project manager for enterprise software

EPAM delivers enterprise software products, open source solutions, and accelerators for Fortune Global 500 clients.

• Lead projects from kick-off through go-live and post-production, aligning stakeholders around clearly defined success criteria;
• Own the delivery process end to end, including requirements, scope, risk, quality, and budget;
• Apply GenAI across the delivery lifecycle for productivity evaluation, risk detection, status reporting, and data-driven decisions;
• Set and enforce product quality benchmarks, engaging the team to meet them;
• Facilitate UAT and production deployments; manage releases and environments;
• Prepare the WBS, resource plans, and delivery roadmap;
• Act as the primary stakeholder contact, communicating status, risk, and progress with data;
• Interface with clients daily through demos, expectation management, and upskilling engineers on AI-augmented ways of working;
• Establish governance models, run Agile ceremonies, and define escalation, change, and risk-management procedures;
• Foster a collaborative environment; mentor, coach, and resolve people-management issues;
• Implement organizational best practices and embed AI tooling into team workflows.

• 7+ Years leading teams and projects, with at least five successful commercial enterprise deliveries;
• Ability to lead 50+ people, including direct people management;
• Hands-on use of GenAI for productivity evaluation, delivery insight, and decision-making, or strong technical depth with a track record of adopting new tooling quickly;
• Production experience delivering Digital, Data, or Cloud projects;
• Command of the full product lifecycle, from pre-sales to post-production support;
• Experience setting up Dev, QA, and BA processes on projects;
• Solid grasp of Agile, SAFe, and Kanban;
• Emotional intelligence, strong analytical and problem-solving skills, and cultural awareness;
• Fluent English;
• Prior hands-on engineering experience in development, architecture, or platform work;
• Ability to reason about system architecture, environment landscapes, sizing, and delivery techniques;
• Ability to challenge technical estimates and trade-offs credibly with engineering teams;
• Nice to have: Experience embedding AI/GenAI tooling into delivery or SDLC workflows, familiarity with DORA/flow metrics and data-driven delivery governance.

• No conditions specified