Technical project manager [h1.location_city]
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Technical project manager • boston ma
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Job Title : Technical Project Manager.The Technical Project Manager plays a pivotal role in leading next-generation software rewrites using agentic AI and GenAI-assisted development.This is not a co...[show_more][last_updated.last_updated_1_day]
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Vantage Data Centers powers, cools, protects and connects the technology of the world's well-known hyperscalers, cloud providers and large enterprises.
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[job_preview.job_type]
- [job_card.full_time]
[job_card.job_description]10+ years in technical project or program management delivering complex software transformations. Certifications in Agile, Scrum, or AI / ML (e.g., AWS Certified Machine Learning, PMI-ACP) Strong curiosity and passion for learning cutting-edge technologies and continuously innovating. Experience leading initiatives involving emerging technologies or experimental delivery frameworks. Proven ability to define or iterate technical processes and success metrics in ambiguous environments. High technical fluency in AI / ML, generative AI, automation tools, and AI-augmented development workflows. Exceptional cross-functional communication skills for teams blending human engineers and AI systems. Strong executive stakeholder management experience, especially with technically complex initiatives. Experience managing AI-driven modernization or replatforming projects (e.g., monolith to microservices). Strong familiarity with cloud-native architectures (Azure preferred) and modern engineering practices (microservices, CI / CD, observability). Knowledge of agentic AI architectures, generative AI, and responsible AI practices. Familiarity with cloud AI platforms (AWS, Azure, GCP) and MLOps frameworks. Understanding of data privacy, security, and compliance requirements. Comfortable working in environments focused on breakthrough, transformative goals. Experience across industries, small business environments, or digital transformation initiatives. Inventive and adaptive : Thrives in shaping frameworks where none exist. Systems thinker : Believes process, technology, and human collaboration must evolve together. AI-native : Views AI as an intelligent collaborator, not just a tool. Builder of repeatability : Extracts insights from each cycle to strengthen the next. Impact-driven : Prioritizes customer experience and operational scalability.
Job Title : Technical Project Manager
Location : Bangalore / Hybrid
Duration : Full time
About the Role
The Technical Project Manager plays a pivotal role in leading next-generation software rewrites using agentic AI and GenAI-assisted development. This is not a conventional project management role-our methodology is new, evolving, and redefining how enterprise software is rebuilt. The TPM will help shape the metrics, methods, and practices that guide this transformation, balancing disciplined delivery with innovation and experimentation.
Key Responsibilities
- Lead AI-Accelerated Rewrites : Manage projects that modernize legacy applications into cloud-native, SaaS-based architectures using AI across all phases-Pre-Work, Rewrite, and Deployment.
- Shape a New Methodology : Collaborate with engineering, product, and AI specialists to co-create and refine the agentic rewrite methodology, establishing controls and metrics for GenAI-driven design, coding, and migration.
- Drive Measurable Innovation : Define and evolve metrics of success (efficiency, accuracy, reusability) where industry benchmarks are still emerging.
- Orchestrate AI + Human Collaboration : Coordinate teams that include AI agents, developers, and product owners-ensuring optimal task allocation, strong feedback loops, and process transparency.
- Manage Complexity & Ambiguity : Deliver high-impact outcomes without fully defined playbooks, creating governance structures that evolve as the methodology matures.
- Enable Scalable Replication : Document and systematize learnings from each rewrite cycle, contributing to a repeatable, high-efficiency rewrite factory model.
- Stakeholder Management : Bridge AI engineering teams, business stakeholders, and executives-translating experimental outcomes into meaningful business and technical insights.
- Risk & Quality Oversight : Identify, assess, and mitigate emerging risks in AI-assisted software generation (quality assurance, data leakage, model drift, etc.).
Required Experience
Must-Haves
Mindset & Attributes