Top Artificial Intelligence Jobs

Lead architecture and implementation of Klaviyo's Customer Agent platform. Drive technical strategy for conversational AI at scale, ship AI-powered features, ensure reliability and observability, mentor engineers, and collaborate cross-functionally to evaluate emerging AI technologies and influence platform direction.

Design and build a global, serverless AI inference platform running on heterogeneous GPUs and accelerators. Optimize model scheduling, request routing, caching, and load balancing for low latency. Improve reliability and observability, lead cross-functional projects, and mentor junior engineers.

Plan and execute AI and developer-focused events and content, coordinate cross-functional teams and vendors, manage onsite speaker experience and event operations, maintain event tools and website, track deliverables, mitigate risks, and improve processes to scale community and advocacy programming.

Lead product management for Capital Ones Enterprise AI/ML platform, building intelligence capabilities and tools for data scientists and ML engineers. Drive roadmap, cross-functional execution with engineering, risk, security, and business partners, ensure governance, resiliency, and cost controls, and deliver scalable, user-centered platform experiences.

Design and implement multi-step agentic AI workflows (orchestration, retrieval, tool use, state management) using frameworks like LangGraph/LangChain. Build retrieval pipelines over proprietary CRE data, evaluate and monitor model quality with human-in-the-loop processes, integrate Anthropic models on AWS Bedrock, implement guardrails and observability, and rapidly prototype features with Product and Design to deliver trustworthy, source-linked AI capabilities that perform real business actions.

Own customer integrations for AI agent evaluations from scoping through delivery. Read API documentation, manage credentials, build custom integrations, run evaluations, assess AIUC-1 compliance, communicate technical results, and surface failure modes. Collaborate with customers, sales, delivery, standards, and core engineering teams while turning recurring field solutions into reusable product capabilities.

Leads complex government AI deployments from pre-sale discovery through production adoption, overseeing client relationships, delivery planning, cross-functional execution, change management, and executive communication. Translates agency workflows into technical requirements, manages risks and dependencies, drives measurable outcomes, and converts deployment feedback into product improvements. Builds deployment playbooks, operating cadences, and future delivery teams while supporting renewals and expansions. Requires strong AI/ML and enterprise systems fluency, senior stakeholder leadership, and 30–50% travel.

Owns Five9’s back-office AI transformation agenda through opportunity diagnostics, hands-on automation pilots, value measurement, and scaling roadmaps. The role partners with Finance, HR, Legal, IT, Business Technology, and executives to identify high-value workflows, build or deploy AI and automation solutions, validate measurable outcomes, and establish future-state operating models. It requires direct experience shipping back-office automation, quantitative business-case development, cross-functional change leadership, and the ability to build internal capability rather than rely on outside providers.

As a Forward Deployed Engineer, you will develop AI agents and automation workflows, collaborate with teams, and ensure secure, reliable solutions integrating with various systems.

Own and build JSSI’s AI-first data platform, including Bronze, Silver, and Gold pipelines in Microsoft Fabric and OneLake. Develop governed semantic layers for Power BI, ingest data into Azure SQL and ADLS Gen2, and enforce quality, lineage, security, governance, and PII controls aligned with Entra ID. Expose curated datasets to AI agents through approved APIs or MCP servers while using Claude Code and documentation-first engineering practices.

Owns the end-to-end order-to-cash and billing lifecycle across complex subscription, usage-based, and enterprise revenue models. Responsibilities include invoicing, collections, reconciliations, tax compliance, ASC 606 support, SOX readiness, KPI reporting, close support, billing-system optimization, automation, and team leadership. Partners with Sales, Legal, Revenue Accounting, Engineering, Product, and Collections on launches, pricing changes, and system migrations.

Guide enterprise customers in designing, securing, administering, and deploying Databricks environments on AWS. Architect scalable infrastructure, networking, identity, and security solutions; support pre-sales engagements through proofs of concept and technical content; and provide technical leadership, training, tutorials, and community contributions. The role requires expertise in AWS, distributed data architectures, infrastructure automation, programming, SQL, and customer-facing technical consulting, with travel up to 30%.

Support accounts receivable and collections through aging management, customer outreach, dispute resolution, payment coordination, reconciliations, dunning workflows, and ledger maintenance. Respond to billing inquiries, document resolutions, monitor account escalation thresholds, and collaborate with Billing, Revenue Accounting, Sales, Customer Success, Deal Desk, and Legal. Provide AR data for monthly and quarterly close while identifying recurring issues and maintaining strong customer relationships.

Designs, builds, deploys, and improves AI solutions and agentic workflows across the company. Responsibilities include evaluating AI tools, defining architecture, integrating systems, implementing guardrails, monitoring performance, documenting solutions, supporting training, and partnering with IT and Security on SOC 2 compliance. The role owns the technical AI roadmap and release readiness while enabling staff to adopt AI safely and effectively.

Designs and operates secure AI applications and backend microservices on AWS. Responsibilities include threat modeling, secure design reviews, vulnerability remediation, secure API development, AI guardrails, prompt testing, RAG pipelines, monitoring, audit logging, and incident readiness. The role collaborates with engineering, product, cloud infrastructure, and security teams to embed secure-by-design practices throughout the software development lifecycle.

Designs and builds secure, production-grade Generative AI and agentic AI applications using Python, LLMs, cloud services, and AI frameworks. Responsibilities include developing scalable AI pipelines, integrating Databricks data with AWS services, applying RAG and vector databases, evaluating models, implementing guardrails, researching emerging tools, improving application infrastructure, and guiding team members.

Leads the architecture, development, and deployment of production-grade agentic AI platforms. Builds multi-agent systems, RAG pipelines, fine-tuning applications, MCP servers, and full-stack applications using Python, Java, React, and microservices. Integrates vector and graph databases, develops prompt and intent logic, and collaborates with business subject matter experts to automate enterprise workflows. Provides technical leadership, mentors engineers, and ensures scalable, secure, production-quality AI solutions.

Design, develop, and productionize multimodal AI systems (VLMs, LLMs, reasoning models) and end-to-end ML pipelines for geospatial data. Build training/experiment frameworks, synthetic datasets, scalable inference, monitoring, and collaborate with research, engineering, and product teams to deliver Earth intelligence solutions.

Lead firmwide AI transformation by defining portfolio strategy, prioritizing high-impact AI initiatives, building governance and measurement frameworks, advising senior leaders with data-driven narratives, clearing execution roadblocks, and managing a team to deliver measurable strategic and financial value.

Lead go-to-market and key account sales for Rubrik Agent Cloud, evangelizing agentic AI governance and security solutions. Drive revenue, qualify opportunities, close deals, gather customer feedback, align product roadmap with market needs, develop sales/marketing collateral, and deliver enablement across Rubrik and partners.

Design and build AI-powered prototypes and end-to-end LLM workflows using Claude, ChatGPT, and other platforms. Partner with Services leaders to prioritize opportunities, translate needs into roadmaps, integrate AI with internal systems, and help productionize solutions. Create documentation, run enablement sessions, and drive adoption across Global Services while collaborating with centralized AI engineering.

Design and prototype AI-powered solutions (LLMs, agents, prompts) to solve creative and operational problems, integrate AI with internal data and APIs, enable teams through documentation and training, and partner with engineering to productionize scalable workflows across Services.

Lead and support PET/CT scientific collaborations with KOLs, drive publications, grant and patent efforts, coordinate research and prototype evaluations with internal teams, and execute research contracts while keeping partners informed.

The Senior Analyst will develop AI and ML algorithms, optimize data systems, and present research findings. Requires extensive experience in model development, system architecture, and MLOps.

Design, build, deploy, and scale production AI applications and agents. Translate business problems into scalable AI solutions, develop backend services and APIs, integrate with enterprise data platforms, ensure observability, governance, and MLOps, and collaborate with cross-functional client teams.