Advisory Software Engineer
Pitney Bowes (company site, opens in a new tab)6–8 yrsNoidaOn-siteDirect career pageEst. 20–35 LPA
Posted on 2 Sept
Reach people at Pitney Bowes
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Pitney Bowes you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Own and groom the backlog and delivery cadence for AI agent platform pods, translating ambiguous executive intent into actionable epics and acceptance criteria for probabilistic systems.
- Run efficient scrum ceremonies, track delivery health metrics, remove impediments, and coordinate cross-pod and partner team dependencies to achieve predictable sprint outcomes.
- Provide technical stewardship by partnering on architecture, maintaining AI governance checkpoints, managing platform economics, and running time-boxed POCs with clear decisions.
Minimum Requirements
- 6-8 years of relevant work experience in technical product ownership, program management, or engineering delivery leadership with at least 2 years owning a backlog.
- Experience delivering AI/ML or LLM-based features to production, not just prototypes or pilots.
- Role location: Pune or Noida with 3 days per week mandatory onsite work.
- Experience with managed agent platforms (e.g., Amazon Bedrock/AgentCore) and AI governance processes is preferred but not strictly mandatory.
Ideal Candidate Profile
- Experienced in managing complex AI systems involving probabilistic outputs, agent orchestration, and integration with core product APIs.
- Comfortable working hands-on in sprint planning, writing detailed acceptance criteria, and resolving delivery friction in distributed, multi-timezone agile teams.
- Strong API literacy and experience with AI application patterns (RAG, tool calling, evaluation frameworks), plus ability to communicate clearly to executives through documentation and reporting.