Job Purpose:
This role is responsible for defining and driving the technical architecture of an enterprise-scale SaaS CRM platform built on Ruby on Rails, MongoDB, and modern cloud-native technologies. As a Tech Lead – Architecture, you will own architectural decisions, establish platform-wide engineering patterns, and hands-on build foundational systems that underpin scalability, reliability, and performance.You will lead the design of distributed backend services, cloud infrastructure, and data systems while remaining deeply embedded in the codebase. This is not a management-only role - you will write production code, resolve the hardest technical challenges, and drive AI-augmented engineering practices across the team.
Job Responsibilities:
Architecture & Technical Strategy:
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Own and evolve the overall backend architecture, including service decomposition, API design, data modelling, and integration patterns
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Define and maintain architectural blueprints, technical roadmaps, and Architecture Decision Records (ADRs)
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Design scalable, fault-tolerant distributed systems using Ruby on Rails, MongoDB, Redis, and Sidekiq
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Architect event-driven and asynchronous processing pipelines using Sidekiq and Redis to handle high-throughput workloads
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Lead data architecture strategies including MongoDB schema design, sharding, indexing optimization, and data lifecycle management
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Define caching strategies (Redis) at application, query, and infrastructure layers
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Design and enforce API standards (RESTful, versioning, rate limiting, authentication) across all platform services
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Evaluate build-vs-buy decisions and technology adoption with clear technical and business justification
Hands-On Engineering:
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Write production-grade Ruby on Rails code for core platform services and architectural foundation layers
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Build and maintain shared libraries, internal gems, middleware, and service abstractions
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Conduct performance profiling and optimization using New Relic — identify N+1 queries, memory bloat, slow endpoints, and job bottlenecks
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Implement and optimize Sidekiq job architectures including queue prioritization, retry strategies, and job orchestration patterns
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Design database migration strategies for MongoDB at scale, including zero-downtime migrations and index management
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Develop Infrastructure as Code (IaC) using Terraform or equivalent to provision and manage GCP resources
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Architect CI/CD pipelines (GitHub Actions) with automated testing, security scanning, and deployment orchestration
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Design Kubernetes deployment architectures including Helm charts, autoscaling, health probes, and rolling deployments
Cloud & Infrastructure (GCP):
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Architect cloud-native deployments on GCP, leveraging GKE, Memorystore, Cloud Storage, Pub/Sub, and related services
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Design Kubernetes cluster architectures including namespace strategies, resource quotas, and network policies
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Define Docker containerization standards — multi-stage builds, image optimization, and base image governance
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Establish IaC practices ensuring all infrastructure is version-controlled, peer-reviewed, and reproducible
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Design disaster recovery, backup, and failover strategies for databases, caches, and application services
AI-Augmented Engineering & AI Agents:
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Champion adoption of AI-powered tools (GitHub Copilot, Cursor Agent Mode) and define best practices, prompt engineering guidelines, and internal playbooks for the engineering team
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Leverage AI tools to generate and maintain comprehensive test suites — including AI-assisted test scaffolding, edge case discovery, and test coverage gap identification
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Design and implement AI agent workflows for automating engineering tasks such as PR summarization, code review, documentation generation, and codebase health monitoring
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Establish governance for AI-generated code — mandatory human review policies, hallucination detection, and security review guidelines
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Train and mentor engineers on effective AI prompting techniques for complex tasks including refactoring, architectural analysis, and debugging
Observability, Reliability & Security:
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Design observability strategies using New Relic, including custom dashboards, alerting policies, and SLI/SLO definitions
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Establish production reliability practices — runbooks, incident response procedures, and post-mortem processes
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Implement secure coding practices including OAuth, JWT, RBAC, secrets management, and vulnerability remediation
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Drive capacity planning based on traffic patterns, growth projections, and infrastructure costs
Technical Leadership:
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Lead architecture review boards and technical design sessions
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Mentor engineers on system design, architectural thinking, and effective AI tool usage
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Conduct code reviews focused on architectural consistency, performance, and security
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Drive technical debt reduction through systematic identification and prioritization
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Maintain technical documentation including architecture diagrams, data flows, and operational guides
Requirements:
Required Education and Experience:
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Bachelor's degree in Computer Science, Engineering, or equivalent combination of education and experience
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10+ years of professional software engineering experience in backend systems design, development, and production operations
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3+ years in a technical leadership or architect role owning architecture for production systems at scale
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Expert-level Ruby on Rails — framework internals, ActiveRecord, Rack middleware, Rails engines, and metaprogramming
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Strong MongoDB experience — document schema design, aggregation pipelines, indexing, sharding, replica sets, and performance tuning
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Deep Sidekiq experience — queue topology, concurrency management, retry/backoff strategies, and monitoring at scale
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Strong Redis experience — caching patterns, data structures, Pub/Sub, memory management, and HA configurations
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Hands-on GCP experience — GKE, Memorystore, Cloud Storage, Pub/Sub, IAM, and Cloud Monitoring
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Production Kubernetes experience — cluster management, Helm, autoscaling, resource optimization, and troubleshooting
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Docker expertise — containerization best practices, multi-stage builds, and container security
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Infrastructure as Code — Terraform (preferred) or equivalent, with focus on reproducibility and drift management
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New Relic proficiency — APM, custom instrumentation, alerting, and SLO management
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Advanced Git/GitHub workflows — branching strategies, PR governance, and GitHub Actions
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Solid understanding of distributed systems principles — CAP theorem, eventual consistency, idempotency, and circuit breakers
Required AI Tooling Experience:
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Proficiency with AI coding assistants (GitHub Copilot, Cursor including Agent Mode) in daily development workflows
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Hands-on experience writing and maintaining tests using AI tools AI-assisted test generation, edge case identification, and coverage improvement
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Experience designing or working with AI agents for developer productivity code review automation, documentation generation, or codebase exploration
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Demonstrated ability to craft effective prompts for complex engineering tasks and establish team-wide AI usage guidelines
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Understanding of AI-generated code risks hallucination mitigation, output validation, and responsible AI practices
Preferred Experience:
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Experience migrating monolithic architectures to modular monoliths or microservices
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Experience building custom LLM-based agents or integrating LLM APIs into developer tooling
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Familiarity with AI agent frameworks such as LangChain, CrewAI, or AutoGen
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Contributions to open-source Ruby or infrastructure projects
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Knowledge of compliance frameworks (SOC 2, GDPR) as they apply to platform architecture
Expected Competencies:
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Architectural thinking — ability to reason about systems at multiple levels of abstraction
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Hands-on credibility — writes production code daily alongside architectural responsibilities
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AI-forward mindset — proactive in leveraging AI tools to improve personal and team productivity
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Technical communication — articulates complex concepts to engineering and non-engineering stakeholders
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Pragmatic decision-making — balances ideal architecture with delivery timelines and business constraints
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Ownership and accountability — end-to-end responsibility for architectural decisions and production outcomes
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Mentorship orientation — invests in growing the technical capabilities of the broader team
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Strong English communication skills, both written and verbal
Work Timings:
Monday through Friday from 12 PM to 9 PM IST to provide healthy overlap between India team and US team and supporting both to ensure adequate collaboration. This role will be working in Hybrid Mode and will require at least 2 days’ work from office at Hyderabad. Occasional evening and weekend work may be expected in case of job-related emergencies or client needs.
EEO Statement:
Cendyn provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, Cendyn complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
Cendyn expressly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. Improper interference with the ability of Cendyn’s employees to perform their job duties may result in discipline up to and including discharge.
Other Duties:
Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time with or without notice.
