Full Stack Architect - Agentic AI at Relanto

Job description

7+ Years Fremont, CA, USA Full-Time Responsibilities: • • Architect and deliver end-to-end AI-powered solutions for high-tech clients using GCP-native components and Agentic AI frameworks. • Design scalable backend services using Python (FastAPI, Flask, or Django) and integrate them with LLMs and autonomous agent frameworks (LangChain, AutoGen, CrewAI). • Define solution architectures leveraging GCP services such as Vertex AI, BigQuery, Cloud Functions, Pub/Sub, Cloud Run, and Firestore. • Lead the design and implementation of frontend applications using React, Angular, or Vue, ensuring seamless UX/UI integration with AI capabilities. • Collaborate with clients, product managers, and engineering teams to capture business requirements and convert them into technical roadmaps. • Drive technical workshops, POCs, and architectural reviews focused on AI/ML and cloud transformation strategies. • Implement and optimize vector database integrations (e.g., Pinecone, Weaviate, FAISS) and embedding pipelines on GCP. • Define and enforce best practices in cloud-native DevOps, microservices, and CI/CD automation using GCP tools like Cloud Build, Artifact Registry, and Cloud Monitoring. • Provide architectural guidance and mentorship to distributed engineering teams following Agile delivery models. Required Skills: • • 10+ years of experience in full stack architecture and software engineering, ideally in high-tech product or platform environments. • Strong hands-on experience with Python backend frameworks (FastAPI, Flask, Django). • Proficient in frontend development using Angular with a solid understanding of UX patterns. • Hands-on experience with Agentic AI frameworks such as LangChain, AutoGen, or CrewAI. • Deep knowledge of LLM APIs (OpenAI, Claude, Gemini, Mistral) and prompt engineering strategies. • Solid experience with GCP services including Vertex AI, BigQuery, Pub/Sub, Cloud Storage, Cloud Functions, and Cloud Run. • Familiarity with vector databases and retrieval-augmented generation (RAG) pipelines. • Expertise in REST, GraphQL, microservices architecture, and API gateways. • Proficient in Docker, Kubernetes (GKE preferred), and CI/CD pipelines using Cloud Build or equivalent. • Strong communication skills and ability to engage with both technical and business stakeholders. • Experience working with Agile methodologies and distributed delivery teams. Preferred skills: • • GCP Certification (e.g., Professional Cloud Architect, Professional Data Engineer) is a strong plus. • Experience in CI/CD implementation on DevOps platforms (e.g., GitLab CI/CD, Cloud Build, Jenkins, or GitHub Actions). • Familiarity with multi-cloud deployments (AWS, Azure) in addition to GCP. Required Skills AI/ML GenAI Apply for this job Share with someone awesome View all job openings

Requirements

Must-haves

Fremont, CA, USA
Architect and deliver end-to-end AI-powered solutions for high-tech clients using GCP-native components and Agentic AI frameworks.
Design scalable backend services using Python (FastAPI, Flask, or Django) and integrate them with LLMs and autonomous agent frameworks (LangChain, AutoGen, CrewAI).
Define solution architectures leveraging GCP services such as Vertex AI, BigQuery, Cloud Functions, Pub/Sub, Cloud Run, and Firestore.
Lead the design and implementation of frontend applications using React, Angular, or Vue, ensuring seamless UX/UI integration with AI capabilities.
Collaborate with clients, product managers, and engineering teams to capture business requirements and convert them into technical roadmaps.
Drive technical workshops, POCs, and architectural reviews focused on AI/ML and cloud transformation strategies.
Implement and optimize vector database integrations (e.g., Pinecone, Weaviate, FAISS) and embedding pipelines on GCP.
Define and enforce best practices in cloud-native DevOps, microservices, and CI/CD automation using GCP tools like Cloud Build, Artifact Registry, and Cloud Monitoring.
Provide architectural guidance and mentorship to distributed engineering teams following Agile delivery models.
10+ years of experience in full stack architecture and software engineering, ideally in high-tech product or platform environments.
Strong hands-on experience with Python backend frameworks (FastAPI, Flask, Django).
Proficient in frontend development using Angular with a solid understanding of UX patterns.
Hands-on experience with Agentic AI frameworks such as LangChain, AutoGen, or CrewAI.
Deep knowledge of LLM APIs (OpenAI, Claude, Gemini, Mistral) and prompt engineering strategies.
Solid experience with GCP services including Vertex AI, BigQuery, Pub/Sub, Cloud Storage, Cloud Functions, and Cloud Run.
Familiarity with vector databases and retrieval-augmented generation (RAG) pipelines.
Expertise in REST, GraphQL, microservices architecture, and API gateways.
Strong communication skills and ability to engage with both technical and business stakeholders.
Experience working with Agile methodologies and distributed delivery teams.

Nice-to-haves

Proficient in Docker, Kubernetes (GKE preferred), and CI/CD pipelines using Cloud Build or equivalent.
GCP Certification (e.g., Professional Cloud Architect, Professional Data Engineer) is a strong plus.
Experience in CI/CD implementation on DevOps platforms (e.g., GitLab CI/CD, Cloud Build, Jenkins, or GitHub Actions).
Familiarity with multi-cloud deployments (AWS, Azure) in addition to GCP.

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Keywords to mirror

aigcppythonreactangularvuemlci/cdagilellmrestgraphqlapidockerkubernetesawsazure

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