Technical Solutions Architect - Backend

Technical Architect Location: Coimbatore Experience: 10+ Years Notice: Immediate Joiner The Mission: Simplifying Bookkeeping with AI FluxBooks is an AI-powered bookkeeping workspace that helps CPAs and bookkeepers turn raw bank, credit card, and loan transactions into clean, categorized, and document-backed records ready for QuickBooks and reconciliation. By bringing statement review, document matching, categorization, client clarification, and transaction posting into a single workflow, FluxBooks eliminates the need to switch between spreadsheets, emails, receipts, and accounting software. Rather than replacing accounting judgment, FluxBooks reduces the manual effort involved in collecting documents, matching transactions, and identifying exceptions, enabling professionals to review and reconcile books faster and with greater confidence. Core Responsibilities • Architecture & System Design: Own the end-to-end design of backend systems and APIs from data ingestion and processing to service deployment and performance optimization. Architect scalable microservices, event-driven workflows, and reusable platform components across client domains. Define enterprise standards for API design, caching strategies, service communication patterns, and integration pipelines. • DevOps & Production Deployment: Establish repeatable patterns for deploying Node.js, Java, and Python services in production. Drive automation through CI/CD pipelines using Jenkins, GitHub Actions, and Terraform. Architect for multi-cloud scalability across Azure, AWS, and GCP. Build strategic PoCs to validate technical fitment and translate business problems into working software systems. • Governance, Security & Compliance: Define and enforce AI architecture principles, security policies, and responsible AI guardrails. Implement controls for PII/PHI protection, hallucination risk mitigation, audit logging, and model explainability. Apply zero-trust principles private networking, API gateways, and identity management to keep data within secure perimeters. • Collaboration & Technical Leadership: Partner with frontend, cloud, security, and product teams for end-to-end architectural alignment. Lead build-vs-buy assessments for platforms, databases, and DevOps tooling. Mentor engineers, conduct architecture reviews, and track the evolving technology landscape to recommend timely adoption of emerging frameworks and tools. Technical & Professional Qualifications • Technical Architecture Experience: 10 years in software engineering or platform architecture, with at least 8 years of hands-on experience designing and delivering scalable systems using Node.js, Java, and Python. • Node.js & Java Expertise: Deep hands-on experience with Node.js frameworks (Express, NestJS) and Java ecosystems (Spring Boot, Microservices), with a proven ability to architect and deploy high-performance backend systems at scale. • Python & Engineering Depth: Strong command of Python for backend services, automation, and data processing. Proficient with Docker, Kubernetes, and distributed systems design across Azure, AWS, and GCP. • Database & Storage Proficiency: Hands-on experience with relational databases (PostgreSQL, MySQL), NoSQL (MongoDB, DynamoDB, Redis), and search engines (Elasticsearch), with strong understanding of data modeling and query optimization strategies. • Analytical Thinking: Ability to evaluate technology trade-offs, define solution design strategies, and translate complex business problems into scalable technical architectures. • Governance & Security Knowledge: Strong grasp of data governance, PII/PHI handling, OAuth 2.0, zero-trust architecture, and responsible AI frameworks applicable to enterprise environments. • Soft Skills: Exceptional ability to communicate architectural decisions to both technical teams and business stakeholders, with a focus on clarity, pragmatism, and long-term system thinking. Tech Stack • Backend Languages & Runtimes: LangChain/LangGraph, OpenAI/Anthropic APIs, Pydantic AI, Langfuse (observability), and VectorDB (Pinecone/Chroma). • Deep Learning & Research Stack: REST, GraphQL, gRPC, Swagger/OpenAPI, Kafka, RabbitMQ, WebSockets. • Enterprise Production Stack: Python, TensorFlow/Keras, Docker, Kubernetes, AWS SageMaker/Vertex AI. • Data & Analytics Stack: Apache Spark (Databricks), Pandas, SQL, Kafk