Field Engineer

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🕒 November 27, 2025

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Ardentis AI

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2025

🤖 Artificial Intelligence

🏦 Banking

💳 Fintech

Artificial Intelligence • Banking • Fintech

Ardentis AI is a specialist AI engineering and delivery firm that helps investment banks and capital markets organizations deploy production-grade AI systems safely, credibly, and at scale. They embed experienced engineers, delivery leaders, and capital markets specialists into client programs to build explainable, auditable AI solutions for regulated environments, focusing on use cases like client onboarding, post-trade workflows, regulatory change, and reporting. Ardentis also modernizes data platforms and governance—covering ingestion, classification, quality, and lineage—so AI use cases move from experiments into stable, supported production with appropriate oversight and accountability.

📋 Description

• 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.

🎯 Requirements

• 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

• 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.