Senior Full-Stack AI Engineer

In order to proceed further, Please take the test.

Test link : test

Senior Full-Stack AI Engineer

Title :

Senior Full-Stack AI Engineer – AI-Enabled Help Desk (GCP)

Location : Remote

This test is mandatory as part of this role. Please share a working public URL.

Responsibilities

Own architecture and implementation of a

RAG-based AI Help Desk backend :

Ingestion + indexing of KB docs (markdown / HTML / PDF)

Chat API with conversation history, role context, and tier classification

Guardrails (prompt injection / adversarial prompt detection)

Ticket creation + escalation logic & tier routing

Replace existing

front-end mock AI simulator

with real backend APIs in the provided repo (pcte-ai-help-desk-demo).

Implement analytics & monitoring endpoints to power the

Help Desk dashboard and trend analysis

(ticket topics, deflection rate, SLA metrics, guardrail activations, etc.).

Design and implement

secure, scalable deployment

on GCP (Cloud Run, Cloud SQL / Firestore, Cloud Storage, etc.).

Apply

best practices :

Clean architecture, separation of concerns

API versioning and documentation (OpenAPI / Swagger)

Automated tests (unit + at least one end-to-end)

Observability (structured logging, basic tracing / metrics)

Secure secrets management and least-privilege IAM

Produce clear

technical documentation

(architecture, APIs, deployment instructions).

Prepare a short

demo walkthrough

aligned with Army use-cases : Tier 0 self-service, guardrails, escalation, human takeover.

Required Skills

6+ years as a

full-stack engineer

building production web apps and APIs.

Strong experience with :

React + Vite + MUI

(the existing UI stack)

Node.js / TypeScript

or

Python

for backend services

Designing RESTful APIs and integrating them with front ends

Hands-on experience with

RAG / LLM-powered applications :

Embeddings, vector search, grounding answers in KB

Handling hallucinations with retrieval + guardrails

GCP

experience with at least some of :

Cloud Run or GKE

Cloud SQL / Firestore / AlloyDB (or Postgres with pgvector)

Cloud Storage / Cloud Build / Artifact Registry

Solid background in

system design & scalability :

Stateless services

Horizontal scaling

Caching & rate limiting

Strong focus on

security & compliance :

Familiarity with concepts from NIST 800-53 / FedRAMP / CUI environments