10+ years in full stack architecture and software engineering, particularly in high-tech environments.
Strong experience with Python backend frameworks (FastAPI, Flask, Django).
Proficient in frontend development using Angular and understanding of UX patterns.
Hands-on experience with Agentic AI frameworks like LangChain, AutoGen, or CrewAI.
Deep understanding of LLM APIs (OpenAI, Claude, Gemini, Mistral) and prompt engineering strategies.
Solid experience with GCP services including Vertex AI, BigQuery, and Cloud Functions.
Expertise in microservices architecture, REST, GraphQL, and API gateways.
Responsibilities
Architect and deliver AI solutions using GCP-native components and Agentic AI frameworks.
Design scalable backend services and integrate with LLMs and autonomous agent frameworks.
Define solution architectures leveraging GCP services like Vertex AI and BigQuery.
Lead frontend application design using React, Angular, or Vue with AI integration.
Collaborate with clients and teams to translate business requirements into technical roadmaps.
Drive technical workshops and architectural reviews focused on AI/ML strategies.
Implement and optimize vector database integrations and embedding pipelines on GCP.
Benefits
Opportunity to work on cutting-edge AI technologies with high-tech clients.
Strong emphasis on professional development and mentorship.
Flexible work environment with Agile delivery models.
Involvement in collaborative workshops and innovation-driven projects.
Full 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).
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.
