What are the responsibilities and job description for the AI/ML Architect position at DevExplore?
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
- 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