Forward Deployed Engineer, Relyance AI

As a Forward Deployed Engineer (FDE) at Relyance AI, you partner closely with prospects and customers to translate real-world privacy, security, and AI governance challenges into working solutions on the Relyance platform. You help prospects understand how Relyance will operate in their environment and then work hands-on throughout the customer journey to deploy solutions, drive value realization, and expand adoption across their organization.

FDEs play a critical role across the customer journey—from early discovery and solution design through implementation, enablement, and ongoing adoption—ensuring organizations achieve measurable outcomes with Relyance.

This role is ideal for someone who enjoys jumping into complex customer environments, figuring out how things actually work, and designing practical solutions that make real systems and processes run better.

What You’ll Do:

• Run deep, structured discovery with customer stakeholders (Security/Privacy/Data/Engineering): listen hard, ask incisive follow-ups, uncover root causes, and translate pain into clear outcomes and an actionable technical plan leveraging the Relyance AI platform.
• Own the technical solution end-to-end—from architecture and integration design through implementation—making pragmatic tradeoffs that balance speed, security, and long-term maintainability.
• Implement and ship: configure the platform, stand up integrations, validate outcomes, troubleshoot in real time, and deliver working deployments (not just recommendations).
• Build reusable technical assets that accelerate success: repeatable rollout playbooks, runbooks, reference architectures, automation/scripts, validation checklists, and “starter” templates that customers can adopt and scale.
• Partner with the Value Realization team to drive measurable outcomes and adoption by helping define success metrics, establishing technical baselines, and delivering technical enablement (workshops, working sessions, office hours) that turn platform capabilities into sustained usage.
• Serve as the technical lead for your accounts, partnering with Sales and the Value Realization team to ensure successful deployments, strong technical adoption, and opportunities to expand platform usage.
• Shape product direction with concrete customer evidence: synthesize discovery patterns, propose product gaps and solutions, and work closely with Product/Engineering—especially with early adopters—to refine product fit.
• Communicate with clarity and precision: concise updates, strong stakeholder management, and crisp articulation of risks, timelines, and tradeoffs for both technical and non-technical audiences.

Must have skills:

• Deep discovery leadership: Ability to run structured discovery, listen for the real problem, ask sharp follow-ups, map stakeholders, and translate customer pain into clear outcomes + a concrete technical plan.
• Hands-on solution delivery: Proven ability to design, implement, and validate solutions — from integration planning through deployment and post-go-live optimization.
• Customer-facing technical + account ownership: Experience owning technical relationships and outcomes in roles like Solutions Engineer, Solutions Architect, TAM, Implementation Lead, Support/Systems Engineer, etc.—comfortable being the technical owner for an account.
• Cloud deployment experience: Hands-on experience designing and deploying solutions in AWS, GCP, or Azure (architecture, services, permissions, networking basics, operational considerations).
• Strong data ecosystem understanding: Working knowledge of modern data landscapes—sources, pipelines, storage/warehouses/lakes, data movement, observability, and how tools connect across teams.
• Integration and troubleshooting proficiency: Comfortable with APIs (REST), auth patterns (OAuth/SSO concepts), logs/debugging, and integration validation tools (e.g., Postman). Bonus if you can script/automate and reason about data (SQL).
• AI-powered building mindset: Proficiency in leveraging AI tools to build—prototypes, automations, accelerators, internal utilities, and customer-facing workflows/demos that speed delivery.
• High ownership + detail orientation: Strong accountability, follow-through, and operational rigor—able to run multiple workstreams, track risks, and deliver reliably.
• Clear communication for mixed audiences: Ability to explain complex technical concepts to both technical and non-technical stakeholders; strong stakeholder management and crisp written updates.
• Early-product / GTM maturity: Comfort working with new or emerging products—guiding early adopters, creating repeatable playbooks, and shaping product fit via structured feedback to Product/Engineering.

Our Culture:

At Relyance AI, we pride ourselves on fostering an unreasonably hospitable and data-driven culture. We are dedicated to exceeding customer and team expectations in every interaction. This means empowering our team members to proactively solve problems with informed decisions, crafting personalized experiences, and radiating enthusiasm. We believe in trust and freedom, enabling creative solutions, while a shared purpose and recognition fuel a drive for greatness. We deconstruct failures to learn and grow, and we celebrate our successes with pride.

Relyance AI is an equal-opportunity employer. We celebrate representation and are committed to creating an inclusive environment for all employees. Our compensation practices are fair and equitable, driven by data to ensure our offerings are competitive and our team members are compensated correctly based on their roles, experience, and location. As such, the On-Target Earnings (OTE) for this role are expected to be between $220,000 and $250,000, which includes a base salary and variable compensation.