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Field Engineer
Field EngineerArdentis AI • NA, NY, us
Field Engineer

Field Engineer

Ardentis AI • NA, NY, us
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Job Description

This is a remote position.

Location : Remote US / Canada (Must be able to work EST timezone)

Core focus : Field engineering, solution delivery, platform deployment, managed services, enterprise AI / automation enablement.

About us

Are you ready to help shape the future? Our company is building the next generation of AI solutions, and we’re looking for bold, curious minds who want to make an impact. We aren’t just following trends — we’re creating them. As a growing firm dedicated to the implementation of modern, leading-edge artificial intelligence, we offer a place where your ideas matter, your expertise is valued, and your work creates real change for real people.

You will join a small but fast-moving, collaborative team that thrives on innovation. Every project is an opportunity to explore new technologies, learn rapidly, and build new skills. We encourage creative thinking, strategic problem solving, and hands-on involvement at every level. You’ll have the freedom and support to push boundaries and build something extraordinary.

We are looking for a Field Engineer who can lead delivery for enterprise clients, ensuring their environments are live, reliable, and scaling on top of our AI and automation solutions. You will own hands-on implementation and integration work, partner closely with the Head of Field Engineering, and collaborate with both the CTO (technical standards and solution readiness) and COO (delivery quality and scale) to make sure every client engagement is executed smoothly end to end.

Requirements

What You’ll Do

Implementation & integration

Stand up production environments for the platform.

Configure identity (SAML / OIDC / SCIM), networking (VPCs, peering, VPN, private connectivity), data pipelines, and event streams (Kafka / Kinesis / Pub / Sub).

Solution buildouts

Design and deliver workflows, connectors, and APIs (REST / GraphQL).

Define data mappings, transformations, and robust error-handling patterns.

IaC and releases

Ship repeatable deployments using Terraform and Helm.

Contribute to “golden path” modules, runbooks, and checklists.

Plan and execute cutovers and rollbacks.

Observability and reliability

Instrument services with metrics, logs, and traces.

Define SLOs, set up alerting and dashboards, and drive hypercare after go-live.

Participate in incident response and postmortems.

Security and compliance

Run enterprise security reviews (data residency, encryption, RBAC / least privilege).

Produce customer-facing security and compliance artefacts.

Customer leadership

Lead technical workshops, UAT, performance / load testing, and go-live activities.

Triage issues with clear root cause analysis and actionable remediation plans.

Targeted presales support

Occasionally support scoped demos, POCs, and implementation estimates.

Feedback to product

Feed deployment learnings into product roadmap, architecture, and documentation.

Focus on improving time-to-value, on-time go-lives, SLO / SLA adherence, and CSAT.

What You Bring

5–10 years in field / solutions / implementation engineering for B2B platforms (ideally data / AI / automation).

Hands-on experience with at least two major clouds (AWS / GCP / Azure), plus Kubernetes, Terraform, and containerized deployments.

Strong integration experience with REST / GraphQL APIs, webhooks, event streams, and secure secrets / config management.

Practical experience with SAML / OIDC / SCIM and cloud networking : VPC design, peering, VPN, private connectivity, and firewall policies.

Observability mindset with metrics / logs / traces (e.g. Prometheus, Grafana, OpenTelemetry) and SLO-driven operations.

Proficiency in Python and / or TypeScript / Node.js for automation, tooling, and integration glue.

Comfortable working with PostgreSQL and event-driven patterns for reliable data flows.

Excellent customer-facing communication, clear documentation, and calm execution during cutovers and escalations.

Bonus : exposure to LLM / RAG pipelines, vector databases, and production MLOps.

Benefits

Why Join

Define the standards, tooling, and team that make AI work at scale for large customers.

Work from zero-to-one and then scale globally.

Join a culture of innovation with strong engineering, product, and sales partners.

How to Apply

If you’re excited to design and lead a implementation —apply via LinkedIn.

Requirements

What You’ll Do Implementation & integration Stand up production environments for the platform. Configure identity (SAML / OIDC / SCIM), networking (VPCs, peering, VPN, private connectivity), data pipelines, and event streams (Kafka / Kinesis / Pub / Sub). Solution buildouts Design and deliver workflows, connectors, and APIs (REST / GraphQL). Define data mappings, transformations, and robust error-handling patterns. IaC and releases Ship repeatable deployments using Terraform and Helm. Contribute to “golden path” modules, runbooks, and checklists. Plan and execute cutovers and rollbacks. Observability and reliability Instrument services with metrics, logs, and traces. Define SLOs, set up alerting and dashboards, and drive hypercare after go-live. Participate in incident response and postmortems. Security and compliance Run enterprise security reviews (data residency, encryption, RBAC / least privilege). Produce customer-facing security and compliance artefacts. Customer leadership Lead technical workshops, UAT, performance / load testing, and go-live activities. Triage issues with clear root cause analysis and actionable remediation plans. Targeted presales support Occasionally support scoped demos, POCs, and implementation estimates. Feedback to product Feed deployment learnings into product roadmap, architecture, and documentation. Focus on improving time-to-value, on-time go-lives, SLO / SLA adherence, and CSAT. What You Bring 5–10 years in field / solutions / implementation engineering for B2B platforms (ideally data / AI / automation). Hands-on experience with at least two major clouds (AWS / GCP / Azure), plus Kubernetes, Terraform, and containerized deployments. Strong integration experience with REST / GraphQL APIs, webhooks, event streams, and secure secrets / config management. Practical experience with SAML / OIDC / SCIM and cloud networking : VPC design, peering, VPN, private connectivity, and firewall policies. Observability mindset with metrics / logs / traces (e.g. Prometheus, Grafana, OpenTelemetry) and SLO-driven operations. Proficiency in Python and / or TypeScript / Node.js for automation, tooling, and integration glue. Comfortable working with PostgreSQL and event-driven patterns for reliable data flows. Excellent customer-facing communication, clear documentation, and calm execution during cutovers and escalations. Bonus : exposure to LLM / RAG pipelines, vector databases, and production MLOps.

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