Own the day-to-day delivery and execution of Agentic AI initiatives, ensuring sprint-level progress, quality delivery, and successful deployment of AI solutions into production.
Key Responsibilities
Delivery Execution and Sprint Management
* Manage end-to-end delivery at sprint and release level
* Plan and track sprint backlogs, user stories, and deliverables
* Ensure adherence to timelines, scope, and quality standards
* Monitor team velocity, burndown, and delivery KPIs
Team and Workstream Coordination
* Coordinate across Engineering, development, and architecture teams
* Drive daily stand-ups, sprint planning, reviews, and retrospectives
* Identify and resolve blockers impacting delivery
* Ensure clear task ownership and accountability
Agentic AI Implementation Oversight
* Track development of multi-agent workflows (planner, executor, memory, etc.)
* Ensure delivery of components such as orchestration, APIs, and integrations
* Support testing cycles including functional, integration, and UAT
* Ensure readiness for deployment and release
LLMOps and Release Management
* Ensure implementation of:
o Prompt and model versioning
o Testing and evaluation pipelines
* Support release management across environments (dev/test/prod)
* Track operational metrics such as latency, defect rates, and token usage
Quality and Risk Management
* Ensure adherence to testing standards and acceptance criteria
* Track and mitigate delivery risks and issues
* Ensure compliance with security and governance requirements
Stakeholder Communication
* Provide regular updates on sprint progress and delivery status
* Escalate risks, delays, and dependencies proactively
* Coordinate with business teams during UAT and rollout
Technical Stack
Must Have
* Experience in Agile delivery (Scrum/Kanban) for technology programs
* Exposure to AI/ML or Generative AI project delivery
* Understanding of:
o Agentic AI workflows and LLM-based applications
o API integrations and distributed systems
* Experience with cloud environments (AWS/GCP)
* Strong delivery tracking, reporting, and coordination skills
Good to Have
* Exposure to LangChain, LangGraph, CrewAI, or AutoGen
* Familiarity with LLMOps concepts and tools
* Understanding of RAG pipelines or vector databases
* Experience with Jira, Confluence, or similar tools
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