Product Delivery Manager-AI II
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Job Location:
Monthly Salary:
Posted on:
6 days ago
Vacancies:
1 Vacancy
Job Summary
Role Overview:
Build agentic workflows that automate real user tasks endtoend. Design and orchestrate AI
agents that reliably execute workflows. Solid ML foundations who thrive in a fastmoving
PMFstage environment.
Key Responsibilities
Build agentic workflows that automate real user tasks endtoend. Design and orchestrate AI
agents that reliably execute workflows. Solid ML foundations who thrive in a fastmoving
PMFstage environment.
Key Responsibilities
Agentic automation: Build & deploy AI agents for user task automation and integrate with ecosystem.
LLM workflows: Implement pipelines using LangChain/LlamaIndex; leverage vectorgraph DBs and embeddingbased retrieval.
Workflow design: Utilize LangGraph CodeDB and vector search systems for orchestration.
Cloud operations: Deploy and optimize on AWS AZURE.
Model evaluation: Trial new capabilities; choose models; optimize latency/cost; harden pipelines.
Collaboration: Translate user needs and effectively turn into automated experiences.
Reliability & safety: Ensure accuracy observability and guardrails across AI features.
LLM workflows: Implement pipelines using LangChain/LlamaIndex; leverage vectorgraph DBs and embeddingbased retrieval.
Workflow design: Utilize LangGraph CodeDB and vector search systems for orchestration.
Cloud operations: Deploy and optimize on AWS AZURE.
Model evaluation: Trial new capabilities; choose models; optimize latency/cost; harden pipelines.
Collaboration: Translate user needs and effectively turn into automated experiences.
Reliability & safety: Ensure accuracy observability and guardrails across AI features.
Requirements
Experience: 3 5 years in software or applied AI engineering.
Core skills: Python (strong) ML foundations agent/agentic workflow experience orchestration & tool use.
Backend: Familiar with and react ecosystem
Data: PostgreSQL MYSQL ; vector DBs (e.g. Pinecone/Qdrant).
LLM stack: LangChain/LlamaIndex; flexibility across LLMs (GPT SonnetLLaMA 3.1 etc.).
Cloud: AWS/AZURE deployment and ops.
Mindset: Adaptable handson fast iteration; experience in B2B/B2C product teams.
Core skills: Python (strong) ML foundations agent/agentic workflow experience orchestration & tool use.
Backend: Familiar with and react ecosystem
Data: PostgreSQL MYSQL ; vector DBs (e.g. Pinecone/Qdrant).
LLM stack: LangChain/LlamaIndex; flexibility across LLMs (GPT SonnetLLaMA 3.1 etc.).
Cloud: AWS/AZURE deployment and ops.
Mindset: Adaptable handson fast iteration; experience in B2B/B2C product teams.
Impact:
This role drives innovation by embedding AI into enablement workflows reducing manual effort and enhancing learner experience through intelligent automation.
