Technical Project Manager

Calsoft Japan; Bavdhan; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Calsoft Japan is seeking an experienced Technical Project Manager to lead complex enterprise software initiatives spanning cloud-native platforms, SaaS, data engineering, analytics, and AI-driven solutions. You will own technical delivery, coordinate cross-functional teams, and manage customer-facing communications across distributed engineers.

The role requires strong execution discipline, architectural participation, risk management, and release governance in a SAFe environment.

Qualifications

• 10+ years of experience in Technical Project Management.
• Experience managing enterprise-scale software development projects.
• Strong experience with distributed engineering teams.

Responsibilities

• Lead end-to-end execution of enterprise software projects and platform initiatives.
• Drive planning, estimation, execution tracking, release coordination, and governance.
• Coordinate multiple workstreams across UI, backend, cloud, DevOps, QA, and data engineering.
• Identify risks, dependencies, blockers, and mitigations proactively.
• Ensure predictable sprint and release execution across distributed teams.
• Facilitate Scrum ceremonies and coach Agile teams on best practices.

Skills

Technical PM

AWS

Cloud-native

SaaS

Data engineering

AI platforms

Cross-functional leadership

Stakeholder management

Agile/Scrum

Jira/Confluence

Tools

Jira

Confluence

Job description

Interview PRocess: L1, L2, Client (F2F Mandatory), Manager, HR

5 days WFO mandatory

Technical Project Manager (Cloud, SaaS, Data Engineering & AI Platforms)

Role Overview

We are looking for an experienced Senior Technical Project Manager to lead complex enterprise software initiatives involving cloud-native platforms, SaaS applications, data engineering systems, analytics platforms, and emerging AI-driven solutions. The role requires strong technical project ownership, cross-functional coordination, customer-facing communication, and execution leadership across distributed engineering teams. The ideal candidate should be capable of driving large-scale engineering projects involving AWS cloud technologies, microservices-based architectures, data platforms, platform modernization, and AI-enabled initiatives.

The Technical PM will work closely with: Engineering teams Architects Product stakeholders Customer engineering leaders QA and DevOps teams Data engineering teams External vendors and partner teams The role demands strong execution discipline along with sufficient technical depth to participate effectively in architecture discussions, delivery planning, risk management, release governance, and customer discussion.

Key Responsibilities:

• Project & Delivery Management Lead end-to-end execution of enterprise software projects and platform initiatives.
• Drive planning, estimation, execution tracking, release coordination, and delivery governance.
• Manage multiple concurrent workstreams across UI, backend, cloud, DevOps, QA, and data engineering teams.
• Identify risks, dependencies, blockers, and mitigation strategies proactively.
• Ensure predictable sprint and release execution across distributed teams.
• Drive engineering reviews, status reporting, stakeholder updates, and operational governance.
• Facilitate Scrum ceremonies including Sprint Planning, Daily Stand-ups, Sprint Reviews, Sprint Retrospectives, and Backlog Refinement.
• Coach Agile teams on Scrum principles, engineering best practices, and continuous improvement.
• Remove impediments impacting team velocity and delivery commitments.
• Track sprint health, team velocity, burn-down/burn-up metrics, and delivery predictability.
• Foster collaboration between Product Owners, Engineering teams, QA, DevOps, and business stakeholders.
• Promote Agile maturity, sprint discipline, and engineering accountability across multiple teams.
• Ensure effective backlog prioritization and sprint readiness in collaboration with Product Owners.
• Drive Agile Release Train (ART) execution within a SAFe environment.
• Facilitate and coordinate PI Planning, Iteration Planning, System Demos, Inspect & Adapt workshops, and Release Planning activities.
• Manage cross-team dependencies, risks, and execution across multiple Agile teams.
• Collaborate with Release Train Engineers (RTEs), Product Management, Product Owners, Architects, and Engineering Managers.
• Track Program Increment (PI) objectives, milestones, dependencies, and execution progress.
• Support technical decision-making by aligning architecture with project delivery goals.

Customer & Stakeholder Management:

• Act as the primary coordination point between customer stakeholders and engineering teams.
• Drive technical and project-level discussions with engineering managers, architects, and leadership teams.
• Translate business requirements into executable engineering plans.
• Provide transparent communication around delivery status, risks, and execution challenges.
• Facilitate requirement clarification, prioritization, and release planning.

Must-Have Skills & Experience

• Experience 10+ years of experience in Technical Project Management.
• Experience managing enterprise-scale software development projects.
• Strong experience working with distributed engineering teams.

Technical Understanding:

• Good understanding of AWS cloud ecosystem and cloud-native architectures. Experience with SaaS platforms and microservices-based systems.
• Understanding of APIs, backend systems, and distributed architectures.
• Understanding of Data Engineering concepts: ETL/ELT Data pipelines
• Reporting and analytics systems Familiarity with DevOps, CI/CD pipelines, and release processes.
• Strong understanding of Agile/Scrum delivery methodologies.

Tools & Practices:

• Experience with Jira, Confluence, and Agile tracking tools.
• Experience with SDLC processes and engineering governance models.
• Experience managing offshore/onshore coordination.
• Good to Have Exposure to AI/LLM-based systems and AI platform initiatives.
• Understanding of RAG, Agentic AI, or AI orchestration concepts.
• Experience with observability and monitoring platforms.
• Exposure to analytics/reporting platforms.