Technical Architect

INFINX

Technical Architect

Experience: 13+ years

• Location: Bengaluru
• Full-time
  
  

Company Overview

Infinx Healthcare is a leading healthcare payment solutions provider specializing in next-generation, cloud-based SaaS

products. Our mission is to maximize and preserve revenue across the US healthcare revenue cycle by combining

human expertise with artificial intelligence.

To learn more, visit www.infinx.com.

About The Role

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 AIdriven

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 dataintensive

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).