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As an Implementation Engineer, you’ll lead the technical delivery of Proscia’s platform to customers across on-premise, SaaS, and cloud environments—handling installation, migration, and advisory services from kickoff to go-live. You’ll work across teams (Professional Services, Sales, Product, Engineering) and directly with customers throughout EMEA. AI tools are a natural part of how you navigate unfamiliar integration landscapes, validate your work, and solve problems that don’t come with a playbook. This role is for a technologist obsessed with positive customer outcomes.
Job Responsibility:
Own the end-to-end technical delivery of customer deployments—from planning through installation, integration, and validation—using AI to accelerate your work through unfamiliar territory and to catch issues before the customer does
Partner with Solution Architects to translate architecture and design into validated technical configurations—prototyping and testing with AI and other tools to ensure accuracy before deployment
Drive implementations to customer acceptance—owning quality, managing expectations, and ensuring the delivered solution meets the standard both you and the customer expect
Configuring our customer’s technical specifications, integration requirements, and interface preferences during customer implementations
Resolve technical issues during installation—you’re resourceful, whether that means deep-diving into logs, reaching for AI to accelerate your analysis, or bridging context between teams
Collaborating with product and engineering teams to provide further support and advance feature requests
Reviewing customer feedback, compiling and analyzing data, and recommending technical changes as appropriate
Help build and maintain internal deployment standards and documentation that work for both humans and AI-augmented workflows—because the quality of what AI can do for the next deployment starts with the quality of context from the last one
Requirements:
Experience with Linux (RHEL, CentOS, or Ubuntu) and Windows operating systems, including running scripts and commands in a shell environment
Working knowledge of web-based application architecture and related networking—SSL certificates, DNS, and how they interact in customer environments
Working knowledge of AWS and Azure infrastructure (EC2, S3, RDS, and equivalents)—enough to configure and troubleshoot in customer environments
Experience with storage solutions such as Azure Blob, AWS S3, NFS, etc
Experience with running containerized applications using Docker or Kubernetes
At least 5+ years of experience in enterprise IT solutions
A technical leader who is constantly looking for ways to improve
Strong communicator comfortable speaking with our customers
Strong business acumen with an ability to identify and articulate key value to customers
Comfortable presenting to a range of stakeholders from engineers and architects to IT managers and CIOs
Ability to run several projects in parallel and with a passion to work in a scale-up environment
You already use AI tools in your technical work—for troubleshooting, navigating unfamiliar systems, validating configurations, or however it fits your practice. This isn’t a future aspiration
it’s how we expect our implementation engineers to operate
Experience building with or on top of LLMs, AI agents, or agentic pipelines—or demonstrated hands-on fluency applying AI tools to real technical problems beyond basic code completion
Familiarity with prompt engineering, tool use patterns, and evaluation of AI systems—you know when AI output is ready to use and when it needs different guardrails
Fluent in English
Nice to have:
Experience in healthcare, regulated industries, or mission-critical systems where failure has real consequences
Background that spans multiple domains or disciplines—you’ve reinvented yourself before
Open-source contributions, side projects, or a portfolio that shows how you think and build
Active in technical communities, forums, or meetups—you stay close to where the field is moving