recommendations and communicates insights to senior stakeholders. Partners with analytics, engineering, data science, marketing, and product teams to drive personalization, innovation, and data-informed decision-making.

Paid summer finance internship supporting projects in energy markets. Interns receive industry training, coaching, networking opportunities, and leadership presentation experience. Responsibilities may include analyzing large datasets, drawing actionable conclusions, streamlining processes, and contributing to business projects. The role is based in EDF’s Houston office for a minimum of ten consecutive weeks and may lead to future rotational analyst opportunities.

Leads full-funnel, omnichannel demand generation across campaign strategy, account-based marketing, sales alignment, field marketing, events, marketing operations, reporting, and AI-driven workflows. The role manages budgets, marketing technology, attribution, pipeline optimization, and a team of campaign managers and marketing specialists while partnering with sales and business leaders to drive measurable commercial growth.

Own and grow Federal Civilian accounts by meeting sales quotas, acquiring new customers, expanding contracts, managing the full sales cycle, and cultivating executive and technical relationships. Develop account strategies, forecasts, pipelines, partner ecosystems, and business plans while presenting networking, cybersecurity, AI, and data security solutions to federal agencies, systems integrators, and resellers.

Lead technical recruiting for software and machine learning engineering teams. Develop hiring strategies, partner with engineering leadership, manage structured interviews, improve recruiting systems, analyze funnel metrics, mentor recruiters, and deliver strong candidate experiences. The role requires recruiting specialized technical talent, including autonomy, robotics, defense, embedded systems, or Physical AI professionals, in a fast-growing, in-office environment.

Build and manage technical talent pipelines across autonomy, AI/ML, embedded systems, and software engineering. Develop research-driven sourcing and talent-mapping strategies, partner with hiring managers to define candidate profiles, collaborate with recruiters to support candidate experience, and use market research and data to improve sourcing efforts.

Designs, builds, deploys, and optimizes generative AI and machine learning solutions on AWS, including Amazon Bedrock, foundation models, and RAG architectures. Develops document-processing automation, APIs, AI/ML models, monitoring, evaluation, and continuous-improvement processes. Integrates OCR, ICR, OMR, NLP, and data extraction capabilities while collaborating with cross-functional teams. The role also supports scalable cloud architecture, serverless applications, CI/CD, DevSecOps, and post-implementation troubleshooting.

Architects and delivers customized IVR, conversational AI, generative AI, and agentic virtual-agent solutions for enterprise customers. Leads technical design, development, integration, testing, deployment, consulting, customer workshops, and knowledge transfer. Designs speech-recognition and routing solutions, integrates external systems and APIs, guides Agile delivery, creates test strategies, advises stakeholders, and provides feedback to product and engineering teams.

Develop analytical models, simulations, and algorithms for RF, electronic warfare, PNT, communications, and autonomous systems. Perform performance assessments, trade studies, sensitivity analyses, and data validation. Build MATLAB and Python simulation environments and develop navigation, signal processing, tracking, detection, classification, and sensor fusion algorithms. Collaborate with multidisciplinary engineering teams, support prototypes and demonstrations, and contribute to technical reports, customer briefings, proposals, and technology roadmaps.

Build and operate production AI agents that automate multi-step workflows across internal teams. Responsibilities include integrating agents with internal systems and third-party tools, deploying on Amazon Bedrock AgentCore, creating evaluation and observability frameworks, implementing guardrails, measuring impact, and establishing reusable agent-development patterns. The role also requires partnering with nontechnical teams, translating ambiguous workflows into reliable automation, documenting solutions, and driving adoption.

Leads and develops a team of data scientists and analytics engineers while remaining hands-on. Oversees NPS, surveys, benchmarking, measurement frameworks, experimentation, predictive modeling, analytics pipelines, and AI-powered solutions. Partners with Finance, Product, Engineering, Operations, and senior leadership to turn complex business questions into scalable insights and improve strategic decision-making.

Design and implement backend and systems-level software for defense and intelligence applications. Integrate machine learning and signal-processing algorithms into real-time systems, transition models into field-ready applications, collaborate with domain experts, and build extensible software solutions for complex customer requirements.

Build and manage strategic relationships with AI assistant partners such as Gemini and ChatGPT. Lead consultative discovery, connect partner needs to Amadeus solutions, develop commercial opportunities, create account plans, prepare proposals, support complex negotiations, and share market insights. The role collaborates with Product, Product Marketing, Engineering, and internal stakeholders to shape AI-enabled travel solutions and sustainable commercial outcomes.

Build secure, scalable AI-powered applications and data products across frontend, backend, APIs, data platforms, and LLM capabilities. Develop RAG, vector search, AI agents, intelligent automation, dashboards, and enterprise workflows using React, TypeScript, Next.js, Python, and Node.js. Integrate banking and third-party data, create reusable components and design systems, and collaborate with product, design, data science, engineering, and business teams to deliver production solutions.

Develops production-grade, end-to-end AI and machine learning software solutions that modernize client systems and improve organizational efficiency. Responsibilities include frontend development, RESTful API implementation, production system design, CI/CD, containerization, secure coding, Linux systems, networking, and integration with enterprise security tools. The role requires collaboration across broader operating environments and may support federal or classified systems.

Integrate AI capabilities into production systems by connecting models, inference endpoints, and orchestration components. Implement reliable, secure inference flows, handle latency/token limits and batching, write integration tests, monitor and refine AI integrations, and collaborate with cross-functional teams to deliver scalable AI functionality.

Leads capital projects in regulated Life Sciences manufacturing and quality environments. Responsibilities include planning, scheduling, budgeting, risk management, vendor coordination, stakeholder communication, and cross-functional team leadership. Ensures compliance with GMP, FDA, GxP, validation, and internal quality requirements while managing technical platforms and project delivery across IT, automation, quality, engineering, and validation teams. This is a full-time onsite role in Ohio.

Manage the development, launch, and transition of alternative investment vehicles, including private equity, hedge funds, and co-investment structures. Coordinate cross-functional internal teams, external stakeholders, and service providers across concurrent commingled and bespoke fund projects. Drive process improvements, automation initiatives, and adoption of data, business intelligence, and AI tools to improve scalability and operational efficiency.

Conduct offensive security research across web applications, APIs, cloud infrastructure, and open-source software. Develop and exploit vulnerabilities, translate offensive techniques into AI agent behaviors and playbooks, create vulnerable environments and benchmarks, and analyze findings to reduce false positives. The role requires hands-on penetration testing, red teaming, bug bounty, or vulnerability research experience, strong web security knowledge, and Python or similar programming skills.

Design, build, deploy, and optimize scalable AI and machine learning systems using large datasets. Develop predictive models, recommendation systems, personalization engines, forecasting solutions, generative AI applications, and production ML pipelines. Collaborate with data, backend, and product teams to integrate models into applications, while monitoring performance, data quality, drift, reliability, and cost. Establish best practices for evaluation, experimentation, reproducibility, and deployment, and research emerging AI technologies.

Directs customer success for hundreds of accounts, owning onboarding, adoption, account tiering, coverage models, and health signals. Coaches a seven-person team through call reviews, partners with design and delivery, and improves renewal readiness. The role requires building the customer success program from scratch, automating processes with AI tools such as Claude, creating dashboards and workflows, and establishing realistic onboarding timelines and adoption plans.

Lead the data science function, owning machine learning strategy, predictive models, healthcare analytics, DBT data marts, and executive dashboards. Analyze claims, eligibility, pharmacy, EMR, HIE, clinical, and operational data to identify high-risk patients, evaluate clinical interventions, and improve patient and provider engagement using AI and LLMs. Collaborate with clinical, operations, and technology teams while leading data science staff in a fast-growing healthcare organization.

Provides technical direction for integrating AI and ML capabilities into enterprise and defense environments. Evaluates AI tools, designs data schemas and pipelines, configures APIs and connectors, develops adoption roadmaps, and establishes testing, continuous verification, monitoring, security, and compliance frameworks for AI-enabled solutions.