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Solution Architecture Platforms Manager Jobs

7,291 active opportunities · Updated for October 2026

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Explore current solution architecture platforms manager jobs. Use filters to narrow by work mode, employment type, experience and date posted.

As an Enterprise Customer Success Manager, you will proactively drive new product attachment and effective strong relationships across our largest and most strategic customers. You’ll advocate for the customer internally and focus on a positive customer experience. Interactions are rooted in relationship-management, first and foremost, while also advocating for growth opportunities. Enterprise Customer Success Managers follow a well-defined methodology that helps them identify the customer's unique needs and clearly convey the value of the Datadog product. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Partner with Enterprise Account Executive and Solution Engineering teams to onboard, train, and proactively drive adoption with our Enterprise customers Proactively build relationships with customers to achieve loyalty and advocacy within their organization Collaborate cross-functionally with internal Datadog teams (sales, support, enablement, product, finance, and legal) Own and project manage the on-boarding process for new customers Become a trusted advisor to the client and partner in building a clear and concise plan to meet their business goals Monitor and analyze usage trends to uncover renewal risks and identify opportunity for contract growth/optimization With demonstrated understanding of observability and security platforms, align customers technical and business objectives to our platform offerings Who You Are: Customer-centric with 3+ years in a Customer Success or Account Management role Able to manage a wide portfolio of accounts rolling up to large enterprise corporate accounts Knowledgeable in working with Fortune 1000 companies and global brands across all industries A strong communicator with exceptional attention to detail

aigorust
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OpenAI
📍 New York• Full-time• Remote
1mo ago

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). About the role We are hiring a Forward Deployed Engineer (FDE) to build and deploy AI systems for legal work. You will embed deeply with customers—often working closely with senior legal practitioners—to identify the right first use case, rapidly prototype a solution, and prove measurable value. Early engagements may focus on creating a “hero” workflow that shows how OpenAI’s models can support legal analysis, drafting, research, or real-time work with complex case records. You will own the technical work from discovery and proof of concept through production adoption, while translating customer workflows and constraints into clear product feedback. As the motion matures, you will turn successful deployments into repeatable patterns that can scale across larger accounts and the broader legal market. This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance. Travel up to 50% may be required. In this role, you will Embed with law firms and legal teams to understand their workflows, identify high-value opportunities, and select the right initial use cases to prove value. Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks t

REMOTEjavascriptpythonjava
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O
OpenAI
📍 New York• Full-time• Remote
1mo ago

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). About the role We are hiring a Forward Deployed Engineer (FDE) to build and deploy AI systems for legal work. You will embed deeply with customers—often working closely with senior legal practitioners—to identify the right first use case, rapidly prototype a solution, and prove measurable value. Early engagements may focus on creating a “hero” workflow that shows how OpenAI’s models can support legal analysis, drafting, research, or real-time work with complex case records. You will own the technical work from discovery and proof of concept through production adoption, while translating customer workflows and constraints into clear product feedback. As the motion matures, you will turn successful deployments into repeatable patterns that can scale across larger accounts and the broader legal market. This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance. Travel up to 50% may be required. In this role, you will Embed with law firms and legal teams to understand their workflows, identify high-value opportunities, and select the right initial use cases to prove value. Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks t

REMOTEjavascriptpythonjava
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