Senior Forward Deployed Engineer

About This Opportunity

Our talent team is representing a confidential AI infrastructure client in their search for a Senior Forward Deployed Engineer. This is a customer-facing engineering role where you'll deploy cutting-edge AI capabilities into enterprise production environments, solve real-world reliability challenges, and directly shape product direction based on field insights.

You'll serve as the technical bridge between sophisticated enterprise customers and the engineering organization—implementing AI-powered site reliability tooling, leading platform migrations, and ensuring successful production outcomes in complex, heterogeneous environments.

Responsibilities

• Own enterprise implementations end-to-end—from technical discovery and solution design through production cutover, UAT, go-live, hypercare, and post-launch stabilization
• Deploy and optimize AI-powered site reliability solutions in customer production and pre-production environments
• Lead enterprise migrations from incumbent alerting and AIOps platforms (BigPanda, Moogsoft, PagerDuty, Elastic, Splunk), including replicating hundreds to thousands of existing correlation rules and executing phased cutovers
• Design, build, and tune alert normalization and correlation policies—writing conditions and operators (IN/CONTAINS/REGEX), extracting fields from noisy sources, and choosing tailored playbooks
• Integrate solutions with customer operational stacks—ticketing systems (ServiceNow bi-directional sync and field mapping), collaboration platforms (Microsoft Teams/Slack), observability tools (Dynatrace, Datadog, Prometheus), and knowledge sources
• Stand up proactive health monitoring for customer deployments with real-time status channels and SLA-driven alerts
• Validate and continuously improve investigation quality—diagnosing query-conversion and enrichment errors, unblocking failed investigations, and tuning RCA accuracy
• Own customer-facing communications—weekly executive status updates, SLA documents, escalation paths, and migration tracking
• Build long-term technical relationships with senior engineering leaders at customer organizations
• Translate ambiguous customer requirements into clear technical designs, milestones, trade-offs, and acceptance criteria
• Design and ship AI-powered investigation and remediation workflows with clear guardrails, deterministic fallbacks, and human-in-the-loop controls
• Create reusable deployment modules, reference architectures, runbooks, and cutover plans that accelerate future implementations
• Own the value case: set impact hypotheses, baselines, and KPIs (MTTI/MTTR reduction, toil eliminated), measure outcomes, and report ROI to executive sponsors
• Channel recurring field learnings into roadmap input and product improvements
• Train SRE, Ops, and Platform teams at customer organizations on best practices

What We're Looking For

Required:

• Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience
• 6+ years of experience in Site Reliability Engineering, DevOps, or similar operational role, including technical leadership or end-to-end ownership of customer-facing delivery
• Strong proficiency in at least one programming language (Python, Go, Java)
• Extensive experience with cloud platforms (AWS, GCP, or Azure)
• Solid understanding of Kubernetes, infrastructure as code tools (Terraform, CloudFormation, Ansible), and CI/CD pipelines
• Intimate familiarity with Generative AI and ML concepts—must be actively using AI tools to drive personal productivity
• Strong hands-on experience with observability tools (Dynatrace, Datadog, Prometheus), ITSM/ticketing systems (ServiceNow), and incident management/response systems
• Excellent problem-solving skills to diagnose complex systems systematically, including writing and debugging alert-correlation logic, normalization rules, and regular expressions
• Track record of independently owning enterprise implementations end-to-end—managing timelines, driving customer syncs, producing executive documentation, with minimal execution drift
• Strong integration and data experience: APIs, webhooks, event-driven systems, schema alignment, transformations, reliable error handling, and end-to-end integration configuration
• Hands-on experience designing and delivering production-grade AI/automation workflows with practical guardrails and evaluation approaches
• Comfort with enterprise security and architecture requirements—RBAC, encryption, auditability, private networking, identity
• Calm, high-judgment execution in ambiguous, fast-moving customer environments
• Deep customer empathy and passion to reduce operational toil
• Strong written and verbal communication skills with a collaborative mindset

Bonus:

• Prior experience in technical customer success or forward-deployed/solutions engineering role
• Experience migrating customers off incumbent AIOps, alerting, or incident-management platforms
• Experience with operating/supporting customers running AI infrastructure or AI tools
• Familiarity with marketplace certification processes (ServiceNow Store, Microsoft Teams)
• Experience building internal tooling and automation to accelerate validation, migration, and monitoring

How We Work With You

When you apply through Get A Job.ai, our recruiting team will review your profile and conduct an initial screening. If there's a strong match, we'll submit your candidacy to our client for consideration. Throughout the interview process, we'll provide guidance and support.

Please apply exclusively through Get A Job.ai—do not contact the client directly, as we are managing this search on their behalf.

Pay

Compensation details will be discussed during the screening process and are competitive with senior engineering roles in the AI infrastructure space.

Equal Employment Opportunity: Get A Job.ai is committed to inclusive hiring practices. We welcome applications from candidates of all backgrounds and work with our clients to ensure fair and equitable consideration.