Role overview
**Job Title: Google AI Full Stack Developer**
**Location: Hartford, CT**
**Employment type : 6 months Contract To Hire**
We are seeking a highly skilled
**Google AI Full Stack Developer**
to design, build, and deploy
**AI-driven applications**
using the
**Google Cloud AI ecosystem**
, including
**Vertex AI**
,
**Gemini models**
, and
**Generative AI Studio**
. The ideal candidate will have end-to-end expertise across
**frontend development**
,
**backend integration**
, and
**AI/ML pipeline implementation**
within the Google Cloud Platform (GCP) environment.
This role blends
**software engineering**
,
**AI integration**
, and
**cloud architecture**
— ideal for developers passionate about building intelligent, scalable, and secure AI solutions.
**Key Responsibilities**
**AI & Generative AI Development**
* Design and implement
**AI-powered full-stack applications**
using
**Google Vertex AI**
,
**Generative AI Studio**
, and
**Gemini APIs**
.
* Integrate
**LLM (Large Language Model)**
and
**multimodal AI**
capabilities into business workflows and user-facing apps.
* Build
**Retrieval-Augmented Generation (RAG)**
and
**chatbot applications**
with Google
**Vertex AI Search**
and
**Embeddings API**
.
**Frontend Development**
* Build responsive, user-centric interfaces using
**ReactJS**
,
**Angular**
, or
**Vue.js**
, integrated with AI backend APIs.
* Develop interactive dashboards, chatbot UIs, and visualization tools for AI insights.
* Ensure performance optimization, accessibility, and secure frontend data handling.
**Backend Development**
* Design and implement secure APIs and microservices using
**Python (FastAPI/Flask)**
,
**Node.js**
, or
**Go**
.
* Integrate with
**Google Cloud Functions**
,
**Cloud Run**
,
**BigQuery**
, and
**Vertex AI endpoints**
for data and model access.
* Manage user sessions, authentication, and API rate control using
**Google Identity**
and
**IAM policies**
.
**Cloud & MLOps Integration**
* Develop and deploy ML workflows using
**Vertex AI Pipelines**
and
**GCP AI Infrastructure**
.
* Automate builds and deployments with
**Cloud Build**
,
**Terraform**
, or
**GitHub Actions**
.
* Collaborate with Data Scientists and ML Engineers to operationalize and monitor models.
* Optimize AI workloads for cost, scalability, and latency in production.
**Security & Governance**
* Implement
**RBAC**
,
**API Gateway**
, and
**secure data handling**
practices.
* Ensure compliance with
**enterprise and cloud security standards**
(IAM, VPC, data encryption).
* Maintain code quality through testing, reviews, and vulnerability scanning.
**Required Skills & Qualifications**
* 5+ years of experience in
**full-stack application development**
.
* 2+ years of hands-on experience with
**Google Cloud AI**
— especially
**Vertex AI**
,
**Gemini API**
, or
**Generative AI Studio**
.
* Strong proficiency in
**ReactJS**
,
**Node.js**
, and
**Python**
(or equivalent backend language).
* Solid understanding of
**RESTful APIs**
,
**microservices architecture**
, and
**event-driven systems**
.
* Experience deploying applications with
**Docker**
and
**Kubernetes**
.
* Familiarity with
**MLOps**
concepts,
**AI model lifecycle management**
, and
**data engineering**
practices.
* Experience with
**BigQuery**
,
**Cloud Storage**
, and
**Pub/Sub**
for data flow and analytics.
**Preferred Qualifications**
* Certifications in
**Google Cloud Professional Developer**
,
**AI Engineer**
, or
**Data Engineer**
.
* Experience implementing
**Generative AI**
,
**chatbots**
, or
**RAG pipelines**
in production.
* Knowledge of
**LangChain**
,
**Vector Databases**
(like Pinecone or FAISS), and
**custom embedding models**
.
* Familiarity with
**CI/CD**
,
**DevSecOps**
, and
**cloud observability tools**
(Stackdriver, Prometheus).
* Exposure to other cloud AI platforms such as
**AWS Bedrock**
,
**Azure OpenAI**
, or
**IBM WatsonX**
.