A productized deployment service that helps enterprise teams identify, scope, and ship the first practical AI workflows inside their existing operations.
Added Jun 28, 2026
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Medium opportunity
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Enterprise buyers are struggling to turn AI platform interest into deployed workflows that work inside real operational constraints. Vendors are hiring solutions engineers, account directors, and forward-deployed engineers because customers need someone to understand their business processes, qualify the right use cases, and bridge the gap between platform capability and production deployment. The pain is not generic AI education; it is the messy implementation work between buyer intent and a working internal workflow.
Offer a fixed-scope AI deployment sprint for enterprise teams adopting tools like Devin, Handshake AI, permitting platforms, or internal AI agents. The service embeds with one customer team, maps current workflows, ranks feasible use cases, designs the deployment plan, builds lightweight integrations or prototypes, and hands off an operating playbook. Over time, the repeatable artifacts become templates for discovery, workflow mapping, technical scoping, integration checklists, and deployment governance.
AI vendors are moving from demos to enterprise deployment, and job signals show they need customer-facing technical operators who can make deployments practical. Buyers want outcomes, but internal teams often lack the cross-functional implementation capacity.
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The AI Deployment team is the tip of the spear in getting Altana's platform into production inside our customers' businesses. We own the path from signed contract to realized value: standing up integrations, deploying agentic AI into the customer's existing business processes, and making sure the insight we deliver actually changes decisions on the customer's side.
We are looking for a Forward Deployed AI Engineer to design and deploy AI solutions for enterprise customers. You will work directly with customers to understand their workflows, translate business
Partner with R&D, design, and data science to scope, prioritize, and ship features that surface and reduce AI token waste. Work directly with enterprise customers and prospects to understand how they deploy AI agents in production and where their cost and visibility gaps are.
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