About Lyzr

Lyzr.ai is on a mission to put enterprise-grade agentic AI in the hands of every organisation. Our Professional Services team partners with marquee clients — from global consulting firms to Fortune 500 enterprises — to design, deploy, and scale Lyzr-powered AI agents in production.

As Senior Project Manager, you will own end-to-end delivery of these high-stakes engagements, acting as the connective tissue between client stakeholders, Lyzr's engineering pods, and Lyzr's product and commercial teams.

About the Role

As Senior Project Manager (Infra Deployments), you will own the end-to-end technical delivery of high-stakes enterprise engagements. You will be responsible for orchestrating infrastructure deployments from source repositories across multi-cloud environments, ensuring seamless deployment, stability, and scale.

Acting as the vital connective tissue between enterprise client stakeholders, Lyzr’s cross-functional engineering pods, and our commercial leadership, you will balance rigorous technical execution with strategic client management.

What You'll Own

Delivery, Infrastructure Deployment & Client Success

• End-to-End Delivery: Lead complex, multi-phase AI agent deployments (from SOW execution through hypercare) across multiple concurrent enterprise client projects.

• Infra-as-Code & Repository Deployment: Oversee infrastructure deployments directly from repository source code into client environments (Cloud/On-Prem).

• Project Governance: Define project scope, Work Breakdown Structure (WBS), risk registers, and RAID logs from kick-off; maintain a single source of truth for scope, timeline, and status.

• Steering & Communication: Run executive steering committees and weekly client status calls; deliver clear, concise written updates that build trust and surface critical decisions early.

• Scope & Change Management: Manage client-side change requests and scope creep using a structured CR process, protecting both Lyzr’s margins and client satisfaction.

• Go-Live & Hypercare: Oversee User Acceptance Testing (UAT), go-live readiness, and hypercare handovers to ensure every deployment enters production on a secure, stable footing.

Commercial Accountability & Practice Building

• Account Expansion: Identify and qualify organic growth and expansion opportunities within active accounts, partnering with the account team.

• SOW & SLA Definition: Support SOW drafting, milestone definitions, and SLA parameters for new and renewal engagements.

• Practice Refinement: Contribute to professionalizing Lyzr’s Professional Services practice by refining delivery frameworks, deployment templates, and lessons-learned libraries.

What You Bring

Core Experience & Expertise

• Track Record: 6–10 years in client-facing Project Management roles, specifically delivering enterprise AI, automation, cloud infrastructure, or SaaS platform deployments.

• Multi-Cloud & Container Mastery: Hands-on familiarity and delivery experience with AWS, GCP, Azure, Kubernetes, and Docker.

• Repository-Driven Deployments: Demonstrated experience managing infrastructure deployments directly from source repositories (Git/CI-CD pipelines).

• Multi-Project Handling: Proven ability to simultaneously manage multiple enterprise client deployments without compromising quality or timeline.

Methodology & Tools

• Delivery Frameworks: Strong command of Hybrid Agile-Waterfall delivery models tailored for enterprise SaaS/AI integrations.

• Tooling: Proficient with Jira, Confluence, MS Project, or Notion.

• Certifications (Preferred): PMP or PMI-ACP certification.

Communication & Commercial Acumen

• Executive Presence: Comfortable presenting to and managing C-suite, VP, and Director-level stakeholders.

• Commercial Instinct: Strong ability to read SOWs, track utilization burn rates, and navigate hard scope conversations constructively.

• Technical Translation: Ability to simplify complex cloud and AI infrastructure nuances for business audiences while translating business requirements into technical specs for engineering teams.

Bonus Points

• Experience with Agentic AI frameworks, LLM-based product architectures, or Intelligent Automation / RPA programs.

• Background working in Big-4 consulting, global systems integrators (GSIs), or high-growth enterprise AI startups.