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We are seeking an experienced Senior Data Product Manager to own the strategic direction, scaling, and optimization of AI and data platform. This is a high-impact leadership role where youll define the long-term vision, shape platform-wide data standards, and ensure our data products deliver measurable business value at scale.
As the strategic owner of core data capabilities, youll work closely with executives, enterprise customers, and multi-disciplinary teams to deliver intelligent, self-optimizing workflows that transform how global organizations operate. Youll operate at the highest level of product influence, driving roadmaps, aligning with corporate OKRs, and mentoring other PMs.
Key Responsibilities:
Define and execute a strategic and execution plan for data and AI platform, ensuring alignment with executive priorities and market opportunities.
Lead platform-wide architecture, governance, and interoperability standards for data models, pipelines, and integrations.
Act as the primary product voice for AI/data strategy in executive discussions, client C-level meetings, and partner engagements.
Collaborate directly with clients to ensure onboarding success, define business success metrics, and rollout milestones.
Mentor other PMs, fostering a culture of customer obsession, technical excellence, and measurable impact.
Partner with Engineering, Data Science, and Solution Engineering teams to design data models, pipelines, schemas, and enrichment flows across a wide range of external data inputs (APIs, unstructured formats, operational feeds).
Establish frameworks for data quality, observability, and self-healing ingestion across distributed, multi-vendor systems.
Conduct deep market research and competitive analysis to guide investment decisions and identify emerging opportunities.
Drive platform-wide data consistency by introducing standards for cross-source schema design, entity resolution, and joinability.
Conduct market analysis, user interviews, and internal research to identify product gaps, edge cases, and scalability challenges.
Build internal tooling and dashboards to surface model performance, user adoption, and operational bottlenecks.
Use SQL and Python for hypothesis validation, data exploration, and rapid prototyping to support discovery and iteration.

We are looking for a Product Manager - AI.
What You Will Do
Define success metrics: Define and implement KPIs to track progress toward desired outcomes.
Represent the voice of the customer in the design, AI research, and development processes, with a deep understanding of users mindset, needs, and pain points.
Deliver AI-enabled experiences to transform how procurement and finance teams work.
Partner cross-functionally to ensure that product improvements realize their full potential and impact.
Use data to inform decisions: Collaborate with data scientists and analysts to transform raw data into insights and high impact decisions.

we are looking for a AI Product Lead.
Responsibilities:
Build roadmap for AI tools within our product offering that transform how dairy farmers work.
Dive deep into discovery: Talk to farmers, understand their reality, get obsessed with identifying the big problems.
Build roadmap for internal AI tools that change the way we work as a company; Champion AI adoption internally and externally - make it accessible, valuable, and exciting.
Balance quick wins with long-term bets for high impact, lead rapid POC to Production cycles and deliver measurable impact.

We are seeking a highly skilled Gen AI software engineer to design, develop, and deploy state-of-the-art, scalable, efficient Gen AI solutions. You will be part of a high-performing engineering team that values collaboration, innovation, and teamwork. This role is perfect for someone who thrives in an environment where ideas are shared, challenges are met together, and success is a collective achievement.



Responsibilities

Designed and implemented Gen AI platform components using Python and modern microservices.
Drive engineering and operational excellence and best practices.
Collaborate with tech, product, program, and business peers to deliver customer value and drive product vision.
Drive the end-to-end development of AI systems, from research and experimentation to deployment and scaling
Mentor and support engineers, fostering a culture of collaboration, knowledge-sharing, and continuous learning
Analyze complex problems and identify and define the requirements to solve them.
Apply DevOps principles to maintain high-performance and scalable AI systems.
Design and implement secure APIs, ensuring data protection and safe interaction with AI models.
Stay updated on the latest Gen AI trends and technologies, bringing fresh ideas to the team

Required Al Builder - Performance
About the role (overview)
As part of our Business Technologies & AI organization, youll build and ship AI agents and workflows that drive measurable impact on our internal core business processesand then own their performance over time.
Using our AI Gateway, Custom GPTs, and low-code/no-code tooling, youll orchestrate prebuilt actions, design robust prompts, and wire data flows across systems like Salesforce, Snowflake, Gong, ERP, and internal toolswithout writing low-level API code.
You will also treat AI agents like a real workforce: defining how they are onboarded, measured, evaluated, and improved. Youll build the operating model, metrics, and evaluation solutions that keep our AI ecosystem powerful, safe, and cost-effective.
1) AI Solution Design & Development
Rapidly build, test, and deploy AI agents using the AI Gateway, Custom GPTs, and low/no-code tools.
Design scalable, secure, and reliable workflows with strong prompt patterns, evals, and canary tests.
Define new actions with Platform/Integrations when needed; ensure every agent has clear I/O, purpose, and a KPI.
2) Orchestration, Data, & Operations
Configure and chain actions; handle mapping, preprocessing, errors, retries, and safe context assembly.
Use managed auth/secrets with least-privilege access and data minimization.
Write SQL for retrieval context, routing rules, golden sets, and performance queries.
Integrate logs, BI, and admin tools into a single operational view.
3) Performance, Quality & Evaluation
Define and track core metrics: usage, adoption, accuracy, cost, time saved, revenue impact.
Build dashboards, scorecards, leaderboards, and automated alerts (health, anomalies, regressions).
Maintain evaluation frameworks and pipelines (golden sets, scenarios, automated checks).