AI/ML Architect

DevExplore; Fremont (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

DevExplore seeks a senior architect to design and deliver AI-powered, scalable backend and frontend systems on Google Cloud. You will architect end-to-end solutions for high-tech clients, integrating LLMs, agent frameworks, and vector databases.

The role requires hands-on Python expertise, GCP mastery, and leadership across cross-functional teams. You will drive architecture reviews, define roadmaps with clients and PMs, and mentor distributed engineers in Agile delivery.

Qualifications

• 10+ years of experience in full stack architecture and software engineering.
• Strong hands-on experience with Python backend frameworks (FastAPI, Flask, Django).
• 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.

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 and integrate with LLMs and autonomous agent frameworks.
• Define solution architectures leveraging GCP services like Vertex AI, BigQuery, Cloud Functions, Pub/Sub, Cloud Run, and Firestore.
• Lead frontend applications using React, Angular, or Vue with AI capabilities.
• Collaborate with clients, product managers, and engineering teams to capture business requirements and translate into roadmaps.
• Drive technical workshops, POCs, and architectural reviews focused on AI/ML and cloud transformation strategies.
• Implement and optimize vector database integrations and embedding pipelines on GCP.
• Define and enforce best practices in cloud-native DevOps, microservices, and CI/CD with Cloud Build/Artifact Registry/Cloud Monitoring.
• Provide architectural guidance and mentorship to distributed engineering teams following Agile delivery models.

Skills

Python backend frameworks (FastAPI,Fl/

LLM APIs & prompt engineering

GCP Vertex AI

REST & GraphQL

Agile methods

Communication with stakeholders

Distributed delivery teams

Tools

LangChain

AutoGen

CrewAI

Docker

Kubernetes (GKE)

Cloud Build

BigQuery

Cloud Functions/Run

Pinecone/Weaviate/FAISS

Job description

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)
• 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