Principal Engineer & Architect - AI Agent Plaform
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 4d ago
The date the source published, not the day we noticed it (2026-10-06). Last seen at its source 2h ago.
We have tracked this listing since 7 Oct 2026 (4 days). The employer's own board has carried it every time we have read it, most recently 2 hours ago.
Is it remote?
The listing says yes
The location field doesn't say remote, so our assessment is based on the title or the description. Read the listing before applying.
Who may apply?
LATAM
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $6,500–7,250/mo
Middle 50% of 29 listings that do state pay — Engineering · Senior · LATAM · USD/month. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Ashby employer's own board first seen 4d ago · last seen 2h ago
The listing
About DevSavant
DevSavant builds and operates managed AI agents / AI coworkers that run real business workflows in production for SaaS companies. We are turning that service into a scalable product: connecting client systems, normalizing their data, and running agent-driven workflows with human approval, dashboards, and full auditability.
Role Overview
You will be the senior-most engineer on the platform and its technical architect. You will design the integrations, data layers, APIs, infrastructure, security model, and the AI agents themselves. You present those designs to the Director of Engineering for sign-off, and then own building and shipping them alongside a distributed team of senior engineers.
How authority works here: you architect and propose, the Director of Engineering signs off on the direction, and you own execution, technical standards, and team direction from there. This is a hands-on architectural and technical leadership role. You will be writing code on the hard parts of the system, not managing HR functions or line-by-line supervision.
You will start by owning the architecture for the core platform (Managed AI Agents). As we expand into new business modules (Company Brain), you will take ownership of their technical architecture too, stepping in across projects to guide distributed engineering teams based on business priorities.
Responsibilities
Whole-Platform Architecture: Design how client systems connect, how data is normalized and stored, how information is served to dashboards and AI agents, and how new client tools get integrated efficiently. You will be hands-on, building the primary framework skeletons yourself.
Production AI Agent Systems: Handle agent design, tool usage, guardrails, evaluations, and monitoring for agents executing business workflows with human oversight.
Cloud & Infrastructure Direction: Lead deployment architecture, CI/CD, observability, and cost management. The platform runs on containerized infrastructure today; deciding where the runtime should live long-term is one of your first major projects.
Security & Multi-Tenant Architecture: Own tenant isolation, secrets management, least-privilege access, and audit trails for a platform handling financial data. You define the standards, and the team implements them.
Technical Leadership: Set code standards, conduct reviews, and guide a distributed bench of senior engineers through clear written specifications.
Client Engagement: Serve as the technical point of contact with clients and design partners when complex architectural discussions require it.
Requirements
8+ years of production software experience, including recent hands-on ownership of a major system's architecture.
Modern Tech Stack Expertise: Deep experience in TypeScript and Node.js ecosystems, modern frontends (React, Remix / React Router v8, Tailwind, ShadCN), relational ORMs (Drizzle), validation tools (Zod), databases (PostgreSQL, Redis), and queueing systems (PgBoss).
Production LLM Agent Systems: Proven track record shipping and operating real LLM agent systems, not just prototypes. You have built guardrails, evaluated agents prior to launch, monitored them in production, and handled agent-specific failure modes like loops, silent stalls, context drift, and tool misuse.
RAG & Engineering Depth: Deep understanding of RAG pipelines, chunking strategies, and vector data workflows.
Production Infrastructure Ownership: Experience managing uptime, running CI/CD, setting up observability, and handling production incidents end to end.
Cloud Architecture (AWS or GCP): Proven experience making and defending decisions around platform hosting and runtimes.
Production API Integrations: Experience with complex third-party API environments involving webhooks, incremental polling, idempotency, retries, data
normalization, and data reconciliation.
Data Modeling: Strong experience with relational and event-driven data designs where data accuracy is the priority.
Multi-Tenant SaaS Security: Practical experience with tenant isolation, secrets hygiene, least-privilege access control, and audit logs.
Written-First Leadership: Ability to write clear, complete technical specifications that allow remote engineering teams to execute high-quality work asynchronously.
Communication: Excellent written and spoken English and Spanish.
Nice-to-haves
Official AWS or GCP Cloud Architect certifications.
Experience with agent frameworks beyond single-vendor stacks (such as OpenClaw, MCP, or A2A).
Experience with Infrastructure as Code and observability tools like Prometheus or Grafana.
Background in graph databases and knowledge graphs.
Early-stage startup experience building new product lines from 0→1.