Project Manager

JOB Title: RPA Project Manager

Experience: 8+ Yrs

Notice Period: Immediate Preferred

Role Summary

RPA Project Manager

Key Responsibilities

• Lead and manage RPA projects across multiple domains, ensuring timely delivery, quality, and stakeholder satisfaction.

• Collaborate with business and technical teams to identify automation opportunities and design agentic AI-enhanced workflows.

• Oversee integration of RPA tools (UiPath, Automation Anywhere, Blue Prism) with agentic frameworks (LangChain, AutoGen, Semantic Kernel).

• Drive project planning, resource allocation, risk management, and reporting for automation initiatives.

• Ensure compliance with enterprise architecture, security, and governance standards.

• Facilitate client workshops, requirement gathering sessions, and solution walkthroughs.

• Mentor and guide cross-functional teams on best practices in RPA and agentic AI adoption.

• Track KPIs such as automation ROI, FTE savings, and productivity improvements. Required Skills & Experience

• 10+ years of experience in IT project management, with at least 5 years in RPA delivery.

• Proven track record of managing large-scale automation programs across industries.

• Hands-on experience with RPA platforms: UiPath, Automation Anywhere, Blue Prism.

• Familiarity with agentic AI concepts and tools (LangChain, AutoGen, Semantic Kernel).

• Understanding of Gen AI models (OpenAI GPT, Claude, Gemini) and their role in intelligent automation.

• Strong stakeholder management, communication, and leadership skills.

• Experience with Agile/Scrum methodologies and project tracking tools (JIRA, MS Project).

• Exposure to enterprise IT environments, cloud platforms, and data security standards. Preferred Qualifications

• Certifications in RPA tools (UiPath Certified Professional, Automation Anywhere Master RPA Professional, etc.)

• PMP or PRINCE2 certification.

• Exposure to AI/ML integration in automation workflows.

• Experience with vector databases and RAG architectures is a plus. Success Metrics

• On-time and on-budget delivery of automation projects.

• Successful integration of agentic AI components into RPA workflows.

• Documented business impact (cost savings, efficiency gains).

• Positive feedback from clients and internal stakeholders.

• Creation of reusable assets and frameworks for future automation initiatives.