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.
- Strong 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.
