Technical Architect

We are looking for a highly experienced Technical Architect to provide technical leadership for our Core Platform & Automation teams. This role is central to driving cloud architecture, platform modernization, the adoption of AI-driven product capabilities, and the embedding of industry best practices across our B2B SaaS platform, raising engineering excellence, product reliability, and long-term scalability.

The ideal candidate brings deep expertise in cloud-native architecture, distributed systems, enterprise SaaS, and data-intensive applications, combined with strong platform thinking. You will work closely with Product Management, Engineering Managers, Leads, TPMs, QA, DevOps, and leadership to shape the long-term technical direction of the platform.

This role requires a strong balance of hands-on technical depth, architectural leadership, mentoring capability, execution ownership, and cross-functional collaboration.

Key Responsibilities :

Cloud Architecture & Technical Leadership :

- Define and drive the long-term cloud architecture vision and roadmap for the Infinx Core Platform & Automation Products.

- Design highly scalable, secure, multi-tenant SaaS systems on the cloud (AWS) capable of handling high transaction volumes and rapid customer growth.

- Drive adoption of microservices, event-driven architecture, API-first design, and cloud-native development practices.

- Establish engineering standards, architectural guidelines, and reusable reference architectures across teams.

- Review system designs, architecture proposals, and critical implementation decisions.

- Proactively identify and address architectural bottlenecks, performance issues, and technical debt.

Platform Modernization :

- Lead modernization initiatives spanning scalability, resiliency, observability, security, and maintainability.

- Re-architect legacy components toward cloud-native, containerized, and serverless patterns.

- Drive decomposition and cloud migration strategies (e.g., monolith-to-microservices) with minimal disruption.

- Lead cloud cost optimization (FinOps) and platform efficiency initiatives.

AI-Driven Product Innovation :

- Partner with Product and Data teams to design and embed AI/ML-driven capabilities into the platform.

- Define architecture patterns for integrating LLMs, ML models, and intelligent automation into product workflows.

- Drive adoption of AI-assisted engineering practices to accelerate delivery and improve developer productivity.

- Evaluate and recommend emerging AI frameworks, tooling, and other solutions.

Engineering Excellence & Industry Best Practices :

- Bring industry best practices to product development across the full software delivery lifecycle.

- Improve platform reliability, performance, availability, and operational stability.

- Drive engineering quality initiatives such as automated testing, code quality, secure coding (OWASP), and CI/CD maturity.

- Champion observability practices including logging, monitoring, tracing, and alerting.

- Improve developer productivity through reusable frameworks, tooling, standards, and automation.

- Partner with QA and DevOps to strengthen release engineering and production readiness.

Product & Business Collaboration :

- Work closely with Product Management and business stakeholders to translate business needs into scalable technical solutions.

- Participate in roadmap planning, technical estimation, risk identification, and prioritization.

- Balance short-term delivery goals with long-term platform sustainability.

- Support customer escalations and critical production issue resolution when required.

Mentorship & Team Development:

- Mentor Technical Leads and engineers across teams.

- Raise the technical bar through architecture reviews, design discussions, and engineering coaching.

- Drive a culture of ownership, innovation, operational excellence, and continuous learning.

- Build strong engineering depth across backend, frontend, platform, and data engineering functions.

Required Skills & Qualifications :

Technical Skills :

- 13+ years in product engineering, with strong experience designing and building scalable enterprise SaaS platforms.

- Strong expertise in Java and Spring Boot based enterprise application development.

- Deep understanding of distributed systems, scalable architectures, and cloud-native design principles.

- Proven experience designing and building microservices-based platforms.

- Strong experience with REST APIs, asynchronous messaging, and event-driven systems; Kafka or other streaming/event platforms.

- Hands-on experience with relational and NoSQL databases such as PostgreSQL, MongoDB, and Redis.

- Strong understanding of performance tuning, scalability, caching, and resiliency patterns.

- Hands-on experience with AWS services such as EC2, ECS/EKS, S3, RDS, Lambda, CloudWatch, and IAM.

- Strong understanding of software security best practices and OWASP guidelines.

AI & Data Engineering :

- Experience integrating AI/ML or LLM-driven capabilities into products.

- Familiarity with AI-assisted development tooling and related concepts.

- Hands-on experience in data engineering technologies such as SQL, Apache Spark, Apache Flink, or equivalent frameworks.

- Understanding of data lakes, lakehouse architectures, batch processing, and stream processing.

Leadership & Execution :

- Proven experience leading large-scale product engineering initiatives.

- Strong architectural decision-making and problem-solving skills.

- Ability to influence teams across organizational boundaries.

- Excellent communication and stakeholder management skills.

- Experience working in Agile/Scrum product engineering environments.

- Ability to operate effectively in fast-paced and evolving product environments.

Preferred Qualifications :

- Exposure to AI/ML-driven product capabilities or AI-assisted software development.

- Experience building highly configurable enterprise workflow platforms.

- Experience with data engineering, analytics, or reporting platforms (Lakehouse / Warehouse / Databricks / QuickSight / Power BI).

- Cloud certifications (e.g., AWS Solutions Architect - Professional).

Skills

Technical Architect, Distributed Systems, SaaS, AWS, Java, Spring Boot, REST API, Microservices Architecture, Kafka, RDBMS, PostgreSQL