Top Artificial Intelligence Jobs

Build production AI systems for finance teams, including per-customer anomaly-detection models, grounded natural-language generation, and agentic workflows with verification checkpoints. Integrate managed LLMs across AWS, Azure, and GCP; develop Python services with SQL and warehouse access; and enforce rigorous evaluation for grounding, hallucination, and faithfulness. The role also involves customer-specific modeling, anti-leakage practices, human confirmation, user-feedback loops, and secure containerized deployments.

Applies Generative AI and emerging technologies to advertising and VFX production. Develops ComfyUI workflows for high-fidelity visuals and short-form video, integrates AI assets with traditional VFX pipelines, and collaborates with artists and production teams. The role requires strong visual judgment, 3D workflow expertise, AI agent experience, creative problem-solving, and the ability to implement efficient solutions under tight deadlines.

Lead architecture for eBay’s agentic customer experience platforms. Define reusable patterns spanning AI models, orchestration, retrieval, tools, workflows, policy, evaluation, and human support. Architect integrations with enterprise knowledge, APIs, transactional systems, and case management while optimizing reliability, security, scalability, latency, observability, and cost. Evaluate emerging AI technologies, validate decisions through prototypes and technical reviews, and influence architecture across multiple engineering teams.

Coordinate OpenAI’s Government Trusted Access portfolio across sensitive public-sector domains. Own intake through offboarding, maintain portfolio visibility, build operating mechanisms, coordinate cross-functional reviews, track risks and decisions, monitor program health, support government-facing communications, and convert manual processes into scalable workflows, documentation, automation, and tooling.

Lead enterprise presales discovery, shape Azure cloud and AI solutions, and guide sales wins through architecture, consulting, and executive communication. Design solutions spanning data, AI, security, integration, and Power Platform; develop SOWs, phased delivery plans, estimates, assumptions, and risk controls. Translate AI and automation requests into measurable business outcomes, manage delivery risk and deal readiness, and coordinate clean handoffs among sales, delivery, and leadership.

Build and deploy AI and machine-learning capabilities for cyber threat hunting, anomaly detection, incident response, detection engineering, and security automation. Develop custom models, LLM applications, and agentic systems, managing the full production lifecycle from data preparation through monitoring. Partner with security, engineering, offensive security, and governance teams to evaluate emerging technologies, support responsible AI, advise leadership, and mentor technical staff.

Leads enterprise workforce AI enablement, adoption strategy, and transformation initiatives. Oversees AI Solutions Consultants, identifies workflow opportunities, establishes prioritization and engagement models, develops learning programs, and partners with business, engineering, governance, and finance teams. The role measures productivity, quality, adoption, and business value while promoting responsible AI use and translating emerging capabilities into scalable enterprise solutions.

Lead the maturity and optimization of Google SecOps, including detection rules, parsers, data pipelines, log integrations, and platform administration. Develop AI-assisted security workflows, automations, enrichment capabilities, and high-confidence detection content. Partner with Security Operations, Threat Intelligence, Incident Response, and Engineering teams to improve alert triage, investigations, response times, data quality, and analyst productivity. Track detection effectiveness and maintain technical documentation.

Provides technical advisory and systems engineering support for AI-enabled applications in DoD environments. Evaluates LLM, RAG, agentic AI, orchestration, architecture, data pipelines, security, scalability, and model performance. Develops prototypes, recommendations, documentation, and briefings; supports testing, guardrails, and evaluation frameworks; and collaborates with engineers, platform teams, product managers, and government stakeholders to integrate secure AI capabilities.

Designs and deploys Vectra AI integrations across AWS, Azure, and GCP. Builds cloud-native microservices, distributed telemetry and ingestion pipelines, security analytics integrations, and infrastructure-as-code deployments. Integrates NDR with SIEM, SOAR, identity, Zero Trust, and logging platforms while optimizing performance, security, and resiliency. Develops dashboards, automation, runbooks, and monitoring strategies for secure cloud environments.

Leads pharmaceutical commercial analytics and AI activation across brand, marketing, and field teams. Develops machine learning and statistical models for targeting, segmentation, forecasting, launch readiness, and promotional impact measurement. Translates complex analyses into executive recommendations, identifies practical AI use cases, ensures privacy and governance compliance, and drives adoption across cross-functional and global teams.

Leads pharmaceutical commercial analytics and data science initiatives supporting brand, marketing, and field teams. Develops machine learning, statistical, predictive, segmentation, targeting, forecasting, and causal models using pharmaceutical commercial data. Translates analyses into recommendations, identifies practical AI opportunities, supports pilots, and drives adoption across business stakeholders. Partners cross-functionally on launch readiness, opportunity sizing, performance tracking, governance, privacy, and compliance while providing subject-matter expertise in pharmaceutical data and commercial strategy.

Leads enterprise AI initiatives from ideation through production, designing generative AI, LLM, RAG, and agentic solutions. Establishes scalable architectures, evaluation frameworks, guardrails, MLOps/LLMOps practices, and responsible AI governance. Partners with pharmaceutical commercial, marketing, analytics, IT, vendors, and senior stakeholders to prioritize use cases, demonstrate business value, and drive adoption. Mentors teams and builds organizational AI capabilities.

Leads and develops a customer-facing Cyber Applied AI Architect team across pre-sales discovery, solution design, implementation, deployment, and adoption. Partners with customers, Sales, Solutions Engineering, Product, and Engineering to build AI-enabled cybersecurity solutions using OpenAI models, APIs, Codex, and agentic workflows. Oversees architecture, technical escalations, governance, integrations, customer outcomes, reusable assets, and team performance.

Build customer-facing agentic AI experiences, including chatbots, embedded assistance, MCP integrations, and automated reconciliation workflows. Partner with product teams, domain experts, customers, and engineers to identify valuable AI applications across fund-management software. Design reliable multi-step agent systems, evaluate model outputs and failure modes, and ship production software while shaping product direction in a fast-moving environment.

Build and deploy AI agents for logistics and transportation across email, phone, and SMS. Improve model reasoning, fine-tune foundational models, integrate AI tools, and create evaluation frameworks for agent performance. Collaborate with engineering, product, and logistics teams to solve complex operational problems. The role requires Python, cloud AI deployment, model optimization, and familiarity with TensorFlow or PyTorch. A bachelor’s degree in a related field is required.

Design, build, deploy, and support AI workflows and internal applications across finance, construction, investments, asset management, HR, and legal. Automate document processing, invoice coding, reconciliations, reporting, audits, and knowledge workflows using Claude, APIs, code, and MCP integrations. Partner with department leaders, ensure accuracy and security, manage exceptions, train users, document systems, and measure adoption, reliability, and cost.

Owns positioning, messaging, competitive intelligence, content, and sales enablement for Moby, Triple Whale’s AI product. The role translates complex AI capabilities into customer value, develops market differentiation, evaluates competing solutions, creates collateral and demonstrations, and serves as an AI evangelist. The manager collaborates closely with Product, Engineering, Sales, Customer Success, Growth, Brand, and executive leadership to improve product adoption and go-to-market effectiveness.

Design, build, and productionize LLM-powered systems (adaptive content, tutors, evaluators) and AI pipelines (RAG, embeddings, fine-tuning). Prototype and optimize models across modalities, define AI safety/evaluation/observability practices, and collaborate with product and engineering to measure learner outcomes and iterate.

Lead the vision and strategy for ServiceNow’s enterprise search, RAG, question-answering, and conversational AI products. Drive measurable business and customer outcomes, guide engineering and ML partners, incorporate user research and market insights, expand AI capabilities across the platform, and define performance metrics. Manage and mentor a team of at least four Product Managers while securing executive alignment and delivering scalable, customer-centric solutions.

Senior Sales Operations Manager serving as the primary operations partner to the Chief Revenue Officer. Owns sales metrics, forecasting, pipeline analysis, quota and territory planning, executive reporting, cross-functional initiatives, analyst quality, performance management, and sales headcount planning. Requires advanced modeling, Salesforce expertise, executive communication, program management, and experience supporting B2B SaaS sales organizations.

Build, deploy, test, scale, and optimize machine learning models and AI inference workflows for edge and cloud environments. Develop maintainable software components and APIs, profile performance, document engineering designs and benchmarks, and communicate technical trade-offs across software, machine learning, and hardware teams.

Drive adoption and growth of Heartflow’s cardiovascular diagnostic technology within assigned accounts. Build relationships with cardiologists, referring physicians, administrators, and clinical stakeholders; educate customers; develop account plans; coordinate cross-functional resources; organize clinical programs and events; and increase cCTA and FFRCT utilization. Performance is measured by quota attainment, account growth, referral expansion, and clinical pathway adoption.

Leads enterprise GEOINT systems integration, architecture, requirements, testing, transition, and readiness initiatives across NGA and mission partners. Develops transition roadmaps, architectures, requirements, CONOPS, analyses, and risk mitigations; coordinates IPTs and governance activities; supports GEOINT data standards modernization; and drives adoption of cloud, Agile, digital engineering, MBSE, automation, and AI. Provides technical leadership, customer advising, mentoring, and task oversight for complex multi-agency programs.

Designs enterprise parsing and document preprocessing architecture for AI agents and LLM applications. Responsibilities include orchestrating OCR and vision-language technologies, building resilient data pipelines, defining semantic schemas and chunking rules, architecting retrieval and vector database integrations, implementing secure GraphRAG access controls, and enforcing data lineage and automated PII/PHI filtering. Requires a relevant bachelor’s degree, 10 years of experience, AI data-processing expertise, governance knowledge, and active federal security clearance.