About MADTECH.AI

MADTECH.AI is a next-generation Marketing Decision Intelligence Platform that enables enterprises to unify marketing, media, customer, and business data into actionable insights. Our cloud-native B2B SaaS platform leverages AI, advanced analytics, automation, and scalable data engineering to help global organizations make faster, data-driven decisions.

We are looking for a highly experienced Technical Architect to lead the architecture and technical direction of our platform. This role is ideal for a hands-on technology leader who enjoys solving complex engineering challenges, mentoring teams, and building scalable cloud-native products.

Key Responsibilities

Platform Architecture

- Define and own the overall technical architecture for MADTECH.AI's cloud-native multi-tenant SaaS platform. Design scalable, secure, resilient, and highly available distributed systems capable of supporting enterprise workloads.

- Architect multi-tenant solutions with tenant isolation, role-based access control (RBAC), feature management, licensing, subscription management, and usage metering.

- Define architecture principles, engineering standards, technical guidelines, design patterns, and best practices.

- Establish architecture governance through Architecture Decision Records (ADRs), design reviews, technical standards, and governance processes.

- Drive technical decision-making and evaluate architectural trade-offs across engineering initiatives.

- Lead technology evaluations and recommend modern technologies aligned with business strategy.

- Drive platform modernization initiatives while reducing technical debt and improving long-term maintainability.

Cloud &

- Infrastructure

- Design and implement enterprise-grade cloud-native architectures on AWS.

- Architect cloud-native applications leveraging services such as: Amazon EKS, EC2, Lambda, API Gateway, S3, RDS, Redshift, DynamoDB, SNS/SQS, EventBridge, CloudFront, WAF, ElastiCache, Secrets, Cognito, CloudWatch, etc.,

- Build highly available, fault-tolerant, disaster recovery-ready architectures across cloud environments.

- Design scalable infrastructure supporting high availability, business continuity, disaster recovery, and automated failover.

- Optimize cloud architecture for scalability, reliability, security, operational excellence, and cost efficiency.

Application Engineering

- Lead architecture and design of modern cloud-native microservices-based applications.

- Define API-first architecture principles and service-oriented design standards.

- Establish engineering standards for Python, React, Node.js, TypeScript, FastAPI, and modern backend technologies.

- Define reusable software architecture patterns, coding standards, and engineering governance.

- Guide engineering teams in building highly maintainable, extensible, testable, and performant applications.

- Establish secure API lifecycle management, versioning, documentation (OpenAPI), OAuth2 authentication, rate limiting, and API governance.

- Drive adoption of Domain-Driven Design (DDD), event-driven architecture, CQRS, and scalable integration patterns where appropriate.

Data Engineering &

- Analytics

- Architect enterprise-scale cloud-native data platforms supporting structured, semi-structured, and unstructured data.

- Design modern Data Lake, Lakehouse, and analytical data warehouse architectures.

- Architect scalable ETL/ELT pipelines, Change Data Capture (CDC), streaming pipelines,



and reverse ETL solutions.

- Design robust enterprise data models optimized for analytics, AI workloads, reporting, and self-service analytics.

- Work with PostgreSQL, Amazon Redshift, Snowflake, NoSQL databases, Redis, and distributed data stores.

- Optimize large-scale analytical workloads for performance, scalability, and cost efficiency.

- Enable high-performance data access supporting AI, reporting, and advanced marketing analytics.

Integration & iPaaS

- Design scalable enterprise integration frameworks using REST APIs, GraphQL, event-driven architectures, messaging systems, and asynchronous processing.

- Build reusable integration services and connectors using iPaaS principles.

- Lead integrations with MarTech, AdTech, CRM, CDP, ERP, and third-party marketing platforms.

- Design secure, scalable, and resilient integration architectures.

- Establish API lifecycle management, integration governance, versioning strategies, and developer standards.

- Design reusable connector frameworks supporting rapid onboarding of new data sources and destinations.

AI &

- Intelligent Automation

- Partner with AI/ML teams to integrate predictive analytics, machine learning, Generative AI, and Agentic AI capabilities throughout the platform.

- Design AI-native application architectures utilizing Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, and intelligent workflows.

- Architect scalable AI orchestration frameworks using technologies such as LangChain, LangGraph, Model Context Protocol (MCP), and modern AI tooling where appropriate.

- Design AI governance frameworks covering model deployment, observability, security, scalability, monitoring, and responsible AI practices.

- Support deployment and lifecycle management of production AI models through scalable MLOps practices.

- Evaluate emerging AI technologies and drive adoption where they create measurable business value.

Security &

- Compliance

- Ensure platform architecture follows Secure-by-Design and Zero Trust principles.

- Design secure authentication, authorization, RBAC, encryption, secrets management, secure API practices, and identity management.

- Implement cloud security best practices across AWS services.

- Collaborate with Security teams to meet SOC 2, ISO 27001, GDPR, and other regulatory compliance requirements.

- Drive threat modeling, vulnerability management, secure SDLC, and security architecture reviews.

- Promote secure coding practices and proactive risk mitigation across engineering teams.

DevOps &

- Engineering Excellence

- Champion CI/CD, Infrastructure as Code (Terraform), automated testing, deployment automation, and release management.

- Collaborate with DevOps teams on Kubernetes, Docker, Helm, GitHub Actions, Jenkins, and modern deployment pipelines.

- Drive Platform Engineering initiatives to improve developer experience through self-service infrastructure, reusable platform components, and internal developer tooling.

- Improve platform observability using OpenTelemetry, distributed tracing, centralized logging, monitoring,



alerting, Grafana, Prometheus, CloudWatch, and New Relic.

- Define Service Level Objectives (SLOs), Service Level Indicators (SLIs), operational metrics, and platform reliability standards.

- Lead architecture reviews, design documentation, performance optimization, capacity planning, and engineering governance.

Leadership

- Provide technical leadership and mentorship to engineering teams, technical leads, and senior engineers.

- Drive architecture strategy and long-term technology roadmap aligned with business objectives.

- Guide solution design, technology selection, and architectural trade-offs.

- Partner closely with Product Management, Engineering Leadership, AI/Data Science, DevOps, Security, and Customer Success teams.

- Participate in product roadmap planning and strategic technology decisions.

- Lead architecture review boards, technical governance forums, and engineering design reviews.

- Mentor engineers on software architecture, cloud-native design, distributed systems, and engineering best practices.

- Represent engineering in executive discussions, customer technical engagements, and strategic architecture planning.

- Foster a culture of innovation, engineering excellence, collaboration, and continuous improvement.

Required Qualifications

- Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline.

- 12 years of software engineering experience, including 5 years in solution/application architecture.

- Proven experience architecting enterprise-scale multi-tenant B2B SaaS platforms.

- Strong experience designing cloud-native applications on AWS.

- Deep understanding of distributed systems, microservices, event-driven architecture, Domain-Driven Design (DDD), and scalable system design.

- Strong programming knowledge in Python and experience with modern frontend technologies such as React.

- Expertise in REST APIs, GraphQL, API Gateway, and integration architecture.

- Experience with SQL, PostgreSQL, Redshift, Snowflake, and NoSQL databases.

- Robust knowledge of ETL/ELT frameworks and large-scale data platforms.

- Experience working with Kubernetes, Docker, and container orchestration.

- Strong understanding of DevOps practices, CI/CD pipelines, and Infrastructure as Code.

- Experience implementing secure application architecture and cloud security best practices.

- Excellent leadership, stakeholder management, communication, and problem-solving skills.

Preferred Qualifications

- AWS Certified Solutions Architect (Professional) or equivalent certification.

- Experience with Marketing Analytics, MarTech, AdTech, Customer Data Platforms (CDPs), or Marketing Mix Modeling (MMM).

- Exposure to AI/ML platforms, LLMs, Generative AI, and MLOps.

- Experience with streaming technologies such as Kafka or Kinesis.

- Familiarity with observability platforms such as Grafana, Prometheus, ELK, or Datadog.

- Experience building multi-tenant SaaS platforms.

- Experience working in Agile/Scrum product organizations.

Why Join MADTECH.AI

- Build a cutting-edge AI-powered Marketing Decision Intelligence platform.

- Solve large-scale data, analytics, and cloud engineering challenges.

- Work alongside experienced AI, Data Science, Product, and Engineering leaders.

- Influence product architecture and technology strategy from the ground up.

- Be part of a fast-growing, innovation-driven global SaaS organization.

📌 Technical Architect (Bengaluru)
🏢 iSOCRATES
📍 Bengaluru