Full Stack Engineer

OVERVIEW

Seeking a hands-on Full Stack Engineer to design, build, and deliver production-grade platform services for an AI-native enterprise

system. This role sits at the intersection of frontend engineering, backend services, and agentic AI platforms—supporting AI agents and Lang Graph orchestration workflows across the full stack, while ensuring scalable, secure, and observable systems in a cloud-

native environment.

RESPONSIBILITIES

Full Stack Development Backend & API Engineering

• Build modern frontend apps (React or Angular,

TypeScript, component architecture)

• Develop backend services and APIs using Python

(FastAPI preferred)

• Implement secure REST APIs and real-time

communication (WebSockets/streaming)

• Ensure clean separation of concerns across

frontend, API, and data layers

• Build layered backend architectures using FastAPI and dependency

injection

• Implement asynchronous data access patterns and high-performance APIs

• Define API contracts, validation models (Pydantic), and error handling

standards

• Implement authentication and authorization using JWT, OAuth, IAM

Agentic AI Platform Integration Cloud-Native Development

• Build backend services as tools and APIs for

AI agent workflows

• Design APIs providing structured, deterministic

data to LLM orchestration layers

• Support Human-in-the-Loop (HITL): approvals,

callbacks, state management

• Integrate with tool-calling frameworks and external

AI orchestration systems

• Enable agent observability via structured logging,

tracing, and correlation IDs

Frontend Engineering

• Build responsive, accessible UI components

• Implement state management (Redux Toolkit,

Zustand, NgRx, etc.)

• Integrate APIs, handle auth flows, and optimize

performance

• Write unit and integration tests (Jest, React Testing

Library, Angular equivalents)

• Build and deploy services on GCP (preferred), AWS, or Azure

• Implement event-driven architectures (Pub/Sub, messaging systems)

• Work with managed services for compute, storage, and data processing

• Ensure secure configuration, secret management, and scalable deployments

Data Layer & Integration

• Design and implement data access across:

• Relational databases (PostgreSQL / AlloyDB)

• Graph database (Spanner), NoSQL (Firestore)

• Caching (Redis) and analytics (BigQuery)

• Integrate with enterprise systems (SAP, Microsoft Graph, internal APIs)

• Build resilient integrations with retry, timeout, and fault handling

Scope & Expectations

• 100% hands-on engineering role (no people management)

• Collaborate closely with AI/ML engineers on agent workflows

• Participate in design discussions, code reviews, and architecture decisions

• Deliver production-quality, scalable, and maintainable systems

Testing & Quality Engineering

• Write comprehensive tests (pytest, pytest-

asyncio, Jest)

• Cover edge cases, failure scenarios, and

asynchronous workflows

• Follow best practices for code quality,

observability, and maintainability

SKILLS & EXPERIENCE

Required

• 8+ years of full stack software engineering experience

• Strong frontend experience with React or Angular (TypeScript)

• Solid backend development with Python (FastAPI, Flask, or Django)

• Production-grade APIs, microservices, and distributed systems

• Agentic AI concepts: LangGraph, LangChain, tool-calling workflows

• REST APIs, async programming, relational and graph databases

• Hands-on with at least one major cloud provider (GCP preferred)

• Strong testing practices and Git-based workflows

Preferred

• LangGraph or similar agent orchestration frameworks

• Human-in-the-Loop (HITL) workflow patterns

• Model Context Protocol (MCP) or tool integration patterns

• Real-time systems (WebSockets, streaming architectures)

• GCP services: Firestore, Pub/Sub, BigQuery, Cloud Run

• Distributed caching and concurrency patterns (Redis)