Top Artificial Intelligence Jobs

Leads the development of partner enablement programs for Databricks and Snowflake ecosystems. Establishes strategies, governance, stakeholder relationships, learning pathways, workshops, bootcamps, champion networks, and readiness frameworks for technical and business audiences. Translates data, AI, analytics, and lakehouse use cases into scalable learning experiences, aligns programs with partnership growth objectives, measures engagement and effectiveness, and continuously improves initiatives based on partner feedback and business impact.

Designs and maintains scalable data pipelines and architectures for operational, intelligence, and mission data. Aggregates, cleans, transforms, and analyzes structured and unstructured datasets using Python, Maven Smart System, Palantir, Power BI, and AI-enabled tools. Develops dashboards, data models, metrics, reports, and decision-support products for C-UAS operations and acquisition efforts. Requires collaboration with technical and mission stakeholders, strong data governance practices, executive communication skills, and an active TS/SCI clearance.

Leads Unlearn’s engineering organization across core engineering, applications, ML/AI Ops, infrastructure, and forward deployment. Owns system quality, reliability, compliance, security, execution, hiring, team design, and engineering roadmap delivery. Partners with Product, R&D, Delivery, and company leadership to translate strategy into shipped AI-powered platforms, tools, and services in a regulated environment. Establishes an AI-centric culture and ensures engineering commitments align with business objectives.

Executive leader responsible for enterprise technology operations, cybersecurity, data strategy, governance, digital transformation, AI adoption, and technology risk management. Oversees infrastructure, business systems, compliance, disaster recovery, business continuity, data platforms, analytics, technology investments, and high-performing technology teams. Advises executive leadership and develops multi-year roadmaps aligned with corporate strategy, operational priorities, and risk objectives.

Provides executive oversight of end-to-end healthcare revenue cycle operations, including patient access, coding, billing, denials, collections, payer contracting, and financial performance. Evaluates AI-generated analyses and workflow tools, establishes enterprise KPIs, leads transformation initiatives, and presents strategic recommendations to executives, boards, and investors. The role also annotates AI outputs and provides structured feedback for healthcare AI training datasets.

Partners with sales teams and customers to drive AI and Developer Platform revenue. Leads technical discovery, architects cloud and serverless solutions, develops proofs of concept, presents to strategic stakeholders, and advises customers on Cloudflare products. Collaborates with product, marketing, and technical teams to improve adoption, content, use cases, and value propositions.

Develop AI harnesses and agentic systems integrating AI/ML services, enterprise platforms, cloud infrastructure, and modern user interfaces. Build secure, distributed architectures; implement CI/CD, automated testing, performance and token optimization, and anti-hallucination controls. Collaborate with technical and executive stakeholders to deliver strategic systems, support rapid-cycle R&D, and improve engineering standards. The onsite McLean role includes occasional travel and requires eligibility for a security clearance, with TS/SCI preferred.

Lead the technical and product direction for Klaviyo’s Customer Agent, building and scaling production conversational AI systems. Design orchestration, evaluation, guardrails, memory, context, and failure-handling capabilities; write and review code; resolve complex production issues; establish reusable engineering patterns; mentor engineers; and partner with product, design, data science, and go-to-market teams. The role requires hands-on ownership of reliable, secure, multi-tenant agentic systems operating against live customer traffic.

Build the data and AI platform for construction equipment dealerships. Responsibilities include developing Python ingestion pipelines, orchestrating cloud workloads, maintaining canonical schemas in Databricks and PostgreSQL, resolving entities, extracting information from documents with LLMs, and building LangChain/LangGraph agent workflows. The role also involves production cloud deployment, human-in-the-loop approvals, model routing, observability, action logging, and autonomous execution safeguards.

Leads SEO and Answer Engine Optimization strategies across traditional search engines and generative AI platforms. Oversees content workflows, optimizes metadata, landing pages, site architecture, crawlability, redirects, canonicalization, and crawler directives, and partners with web development teams. Uses enterprise SEO, AI observability, and analytics tools for keyword research, competitive intelligence, performance reporting, and growth opportunities. Also guides content teams and independently manages complex initiatives.

Founding Engineer responsible for building FilmoreAI’s production AI and data platform for construction equipment dealers. The role covers agent infrastructure, model routing, LLM extraction and reasoning, canonical data modeling, entity resolution, Python data pipelines, Azure cloud orchestration, evaluation, observability, and safe human-approved write-back. The engineer will work independently in an ambiguous startup environment and use agentic development tools to ship reliable systems with strong cost, latency, accuracy, and operational guardrails.

Lead scientific communications and external engagement for Click's digital therapeutics pipeline; publish and present clinical evidence; build KOL relationships; provide scientific support for business development and partnerships; and collaborate cross-functionally with product, clinical, and regulatory teams to align development with clinical evidence and market access requirements.

Owns customer success for strategic enterprise customers using Edwin’s AI platform. The role guides customers from deployment through adoption, value realization, and Autonomous IT maturity; develops success plans, monitors usage and health signals, leads executive business reviews, demonstrates ROI, identifies expansion opportunities, and coordinates with Sales, Product, Engineering, Marketing, and AI Impact teams. The strategist also contributes customer insights and improves AI-first engagement playbooks.

Lead design, development, and deployment of scalable AI/ML applications and MLOps pipelines on Kubernetes. Mentor engineers, define best practices, adopt emerging GenAI tools, ensure observability, security, and alignment with business objectives, and maintain documentation and runbooks.

Serves as a technical authority and trusted advisor for sales teams, customers, and partners. The role develops customer architectures, demonstrates Elastic solutions, supports sales cycles from discovery through technical win, enables partners, creates sales collateral, engages communities through events, and communicates customer needs to product and engineering teams. The position requires strong technical presales and customer relationship skills, with 30% regional travel and occasional international travel.

Lead and grow a team of approximately 12 kernel engineers developing high-performance inference kernels across NVIDIA, AMD, and ASIC hardware. Own the MAX kernel roadmap, performance optimization, portable kernel architecture, and delivery. Partner with framework, serving, compiler/runtime, hardware enablement, and Qualcomm teams while advancing AI-assisted development, verification, and engineering practices.

Own the vision, roadmap, and lifecycle of Kong’s AI Management portfolio, including AI Gateway capabilities, agentic harnesses, LLM routing, policies, context, guardrails, and evaluation. Align engineering, design, marketing, and executives; translate complex AI infrastructure concepts into product requirements; manage backlogs, dependencies, technical debt, and delivery timelines; and support customer engagements and sales enablement.

Designs, optimizes, validates, and supports AI accelerator systems, GPU clusters, Gaudi platforms, and cloud infrastructure for large-scale machine learning workloads. Responsibilities include platform bring-up, system-level debugging, test planning, firmware integration, automated testing, monitoring, full-stack troubleshooting, production deployment, architectural improvements, and mentoring junior engineers. The role collaborates with OEM vendors and cross-functional teams to improve AI infrastructure performance, stability, and reliability.

Architects and builds AI-augmented DataOps capabilities for resilient, observable, scalable data platforms. Responsibilities include intelligent pipeline failure detection and recovery, AI-driven data quality monitoring, automated remediation, productionizing agentic systems, leading architecture and design reviews, partnering across engineering and business teams, troubleshooting platform performance, evaluating modern data and AI technologies, and mentoring engineers.

Develops and implements AI and LLM solutions, including generative AI applications, pilot projects, deployment, monitoring, troubleshooting, testing, and integration. Collaborates with technical and functional stakeholders to identify use cases, define requirements, evaluate models, incorporate feedback, and transition successful pilots into operational capabilities.

Lead an agile engineering team to architect, develop, and productionize secure, scalable software that integrates LLMs and generative AI. Drive AI-assisted engineering practices, mentor engineers, translate business requirements into technical roadmaps, automate reliability, and ensure compliant, high-quality delivery.

Build, deploy, and operate AI/ML models, scalable MLOps pipelines, and real-time inference systems. Collect and process diverse data sources, improve training data quality, monitor model reliability and drift, and validate AI features with real-world users. The role also involves documenting best practices, mentoring teammates, and staying current with emerging AI technologies, LLMs, security risks, and model-development techniques.

Build AI-powered workflows, agents, integrations, and internal tools that automate People Operations. Partner with People, Engineering, and IT to modernize onboarding and other employee processes, while implementing secure access controls, human oversight, escalation paths, and production-ready architectures. Prototype with users, iterate quickly, and measure improvements in efficiency, employee experience, and operational consistency.

Design, develop, deploy, and scale AI-powered solutions, digital workers, intelligent automation, and enterprise AI capabilities. Build Python-based generative and agentic AI solutions using LLMs, vector databases, embeddings, semantic search, and knowledge retrieval. Integrate AI with enterprise platforms and workflows, establish engineering and responsible AI standards, evaluate emerging technologies, and lead innovation pilots in collaboration with business, architecture, engineering, and operations teams.

Leads AI/ML engineering teams and technical strategy for enterprise-scale healthcare and pharmacy solutions. Oversees development, deployment, governance, MLOps, security, and operations for generative AI, LLM, NLP, predictive analytics, and agentic AI capabilities. Partners with product, engineering, data science, and executives to align technology with business goals, evaluate emerging technologies, improve automation, and develop engineering talent.