Software Architect

Engineering Ahmedabad12–14 yrs experience
ROLE SUMMARY
The Software Architect owns the architecture and technical direction of the ALIS Suite and Nexsure codebases. This person establishes and executes a practical engineering roadmap for each product, balancing new capability with technical debt reduction, architecture improvement, security, resilience, and maintainability.

The role works in a Microsoft technology environment that includes C#, .NET, and SQL Server. It requires hands-on understanding of existing systems, clear design decisions, and close partnership with engineering, product, security, and operations. The architect will identify where AI can improve product value and engineering delivery, test those opportunities responsibly, and guide adoption when the evidence supports it.

The person in this role will
  • Own the current and target architecture for ALIS Suite and Nexsure.
  • Publish and deliver distinct, prioritized engineering roadmaps for both products.
  • Guide design and implementation of meaningful product and platform changes.
  • Reduce technical debt while protecting customer commitments and production stability.
  • Strengthen security, reliability, performance, observability, and recoverability.
  • Evaluate AI use cases with clear value, data protection, quality, and operational measures.
  • Make architecture decisions visible through concise records, standards, and reviews.

KEY RESPONSIBILITIES
Architecture and roadmap ownership
  • Assess the structure, dependencies, data flows, and operational risks of ALIS Suite and Nexsure; document material gaps and constraints.
  • Create a product-specific architecture vision and rolling roadmap that links technical work to customer value, delivery speed, and risk reduction.
  • Sequence architecture evolution with incremental milestones, clear tradeoffs, measurable outcomes, and explicit migration plans.
  • Set and maintain design principles, interface contracts, coding standards, and architecture decision records.

Technology Best Practices and Decisions
  • Guide C# and .NET application design, SQL Server schema and query evolution, API and integration patterns, and deployment architecture.
  • Review critical designs and code paths; coach teams on performance, testability, backward compatibility, and safe change.
  • Improve build, test, release, and environment practices so architectural improvements reach production reliably.
  • Improve observability across technologies and platforms
  • Evaluate and introduce new technologies and tech stacks as needed.

AI forward innovation
  • Identify product and engineering workflows where AI could create measurable value for customers or teams.
  • Design small experiments with success measures, human oversight, evaluation data, and safeguards for sensitive information.
  • Turn successful experiments into maintainable capabilities with monitoring, cost controls, and clear ownership.

Technical debt and hardening
  • Maintain a visible debt and risk register, including aging dependencies, fragile integrations, database bottlenecks, and high-risk components.
  • Improve authentication, authorization, data handling, secrets management, auditability, resilience, and disaster recovery in partnership with security and operations.
  • Use incidents, defects, and production telemetry to guide architectural fixes rather than relying only on planned projects.

Cross-functional leadership
  • Partner with product and engineering leaders to make tradeoffs among features, platform health, risk, and delivery capacity.
  • Communicate architecture options and decisions to technical and nontechnical stakeholders with evidence and clear consequences.
  • Mentor engineers and technical leads, encourage constructive design review, and build shared ownership across both codebases.

MEASURES OF SUCCESS
  • Roadmaps for ALIS Suite and Nexsure are agreed, maintained, and translated into delivered milestones.
  • Key architecture risks and technical debt are reduced with visible evidence of improved reliability, security, performance, or delivery speed.
  • Engineering teams can explain and use documented design standards and decision records.
  • AI initiatives advance on the strength of measured value and safe, supportable implementation.

REQUIRED SKILLS AND EXPERIENCE
  • Deep software architecture and hands-on engineering experience with C#, .NET, SQL Server, APIs, and enterprise application systems.
  • Experience modernizing established codebases without interrupting business-critical delivery.
  • Cloud-native architecture experience (containerization, horizontal scalability, zero-downtime deployment patterns)
  • Ability to design systems for security, reliability, scalability, observability, and operational recovery.
  • Strong judgment in prioritizing architectural work and explaining tradeoffs to product, engineering, and executive partners.
  • Experience leading through influence, reviewing designs, and mentoring engineers across teams.
  • Practical experience evaluating or delivering AI-enabled capabilities, including quality assessment, data protection, and human oversight.

Preferred Experience
  • Experience with insurance software, complex customer integrations, or long-lived enterprise products.
  • Experience with cloud platforms, automated delivery pipelines, and data migration.
  • Experience defining architecture governance that helps teams move faster without unnecessary process.

INITIAL PRIORITIES
  • Build a shared architecture and risk assessment for both product codebases.
  • Agree on the first roadmap milestones with engineering and product leaders.
  • Deliver an early improvement that demonstrates safer delivery or measurable reduction in a high-priority risk.
  • Establish a repeatable process for design decisions, debt prioritization, and AI experiment evaluation.

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