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) required.
High technical fluency in AI/ML, generative AI, and automation tools.
Proven experience managing AI-driven modernization or replatforming projects.
Strong familiarity with cloud-native architectures (Azure preferred) and modern engineering practices.
Exceptional cross-functional communication skills across human and AI systems.
Strong executive stakeholder management experience on complex initiatives.
Responsibilities
Lead AI-Accelerated Rewrites: Manage modernization of legacy apps into cloud-native, SaaS architectures using AI from Pre-Work to Deployment.
Shape a New Methodology: Work with engineering and product teams to refine a new agentic rewrite methodology.
Drive Measurable Innovation: Define and evolve metrics for success amid emerging industry benchmarks.
Orchestrate AI + Human Collaboration: Coordinate diverse teams for optimal task allocation and feedback loops.
Manage Complexity & Ambiguity: Deliver outcomes and create governance in uncertain environments.
Enable Scalable Replication: Document learnings to support a repeatable rewrite factory model.
Stakeholder Management: Connect AI engineering teams and business stakeholders for insightful outcomes.
Benefits
Hybrid working model offering flexibility.
Access to continuous learning and development opportunities.
Dynamic and innovative work environment focused on cutting-edge technologies.
Full Job Description
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
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.
Must-Haves
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.
Mindset & Attributes
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.
