Top Artificial Intelligence Jobs

Support technical recruiting by coordinating interviews, managing candidate communications, collecting and aggregating interviewer feedback and assessment scores, and learning to source engineering talent from GitHub, Stack Overflow, and other technical communities. Assist with scheduling technical screens and pair-programming interviews and maintain candidate tracking and reporting.

Lead a cross-functional enterprise AI adoption program: design governance, prioritize AI use cases, run change management and enablement, measure adoption and ROI, manage vendor/tool alignment, and report progress to the C-suite and Board.

Build and maintain end-to-end mobile trading systems for iOS and Android. Ship production-quality, well-tested code, apply blockchain and crypto knowledge, and integrate AI tools to improve engineering workflows. Break down projects, collaborate cross-functionally, conduct and act on code reviews, mentor teammates, and participate in hiring and onboarding. Influence product decisions through data-driven insights and provide domain expertise for mobile trading initiatives.

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.

Design, deploy, and maintain on-prem AI infrastructure and agentic systems. Build GPU clusters, model serving, vector DB-backed RAG pipelines, fine-tune and deploy models, implement governance (MCP), and automate CI/CD and monitoring to integrate AI capabilities into enterprise workflows.

The role involves applied research in LLMs, developing evaluation frameworks, managing knowledge graphs, and collaborating with engineers for scalable AI solutions.

The AI Engineer will design, build, and operate AI solutions for Federal clients, ensuring platform portability and compliance with federal standards.

Lead vision, architecture, and delivery of an enterprise AI engineering platform. Align platform capabilities with engineering, security, and cost controls; enable self‑service AI tooling, governance, and production‑grade CI/CD for AI workflows; build and mentor a high‑performing platform team; and drive responsible, scalable adoption of AI across the company.

Conduct quantitative research to design and validate trading models, alpha signals, and analytics; apply statistical and ML methods to large financial datasets; develop research code and AI tools (Python, Matlab, SQL); collaborate with traders, SSA researchers, and academics to translate findings into scalable trading indicators and internal/client materials.

Lead AI-first strategy and architecture for Unified Communications, designing production-grade AI/ML solutions (NLP, agentic assistants) and scalable cloud-native MLOps across AWS/Azure/GCP, collaborating with engineering, product, and legal to deploy real-time mission-critical audio/video/data capabilities.

Lead design and delivery of secure, cloud-native AI/ML and data platforms for DoW test & evaluation. Architect AWS-based solutions, drive MLOps and DevSecOps practices, mentor teams, support cloud migration, implement CI/CD and automated testing, and apply Zero Trust and federal cybersecurity controls to mission workflows.

Lead end-to-end AI/ML projects: build, deploy, and maintain LLM/NLP and ML models in production. Translate business needs into technical plans, collaborate cross-functionally, apply MLOps and observability best practices, and improve model performance and reliability.

Lead product strategy and roadmap for WorkSolo's international AI creator platform. Design AI-native creation workflows, drive localization and market fit, run user research and experimentation, partner with AI/ML, design, engineering, and data teams, and own cross-functional execution and go-to-market readiness for overseas markets.

Lead strategic partnerships and channel development to grow WorkSolo internationally. Identify, negotiate, and close partnerships and integrations, develop go-to-market plans, manage partner lifecycle, track partnership performance, and collaborate with product and marketing to drive creator acquisition and revenue.

Evaluate and edit AI-generated scripts, design end-to-end content generation workflows, optimize AI writing skills and prompt patterns, and ensure culturally resonant, production-ready scripts for international audiences while collaborating with engineering and product teams.

Principal AI Forward-Deployed Engineer designs and builds production-grade AI and agentic systems, leads forward-deployed projects with business stakeholders, authors scalable cloud architectures (AWS), implements MLOps/DevOps best practices, and ensures operational excellence, security, and measurable business outcomes.

Build and productionize AI systems for logistics: multi-agent copilots, forecasting/optimization models, evaluation and observability, continuous learning loops, and operational reliability. Mentor engineers and make build-vs-rule tradeoffs while shipping high-impact ML services.

Lead development and deployment of AI/ML solutions for target discovery, translational research, biomarker identification, and scientific decision-making. Partner with scientists and engineering teams to build scalable workflows for complex biological and multimodal data, promote best practices, mentor colleagues, and recommend emerging AI technologies to accelerate research.

End-to-end full-stack platform engineer operating AI agent fleets to deliver a multi-tenant B2B platform. Own cloud infra, backend services, React frontends, Postgres/graph data, and deep SAP/ERP integrations. Build automation, verification tooling, runbooks, and adversarial validation to ship coherent, production-verified changes across repositories.

The Principal Applied AI Engineer will lead the design of AI systems for finance, focusing on predictive modeling, intelligent automation, and software engineering best practices. They will oversee AI initiatives, mentor technical teams, and ensure compliance with financial standards and practices.

Lead design, build, and scaling of Agentic AI and industry-specific solution accelerators on Genesys Cloud. Develop reusable multi-agent workflows, RAG-based knowledge orchestration, integrations with enterprise systems, prototypes, and production-grade AI applications. Provide technical leadership, mentor engineers, collaborate with product and industry SMEs, and deliver repeatable solution blueprints to accelerate deployment and time-to-value.

Lead Motivosity's business applications, integrations, automations, and AI transformation. Partner with stakeholders to gather requirements, prioritize and deliver systems projects, build a roadmap, establish governance and change management, and manage a small team to improve operational efficiency and scale AI-powered solutions.

Build and launch AI-powered user-facing features on a Ruby on Rails backend. Integrate LLMs (OpenAI, Google, Anthropic), own zero-to-one product initiatives, write well-tested maintainable code, and mentor engineers while collaborating with product, design, and cross-functional teams.

Produce 2-3 long-form, SEO- and AI-search-optimized articles weekly (≈65 hrs/month). Own content from brief to final draft, use AI tools responsibly, incorporate firsthand AI experimentation, and align content with brand voice and marketing objectives.

Lead client discovery, design and deliver AI prototypes and integrations using LLMs, RAG, and agentic frameworks. Build, evaluate, and optimize models and retrieval pipelines, integrate AI into workflows, mentor teams on responsible AI, and produce evaluation and governance artifacts for federal clients.