Product Manager

Short Description for Internal Candidates

We are looking for a technically strong Manager - AI Product Experience to own the design and delivery of AI-powered product features for the Accounts Receivable and Order-to-Cash domain. The role combines hands-on AI engineering capability with product management ownership, requiring the incumbent to work closely with data scientists, software engineers, and Finance stakeholders to ship intelligent AR automation that reduces DSO, improves cash application accuracy, and enhances collections intelligence.

KEY RESPONSIBILITIES

Product Design & AI Strategy

• Define and manage the AI product roadmap for AR capabilities: cash application automation, deductions management, credit risk scoring, collections prioritization, and dispute resolution.
• Translate AR business requirements into AI architectures, orchestration frameworks, and product features that deliver measurable outcomes (DSO reduction, auto-match rate improvement).
• Design Generative AI solutions using state-of-the-art models (GPT-4o, Claude, Llama 3) for AR-specific tasks: automated remittance parsing, dispute email generation, and intelligent customer communication.
• Architect Agentic AI workflows for autonomous AR operations: cash matching agents, dispute classification agents, and collections prioritization agents using LangChain, AutoGen, and CrewAI.

Technical Leadership

• Guide data science and ML engineering teams in building, fine-tuning, and deploying LLMs and ML models for AR use cases: payment prediction, credit risk scoring, and anomaly detection.
• Architect scalable AI pipelines on cloud platforms (AWS, Azure, GCP); drive adoption of LLM orchestration stacks and MLOps practices for production AR AI systems.
• Stay current on advancements in Generative AI, NLP, and ML engineering frameworks (PyTorch, TensorFlow, LangChain, LlamaIndex, LangGraph); proactively incorporate innovations into the AR AI product.
• Ensure AI solutions meet compliance, security, and auditability standards applicable to receivables and financial data.

Client Engagement

• Collaborate with client Finance technology teams and AR operations leads to identify AI-driven automation opportunities and co-define solution requirements.
• Present Generative AI use cases, proof-of-concept demos, and ROI narratives to both technical and non-technical client audiences.
• Act as a trusted product and AI advisor to clients on the technical, ethical, and operational considerations of deploying AR AI solutions.
• Support Sr. AVP in first-engagement solutioning, client workshops, and RFP/RFI responses for AR transformation engagements.

Product Management & Delivery

• Write detailed Product Requirement Documents (PRDs), user stories, and acceptance criteria for AI-powered AR features; manage and prioritize the product backlog.
• Conduct user discovery interviews with AR operations teams, controllers, and treasury leads to surface pain points and validate product hypotheses.
• Lead sprint planning, grooming, and retrospectives with cross-functional Agile engineering teams; manage release readiness across QA, UX, and compliance workstreams.
• Define and track product metrics: cash application hit rate, auto-match accuracy, DSO improvement, collector productivity, and AI model performance.
• Author product collateral: demo scripts, solution one-pagers, sales enablement decks, and ROI calculators for AR AI solutions.

QUALIFICATIONS

Education & Experience (9-12 Years)

• B.Tech or M.Tech in Computer Science, Software Engineering, Data Science, or a related technical discipline.
• 9-12 years of total experience, with at least 4-5 years in AI/ML product engineering and 3+ years of Finance technology experience with strong AR/O2C domain exposure.
• 3-4 years of hands-on experience with Generative AI and Large Language Models: prompt engineering, LLM fine-tuning, and building applications using LangChain, LlamaIndex, or RAGAS.
• Hands-on experience with deep learning frameworks (PyTorch, TensorFlow) and applying ML models to finance classification, prediction, and anomaly detection use cases.
• Working experience with Agentic AI concepts: Autonomous Agents, AutoGen, CrewAI, LangGraph; ability to design and deploy multi-step AI agent workflows for AR automation.
• Experience in ML Engineering and MLOps: model deployment, performance monitoring, versioning, and retraining pipelines (MLflow, SageMaker, Azure ML).
• Strong software engineering skills in Python; experience building AI-powered APIs, integrations, and cloud-native microservices.
• Proven track record of delivering AI product features from ideation through production deployment in an Agile environment; CSPO or equivalent certification preferred.

Skills & Competencies

• Solid functional knowledge of Accounts Receivable: cash application, collections, credit management, deductions, billing, and ERP AR modules (SAP FSCM, Oracle Fusion AR, HighRadius, Esker).
• Experience with NLP techniques for remittance advice parsing, dispute letter classification, and payment confirmation extraction from unstructured documents.
• Understanding of Vector Databases and Graph Databases and their application in AR knowledge retrieval, semantic matching, and customer intelligence.
• Familiarity with cloud AI services (AWS Bedrock, Azure OpenAI, GCP Vertex AI) for both model inferencing and fine-tuning AR-specific models.
• Strong SQL and Python proficiency; experience with BI/analytics tools (Tableau, Power BI) for data-driven product and model performance decisions.
• Excellent communication skills: ability to explain Generative AI concepts and product value to non-technical Finance audiences.
• Experience working cross-functionally across engineering, data science, UX, and Finance SME teams; comfortable managing competing priorities in a fast-paced product environment.
• Participation in RFI/RFP, thought leadership, and client-facing solutioning activities preferred.

Short Description for Internal Candidates

We are looking for a technically strong Manager - AI Product Experience to own the design and delivery of AI-powered product features for the Accounts Receivable and Order-to-Cash domain. The role combines hands-on AI engineering capability with product management ownership, requiring the incumbent to work closely with data scientists, software engineers, and Finance stakeholders to ship intelligent AR automation that reduces DSO, improves cash application accuracy, and enhances collections intelligence.

KEY RESPONSIBILITIES

Product Design & AI Strategy

• Define and manage the AI product roadmap for AR capabilities: cash application automation, deductions management, credit risk scoring, collections prioritization, and dispute resolution.
• Translate AR business requirements into AI architectures, orchestration frameworks, and product features that deliver measurable outcomes (DSO reduction, auto-match rate improvement).
• Design Generative AI solutions using state-of-the-art models (GPT-4o, Claude, Llama 3) for AR-specific tasks: automated remittance parsing, dispute email generation, and intelligent customer communication.
• Architect Agentic AI workflows for autonomous AR operations: cash matching agents, dispute classification agents, and collections prioritization agents using LangChain, AutoGen, and CrewAI.

Technical Leadership

• Guide data science and ML engineering teams in building, fine-tuning, and deploying LLMs and ML models for AR use cases: payment prediction, credit risk scoring, and anomaly detection.
• Architect scalable AI pipelines on cloud platforms (AWS, Azure, GCP); drive adoption of LLM orchestration stacks and MLOps practices for production AR AI systems.
• Stay current on advancements in Generative AI, NLP, and ML engineering frameworks (PyTorch, TensorFlow, LangChain, LlamaIndex, LangGraph); proactively incorporate innovations into the AR AI product.
• Ensure AI solutions meet compliance, security, and auditability standards applicable to receivables and financial data.

Client Engagement

• Collaborate with client Finance technology teams and AR operations leads to identify AI-driven automation opportunities and co-define solution requirements.
• Present Generative AI use cases, proof-of-concept demos, and ROI narratives to both technical and non-technical client audiences.
• Act as a trusted product and AI advisor to clients on the technical, ethical, and operational considerations of deploying AR AI solutions.
• Support Sr. AVP in first-engagement solutioning, client workshops, and RFP/RFI responses for AR transformation engagements.

Product Management & Delivery

• Write detailed Product Requirement Documents (PRDs), user stories, and acceptance criteria for AI-powered AR features; manage and prioritize the product backlog.
• Conduct user discovery interviews with AR operations teams, controllers, and treasury leads to surface pain points and validate product hypotheses.
• Lead sprint planning, grooming, and retrospectives with cross-functional Agile engineering teams; manage release readiness across QA, UX, and compliance workstreams.
• Define and track product metrics: cash application hit rate, auto-match accuracy, DSO improvement, collector productivity, and AI model performance.
• Author product collateral: demo scripts, solution one-pagers, sales enablement decks, and ROI calculators for AR AI solutions.

QUALIFICATIONS

Education & Experience (9-12 Years)

• B.Tech or M.Tech in Computer Science, Software Engineering, Data Science, or a related technical discipline.
• 9-12 years of total experience, with at least 4-5 years in AI/ML product engineering and 3+ years of Finance technology experience with strong AR/O2C domain exposure.
• 3-4 years of hands-on experience with Generative AI and Large Language Models: prompt engineering, LLM fine-tuning, and building applications using LangChain, LlamaIndex, or RAGAS.
• Hands-on experience with deep learning frameworks (PyTorch, TensorFlow) and applying ML models to finance classification, prediction, and anomaly detection use cases.
• Working experience with Agentic AI concepts: Autonomous Agents, AutoGen, CrewAI, LangGraph; ability to design and deploy multi-step AI agent workflows for AR automation.
• Experience in ML Engineering and MLOps: model deployment, performance monitoring, versioning, and retraining pipelines (MLflow, SageMaker, Azure ML).
• Strong software engineering skills in Python; experience building AI-powered APIs, integrations, and cloud-native microservices.
• Proven track record of delivering AI product features from ideation through production deployment in an Agile environment; CSPO or equivalent certification preferred.

Skills & Competencies

• Solid functional knowledge of Accounts Receivable: cash application, collections, credit management, deductions, billing, and ERP AR modules (SAP FSCM, Oracle Fusion AR, HighRadius, Esker).
• Experience with NLP techniques for remittance advice parsing, dispute letter classification, and payment confirmation extraction from unstructured documents.
• Understanding of Vector Databases and Graph Databases and their application in AR knowledge retrieval, semantic matching, and customer intelligence.
• Familiarity with cloud AI services (AWS Bedrock, Azure OpenAI, GCP Vertex AI) for both model inferencing and fine-tuning AR-specific models.
• Strong SQL and Python proficiency; experience with BI/analytics tools (Tableau, Power BI) for data-driven product and model performance decisions.
• Excellent communication skills: ability to explain Generative AI concepts and product value to non-technical Finance audiences.
• Experience working cross-functionally across engineering, data science, UX, and Finance SME teams; comfortable managing competing priorities in a fast-paced product environment.
• Participation in RFI/RFP, thought leadership, and client-facing solutioning activities preferred.

Bachelor's/Master's