Fullstack Architect - AI Automation

Responsibilities:

• Own end-to-end architecture for new solutions' data model, services, integrations, UI, AI layer, deployment, and observability.
• Hands-on build of core modules, especially LLM integration, agentic orchestration, workflow engines, and anything novel the team has not built before.
• Lead technical discovery with customers, run whiteboarding sessions, size integrations, and produce target-state architecture decks.
• Deliver technical demos to customers and partners TimeCraft, Fingertips, document tampering detection, binder reconciliation, Kissflow flows, and any new product we launch.
• Run code review, engineering standards, and tech mentorship across the BU's engineers (junior to senior).
• Build reusable skills, prompts, Claude Code plugins, and internal tools that multiply the team's output.
• Own integrations with enterprise platforms Kissflow, Zoho, Salesforce, QuickBooks, SAP, NetSuite, Microsoft Dynamics 365 Power Platform and standardise the integration layer.
• Partner with the BU leader on the technical roadmap: what to build in-house vs. buy, what to productise, and when to deprecate.
• Operate deployed apps on the Pierian App Store (Node/React, PM2/Nginx, centralised SSO) and participate in incident response and post-mortems.
• Contribute to proposals and RFP responses; as the technical authority, you should be able to write the solution architecture section of a 30-page RFP in a few hours.

Requirements:

• 9-11 years of engineering experience, with at least 3 years as a hands-on architect or tech lead on production AI or automation systems.
• Full-stack depth: React/Next.js + Node.js/Express on the front; Python (FastAPI, Pandas, LangChain/LlamaIndex) on the back; SQL + at least one NoSQL store; and one cloud (Azure preferred, AWS acceptable).
• Practical experience shipping LLM-powered features into production, including prompt engineering, RAG pipelines, function/tool calling, evaluation harnesses, and cost/latency trade-offs.
• Hands-on, daily usage of AI coding tools Claude Code, GitHub Copilot, or Cursor with shippable output. You should be able to show a public or internal repo where you used these tools to build something real.
• Strong fundamentals: data structures, system design, API design, authentication (OAuth/SSO/SAML), async processing, and observability.
• Excellent written and spoken communication: able to explain a design to a junior engineer, a CFO, and a vendor partner, all in the same afternoon.
• Disciplined engineering habits, source control hygiene, PR reviews, docs that stay current, and tests that actually run in CI.

Skills

Express, FastAPI, LLM, LangChain, LlamaIndex, Next.js, Node.js, Python, RAG, React, architect, tech lead