Senior Full Stack & GenAI Developer

Key Responsibilities

• Partner directly with business stakeholders to translate functional requirements into technical designs, system architectures, and data flow diagrams — without hand-holding.
• Rapidly prototype proof-of-concepts to validate feasibility, demonstrate value, and accelerate stakeholder buy-in.
• Own the end-to-end codebase: backend services, frontend interfaces, APIs, Terraform IaC, and deployment pipelines.
• Design and optimize data-heavy applications that handle large-scale datasets with low latency and high reliability.
• Leverage GenAI-assisted coding tools and agentic frameworks to accelerate development velocity while maintaining code quality and best practices.
• Architect and build multi-agent systems — designing agent roles, tool integrations, orchestration patterns, and memory strategies using frameworks such as Google ADK, LangGraph, or CrewAI.
• Navigate and execute enterprise production readiness processes including IT/application standards, ServiceNow change records, and coordination across infrastructure, security, and platform teams.

Required Technical Skills

• Languages & Frameworks: Python (advanced) — Flask, FastAPI; JavaScript/TypeScript — React, Next.js, modern frontend frameworks; HTML5, CSS3, Tailwind CSS or equivalent utility-first CSS frameworks; RESTful API design.
• Cloud & Infrastructure: Cloud Run, Cloud Functions; BigQuery for large-scale analytics; Cloud SQL (PostgreSQL), Cloud Storage; Cloud IAM, VPC, networking fundamentals; Gemini, Google ADK, APIGEE; Infrastructure as Code & DevOps: Terraform for provisioning and managing cloud infrastructure; GitLab repositories, branching strategies, and CI/CD pipelines; Container orchestration, deployment automation, and environment promotion workflows.
• Data & Performance: SQL proficiency across large-scale analytical and transactional databases; Data pipeline design and optimization; caching strategies, async processing, and query tuning.
• AI & GenAI: Strong understanding of LLMs, prompt engineering, and retrieval-augmented generation (RAG); Hands-on experience with agentic AI frameworks — Google ADK, LangGraph, CrewAI, or equivalent; Multi-agent orchestration: designing, deploying, and managing systems where specialized agents collaborate to complete complex tasks; Experience integrating GenAI capabilities via Vertex AI, OpenAI APIs, or similar platforms; Actively uses AI-assisted development tools (e.g., Google Code Assist, Claude Code, GitHub Copilot) as part of daily workflow; Stays current with the rapidly evolving AI landscape; Evaluates and adopts new frameworks and patterns as they emerge.
• Enterprise Operations: Active Directory group management and RBAC patterns; SSO and Okta integration for federated identity; ServiceNow — submitting change requests, service requests, and coordinating approvals for production deployments; Comfortable navigating enterprise change management, production governance, and release coordination processes.