Top Artificial Intelligence Jobs

Lead design and deliver cohesive, AI-powered digital customer experiences across Actians product ecosystem. Map end-to-end journeys, create prototypes and CX artifacts, embed AI into touchpoints (chatbots, agentic workflows), drive self-service/product-led growth, run design workshops, translate research into prioritized improvements, and measure impact against customer and business metrics. Collaborate cross-functionally to convert strategy into actionable designs and present results to senior leadership.

Drive net-new and expansion sales for Databricks-focused data and AI solutions: identify target accounts, co-sell with Databricks, qualify opportunities, manage pipeline in Salesforce, lead discovery and proposals, coordinate technical teams, and close contracts across commercial and public sector clients.

Lead design, development, training, validation, and deployment of AI/ML/CV/DL models. Architect product features, mentor engineers, run technical reviews, manage milestones, and practice Agile/CI processes.

Lead enterprise AI strategy and portfolio, prioritize high‑impact use cases, build business cases, and ensure responsible AI governance. Provide technical leadership for prototyping, MLOps, model lifecycle, and integration with enterprise systems (SAP, Workday, Azure, Microsoft Copilot). Manage a small AI team, drive cross-functional adoption, change management, and executive communications to deliver measurable business value.

Design, build, and operationalize production-grade AI agents within the Microsoft ecosystem. Define agent architecture, implement RAG and multi-agent orchestration, integrate enterprise systems, establish governance, CI/CD, observability, and enable internal teams. Co-develop pilots, deploy Azure AI services, and drive adoption and scalable platform standards.

Design and evolve AI-enabled applications and system architecture for logistics workflows. Define where AI provides value, create data models, integrate vendor APIs, guide incremental shipping, and ensure usability and scalable engineering practices across product and platform.

Design and build secure, production-grade infrastructure that enables agentic AI systems to interact with Strikes platforms. Develop authentication/authorization for agents, orchestration and runtime environments, IDE agents, enterprise knowledge connections, tiered autonomy safety mechanisms, and embed with teams to operationalize frontier AI tools while enforcing security and ownership.

Lead design and development of AI-powered, multi-service travel experiences. Drive architecture, AI/ML integration (including human-in-the-loop and retraining), operational reliability, incident response, cross-team alignment, and mentoring to deliver scalable, measurable agentic AI solutions.

Architect and build autonomous AI agents for revenue operations: develop agentic systems using LangChain/LlamaIndex, implement RAG and prompt engineering, integrate with Salesforce and cloud services, optimize LLM inference, and add observability and scalable deployments to drive predictive sales and customer success automation.

Own and execute Lyfts illustration system across product and marketing. Lead brand migration, maintain Figma libraries and code handoff via LPL, develop motion for assets, manage intake and contractor work, collaborate with engineers and cross-functional partners, and contribute documentation and guidelines.

Produce customer-facing label and packaging designs, prepare print-ready files, create marketing graphics and AI-generated visuals, maintain asset libraries, and collaborate with leadership and marketing to deliver high-quality, on-brand creative across campaigns and product packaging.

Design and implement scalable graph-based search services and APIs. Build backend systems using Java and Spring Boot, integrate AWS services and databases, ensure observability with New Relic and Coralogix, and champion clean code and engineering best practices while collaborating across product and engineering teams.

Manage strategy creation, sales account management, and relationship building for Akamai. Drive revenue growth and improve customer relations in the telecommunications sector.

Administer and optimize the Greenhouse ATS, build recruiting dashboards and reports, integrate recruiting tech with HRIS/Slack, design and deploy generative-AI workflows to automate hiring tasks, train recruiters on AI tools and interview plans, and support interview coordination using AI scheduling assistants to improve hiring efficiency and data integrity.

Build and scale core AI-native healthcare products across the stack, focusing on real-time audio processing, NLU/transcription, clinical documentation, EHR integrations, and distributed production systems. Drive architecture, ship features with high ownership, and operate in a fast-moving, regulated environment.

Design, build, and operate enterprise AI platforms across the full ML lifecycle. Deliver infrastructure-as-code, reusable services, automated pipelines, and scalable deployments. Integrate data pipelines, model services, APIs, monitoring, and security to support real-time and batch workloads while ensuring high availability, performance, and cost efficiency.

Lead research and analysis of the enterprise AI services market, develop market sizing and forecasting models, publish actionable insights, advise clients and executives, create presentations and conference content, mentor junior analysts, support sales and research processes, and drive thought leadership and improvements. Travel up to 25% where applicable.

Build and prototype AI-enabled internal tools and automations by partnering with cross-functional teams, validating high-leverage use cases, integrating LLM APIs and SaaS systems, and modeling secure, responsible AI practices to enable broader adoption.

Build and own production applied-AI systems focused on information retrieval and LLM pipelines. Design experiment frameworks and evaluation pipelines, optimize for metrics (precision, recall, F1), run benchmarks, perform failure analysis, and iterate to improve real-world system performance at scale.

Design, build, and deploy reliable, outcome-driven AI systems and agentic workflows that plan, reason, and act across enterprise systems. Integrate LLMs into production, work with structured and unstructured data to ground models in business context, and partner with product to ship end-to-end capabilities.

Build and operate production agentic AI systems that convert longitudinal health data into actionable recommendations. Responsibilities include architecting stateful agent workflows, integrating LLMs and multimodal models, implementing retrieval and memory layers, ensuring production readiness and observability, standing up eval pipelines, optimizing cost/latency, and mentoring engineers while partnering with clinicians and cross-functional teams.

Lead design and implementation of agentic AI/ML solutions and modern software (APIs, microservices, CI/CD, streaming) on cloud platforms. Bridge legacy IBMi AS400 systems with modern AI, train and fine-tune models, oversee lifecycle, mentor engineers, set technical direction, and improve automation and testing across claims adjudication systems.

Build core data and AI infrastructure to ingest, model, and serve unstructured healthcare policy data. Design backend systems, data pipelines, LLM-powered RAG/embedding pipelines, evaluation frameworks, and platform APIs. Improve data quality, auditability, and system reliability while iterating rapidly with founders.

Designs, implements, and deploys cloud-native AI/ML solutions and data pipelines to support personalization and optimization. Builds and serves ML models (real-time and batch), develops APIs and front-end tools, automates workflows, and ensures secure, scalable AWS infrastructure. Leads architecture discussions, mentors engineers, manages project lifecycle, and advises senior management on technical strategy and risk.

Own and scale recruiting operations: hire and lead recruiting coordinators, architect ATS and recruiting tech stack, build AI-enabled automations, create hiring dashboards and SLAs, enable hiring managers with guides and training, and partner on headcount planning to improve pipeline conversion and time-to-hire.