Top AI & Machine Learning Jobs

Build the agent evaluation platform for multi-step enterprise AI agents. Responsibilities include orchestrating high-concurrency evaluations, developing OpenTelemetry-based tracing, creating stateful simulations of enterprise systems, managing datasets and reports, implementing validators and scoring, and establishing reliability, reproducibility, and SLOs. The role also develops calibrated evaluation signals that can optimize and train agent behavior.

Develop search relevance algorithms for an enterprise question-answering platform. Create and optimize ranking features, build frameworks for diversified ranking, design tooling for parallel ranking experiments, and develop metrics to evaluate search quality. Analyze query logs to identify improvements and collaborate with product, UX, customer success, and engineering teams to deliver accurate answers across heterogeneous knowledge sources.

Designs scalable data infrastructure, production pipelines, transformation systems, and automated agentic AI evaluation platforms. Defines ground-truth standards, evaluation metrics, quality gates, dashboards, and reproducible datasets for AI workflows. Partners across product, engineering, and data science teams, troubleshoots reliability and data quality issues, drives continuous improvement, and mentors junior engineers.

Own product strategy and execution for Action Fabric, ServiceNow's headless access layer for agentic AI. Define consumption-based pricing and monetization, build telemetry and metering, partner with platform and enterprise application teams, drive adoption and consumption metrics, and lead field messaging and industry partnerships.

Own product strategy and execution for Action Fabric, ServiceNow's headless access and monetization layer for agentic AI. Define invocation patterns, pricing and metering models, telemetry, and platform interoperability. Partner with platform, engineering, finance, and go-to-market teams to drive consumption, instrument usage, and position the product in the market. Shape standards, influence partners, and enable customers while tracking adoption and business metrics to iterate quickly.

Lead an 8-engineer team owning Build Agent's evaluation framework, model benchmarking, and telemetry. Define eval strategy, prompt sets, scoring, and failure taxonomy; drive cross-team accountability to turn findings into owned fixes; manage staffing and performance; represent results and model recommendations to stakeholders and executives.

Own and develop agent execution harness infrastructure for enterprise AI, including orchestration, reliability, observability, prompt management, evaluation frameworks, LLM integration, and multi-agent system boundaries. The role requires shipping production generative AI features, optimizing model cost and latency, designing distributed systems and APIs, and providing technical leadership through architecture, code reviews, and mentoring.

Build cloud-based AI and machine learning solutions for intelligent enterprise services. Collaborate with developers, product managers, quality engineers, and product owners to design, implement, test, and deliver scalable software. Apply high-performance algorithms, core AI/ML techniques, object-oriented programming, unit testing, profiling, and code tuning to improve user experiences and workflow efficiency.

Lead development of AI-native software using LLMs, agents, retrieval systems, cloud AI services, and scalable microservices. Design prompts, agent frameworks, data pipelines, and evaluation harnesses; ensure secure, reliable, and monitored production systems. Mentor engineers, conduct code and AI behavior reviews, manage goals, troubleshoot complex distributed and probabilistic systems, and collaborate with product and domain teams to deliver customer-focused AI solutions.

Design, build, integrate, tune, and launch AI agents on the Moveworks ServiceNow Platform for enterprise customers. The role translates business challenges into scalable AI solutions, integrates enterprise systems, develops full-stack workflows and automations, partners with product and engineering teams, and guides customers on technical adoption and agentic AI roadmaps. It also creates reusable solutions, documentation, architecture artifacts, demos, and customer training.