Top Tech Jobs & Startup Jobs

Design, build, and maintain full-stack applications integrating AI features. Implement React front-ends, Python/FastAPI back-ends, manage Firestore/Cloud SQL, deploy on GCP, collaborate via GitHub, and follow CI/CD and testing best practices.

Design, develop, and maintain backend services with Python and FastAPI; build automated test frameworks and perform QA; integrate with GCP (Cloud SQL, Firestore); use GitHub workflows; conduct code reviews, documentation, and participate in Agile processes.

Lead client-facing delivery of AI-first, full-stack products from discovery to production. Architect and build LLM-powered systems, manage scope and risks, embed with client teams, drive adoption, and mentor engineers while applying AI-native workflows, prompt engineering, and Gen-e2 methodology.

Design and build AI-augmented prototypes and production software. Architect scalable solutions, write and review code, conduct accessibility/performance/security audits, use AI coding assistants and prompt-engineering, collaborate with clients and R&D, and stay current with AI development practices.

Lead design and delivery of scalable AI-driven applications on GCP. Architect systems, integrate AI agents, implement Firestore/Cloud SQL databases, mentor engineers, run architectural and code reviews, and collaborate with product stakeholders to define roadmaps and technical requirements.

Lead discovery workshops, elicit and document business, functional and non-functional requirements, map and re-engineer processes, create user stories and acceptance criteria, manage product backlogs and requirements delivery across SDLC, collaborate with cross-functional teams, validate AI-generated artefacts, and support stakeholder alignment and client relationships.

Lead AI-native full‑stack development using AI-augmented practices, implement DevOps CI/CD pipelines, ensure code quality via testing and AI-assisted reviews, design scalable secure solutions, validate and control GenAI outputs, mentor teams, and drive Gen-E2 methodology adoption to accelerate delivery.

Lead design, evolution, and governance of enterprise data architecture. Define data models, integration patterns (batch and real-time), and technology choices. Drive metadata management, lineage, data quality, privacy, and adoption of cataloging tools. Collaborate with engineering, analytics, and business teams to translate requirements into scalable cloud data solutions and promote standards, best practices, and AI-native development.

Develop robust backend services and Web APIs in C#/.NET (8/10), implement secure authentication (JWT/OAuth2), build cloud-native solutions on Azure (Web Apps, Functions), instrument Application Insights, automate CI/CD (Azure DevOps/GitHub Actions), manage IaC (Bicep/Terraform/ARM), and apply generative AI tooling and prompt-engineering for development productivity.

Design, build, and maintain production-grade full‑stack applications using modern frameworks. Implement CI/CD and testing, ensure code quality and security, and use generative AI tools (e.g., Copilot) and prompt engineering as core parts of the development workflow. Validate AI outputs, collaborate with product teams, and contribute to internal Gen-E2 practices and playbooks.