Technical Project Manager - Java

Job Description – Technical Project Manager (AI & Digital Engineering):

Position: Technical Project Manager (TPM)

Employment Type: Full-Time

We are seeking a highly experienced Technical Project Manager (TPM) with a strong engineering background and proven expertise in delivering enterprise-scale digital transformation and AI-driven initiatives. The ideal candidate will possess hands-on experience in Java, Python, Node.js, Cloud (AWS & Azure), and a solid understanding of Agentic AI architectures and enterprise AI adoption.

This role requires an individual who can bridge business strategy with technical execution, lead cross-functional engineering teams, manage complex stakeholder relationships, and ensure the successful delivery of cloud-native, AI-powered applications.

Key Responsibilities:

• Lead end-to-end delivery of complex technical programs from planning through production rollout.
• Own project planning, execution, milestone tracking, risk management, dependency management, and delivery governance.
• Drive sprint planning, release management, production deployments, and post-production stabilization.
• Ensure projects are delivered on time, within scope, budget, and quality expectations.
• Establish delivery metrics, KPIs, and executive dashboards for leadership reporting.

Technical Leadership:

• Collaborate with Engineering, Product, and Architecture teams to translate business requirements into scalable technical solutions.
• Provide technical guidance across Java, Python, Node.js, microservices, APIs, and cloud-native architectures.
• Participate in architecture reviews, solution design discussions, and technical feasibility assessments.
• Drive engineering best practices, scalability, security, and operational excellence.

AI & Agentic AI Enablement:

• Lead the delivery of AI-powered applications leveraging Agentic AI frameworks and enterprise LLM platforms.
• Work with AI Engineering teams to implement intelligent agents, orchestration workflows, RAG pipelines, and AI-driven automation.
• Understand enterprise AI governance, responsible AI practices, prompt engineering, and AI application lifecycle.
• Collaborate with Data Science and AI teams to operationalize GenAI use cases into production.

Cloud & Platform Engineering:

• Drive cloud-native application delivery on AWS and Microsoft Azure.
• Collaborate with Platform Engineering teams on infrastructure, networking, security, scalability, and cost optimization.
• Work closely with DevOps teams to implement CI/CD pipelines, Infrastructure as Code (IaC), containerization, and deployment automation.
• Ensure applications meet enterprise standards for reliability, observability, and security.

Agile Delivery & Scrum Leadership:

• Act as Scrum Master for one or more Agile teams.
• Facilitate Agile ceremonies including Sprint Planning, Daily Stand-ups, Sprint Reviews, and Retrospectives.
• Coach teams on Agile best practices and continuous improvement.
• Remove delivery impediments and improve team velocity and predictability.

Stakeholder Management:

• Serve as the primary point of contact for business, technology, vendors, and executive leadership.
• Communicate project health, risks, dependencies, and mitigation plans proactively.
• Translate business objectives into technical roadmaps, user stories, and implementation plans.
• Drive alignment across multiple engineering and business teams.

Documentation & Governance:

• Author and review Functional Specification Documents (FSDs), Solution Design Documents (SDDs), Technical Design Documents (TDDs), and architecture documentation.
• Ensure complete traceability from business requirements to delivered functionality.
• Support QA and UAT teams through requirement clarification and acceptance criteria validation.
• Drive governance around SDLC, release management, and change management processes.

Required Skills & Qualifications:

Education:

• Bachelor's or master’s degree in Computer Science, Engineering, Information Technology, or a related field.

Technical Skills:

• Strong engineering background with hands-on experience in:
• Java
• Python
• Node.js
• Strong understanding of REST APIs, Microservices, Distributed Systems, and Event-Driven Architectures.
• Hands-on experience with AWS and Microsoft Azure Cloud (Mandatory).
• Experience with Docker and Kubernetes/OpenShift.
• Good understanding of CI/CD pipelines using GitHub Actions, Jenkins, Azure DevOps, or GitLab CI.
• Knowledge of DevOps practices and Infrastructure as Code.

AI & Modern Technologies:

• Understanding of Agentic AI concepts and enterprise AI architectures.
• Experience working with:
• Large Language Models (LLMs)
• LangChain
• LangGraph
• Microsoft Agent Framework / Semantic Kernel
• Retrieval-Augmented Generation (RAG)
• AI orchestration frameworks
• Exposure to enterprise AI governance and AI-assisted software development.

Project Management:

• 15+ years of experience in Technical Project Management.
• Proven experience delivering enterprise software projects using Agile methodologies.
• Experience working as Scrum Master and/or Agile Coach.
• Strong understanding of SDLC, DevOps, Release Management, and Change Management.
• Experience in project planning, estimation, budgeting, resource management, and risk mitigation.

Documentation:

• Experience writing and reviewing:
• Functional Specification Documents (FSD)
• User Stories
• Acceptance Criteria
• Technical Design Documents
• Solution Architecture Documents

Soft Skills:

• Excellent communication and presentation skills.
• Strong stakeholder management and executive reporting capabilities.
• Ability to manage cross-functional engineering teams.
• Strong analytical, problem-solving, and decision-making skills.
• Customer-first mindset with exceptional leadership abilities.

Nice to Have:

• Certified Scrum Master (CSM)
• PMI-ACP
• SAFe Agilist
• PMP Certification
• Azure Solutions Architect Certification
• AWS Solutions Architect Certification
• Experience with Kubernetes or OpenShift
• Experience with Kafka, Event Streaming, or Messaging Platforms
• Knowledge of Vector Databases, MCP (Model Context Protocol), AI Agents, and Prompt Engineering
• Experience in Aviation, Travel, Retail, Banking, or other large enterprise domains

What Success Looks Like:

• Successfully delivers enterprise-scale technical and AI transformation programs.
• Enables engineering teams to deliver high-quality software with predictable timelines.
• Drives adoption of cloud-native architectures and modern engineering practices.
• Bridges business goals with technology execution while fostering a culture of innovation and continuous improvement.
• Champions Agile delivery, engineering excellence, and AI-driven transformation across the organization.