Top AI & Machine Learning Jobs

Build, optimize, and deploy LLM-powered agents, AI workflows, and production data pipelines for enterprise construction clients. Lead implementations from discovery through production, partner with customer technical teams, translate operational challenges into AI strategies, and deliver measurable business value. The role requires strong machine learning and software engineering skills, customer-facing technical delivery, and travel to client sites exceeding 50% of the time.

Design and build production AI infrastructure that automates financial reporting, reconciliation, variance analysis, and narrative generation. Develop AI agents, data pipelines, retrieval systems, and workflow orchestration with strong reliability, auditability, governance, and human review controls. Partner with Finance, Data Platform, Security, Risk, Audit, and Compliance teams; establish applied AI standards; evaluate tooling and models; mentor engineers; and translate between technical and financial requirements.

Leads data science initiatives from solution design through production, developing and validating statistical, predictive, and machine learning models. Partners with clients to translate business needs into analytics solutions, establishes development and monitoring best practices, reviews Python code, mentors data scientists, and communicates technical findings to executives. The role also contributes to technical strategy, roadmaps, project planning, and business development while collaborating with engineering, product, and business teams.

Build and deploy applied AI solutions for legal and business workflows. Partner with attorneys and operational leaders to identify use cases, design AI applications, orchestrate agentic workflows, engineer prompts, integrate solutions with enterprise systems and APIs, validate outcomes with stakeholders, document delivery, and monitor emerging AI technologies. The role requires software solution delivery experience, hands-on AI building, prompt engineering, API integration, cloud knowledge, and strong communication skills.

Lead enterprise workforce AI initiatives using Microsoft 365 Copilot, Copilot Studio, Azure AI services, and Power Platform. Guide AI governance, security, compliance, responsible adoption, and scalable productivity solutions. Partner with business and technology teams, mentor engineers and citizen developers, troubleshoot outages, conduct capacity planning, coordinate third-party support, and lead service restoration. The role requires after-hours maintenance and participation in an on-call rotation.

Build and deploy AI-powered go-to-market agents, growth experiments, enrichment and signal-detection systems, lead scoring, outbound programs, attribution, SEO tooling, and sales enablement workflows. The role requires independently shipping experiments, measuring pipeline and conversion impact, contributing to Foley’s shared AI platform and ontology, and applying appropriate consent, privacy, deliverability, and release guardrails.

Leads the enterprise AI risk and governance function, establishing multi-year strategy, governance frameworks, risk standards, assessment processes, model risk management, monitoring, control testing, and regulatory readiness. Advises executives on AI adoption and risk decisions, partners with control and technology functions, oversees third-party AI requirements, represents the firm in examinations and audits, and builds a specialized AI risk organization.

Analyze large datasets to identify fraud patterns, emerging risks, and strategy improvements. Develop fraud detection rules and models, monitor performance and loss metrics, build dashboards and reporting, evaluate data sources and analytical methods, and translate findings into recommendations. The role partners with Fraud, Risk, Product, Technology, and Operations teams while applying statistical analysis, predictive modeling, AI tools, and sound judgment when handling sensitive data.

Build and operate production machine learning and generative AI infrastructure, including Azure and Databricks pipelines, CI/CD workflows, RAG systems, APIs, model-serving services, infrastructure as code, automated testing, monitoring, versioning, and governance. The role requires collaboration with AI, ML, data, infrastructure, security, and governance teams to deliver scalable, secure, reproducible, and high-performance AI solutions.

Build and debug LLM agents, integrations, and AI workflows using Python and APIs. Provide technical office hours, mentoring, code reviews, and debugging support to colleagues. Develop reusable agent frameworks, starter kits, evaluations, documentation, and learning resources. Partner with internal teams on AI platform adoption, identify skill gaps, track learning outcomes, and escalate complex data, security, or production issues.