Live opening · Posted 2 days ago

Staff Software Engineer

Applied Systems · Bangalore
Instahyre 11-15 yrs
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At a glance

The key details from the original listing.

Posted 2 days ago
CompanyApplied Systems
LocationBangalore
Experience11-15 yrs
SourceInstahyre
Listed2 days ago

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About the role

Description supplied by the original job listing.

We're searching for a Technical Lead to join our Engineering team in Bengaluru. This is a senior technical leadership role built around quality-led, AI-first product and quality engineering. You will define and drive the application architecture for our platform, designing scalable, resilient systems. NET and Angular/React while embedding quality engineering into every architectural decision. You'll champion AI-powered development practices across the entire SDLC, set the technical vision for quality at the architecture level, and mentor engineering teams on building software that is correct by construction, not just tested after the fact. We're looking for someone who sees quality not as a phase but as an architectural property, who leads through technical excellence, and who thrives at the intersection of product engineering, quality engineering, and AI-driven innovation.
Responsibilities:
Own and evolve the application architecture for full-stack systems built on NET (C#, ASP. NET Core) and Angular/React, ensuring scalability, maintainability, and quality by design.
Design quality-first architectures: embed testability, observability, fault isolation, and graceful degradation as first-class architectural concerns, not afterthoughts.
Define and drive the AI-first engineering strategy: establish standards for AI-powered development tools (e. g., Claude, GitHub Copilot, AI code-review/test-generation tools) and AI SDLC best practices across engineering teams.
Design and build microservice-based, event-driven systems with async design patterns, ensuring resilience, loose coupling, and horizontal scalability.
Lead the quality engineering practice at the architecture level: define test automation strategies, contract testing frameworks, performance/load testing architectures, and shift-left quality gates embedded in CI/CD pipelines.
Establish and enforce coding standards, design patterns, and architectural decision records (ADRs) that raise the quality bar across all product engineering teams.
Collaborate with product managers, engineering leads, QA leadership, and stakeholders to translate business requirements into robust technical solutions and architectural roadmaps.
Drive cross-team technical alignment: review system designs, conduct architecture reviews, and ensure consistency across services and modules.
Mentor and coach senior and mid-level engineers on architecture principles, quality engineering practices, AI tool adoption, and full-stack development excellence.
Evaluate and introduce emerging technologies, AI/ML frameworks, and quality tools to continuously improve engineering velocity, reliability, and product quality.
Prepare and maintain architectural documentation including system design documents, ADRs, runbooks, and quality engineering playbooks.
Champion a culture of continuous improvement by running blameless postmortems, quality retrospectives, and proactively identifying architectural debt and quality risks.
Requirements:
Education: BE, B. Tech, M. Tech Only.
Experience Level: 12-15 years of hands-on software engineering experience, with 4+ years in a lead or principal/staff engineer role.
Mandatory Skills (Full-Stack + Quality and Product Engineering):
Deep expertise in. NET Framework (C#, ASP. NET, . NET Core) and modern frontend frameworks (Angular 10+ and/or ReactJS with TypeScript).
Proven experience designing and owning application architectures: service decomposition, API design, data modelling, and system integration patterns.
Strong proficiency in microservice architecture, event-driven programming, async design patterns, and distributed systems.
Extensive experience designing and consuming RESTful APIs and Web APIs with a focus on contract-first design.
Strong knowledge of HTML5 CSS3 and modern JavaScript/TypeScript for building robust, accessible user interfaces.
Solid experience with relational databases (SQL Server, MySQL, PostgreSQL) including schema design, query optimisation, and performance tuning.
Expert-level quality engineering mindset: deep experience with test automation frameworks, unit/integration/end-to-end testing, contract testing, and performance/load testing at the architecture level.
Proven ability to embed quality gates in CI/CD pipelines: linting, static analysis, test coverage thresholds, security scanning, and automated regression.
Strong understanding of quality management principles: defect prevention strategies, root cause analysis, test planning, quality metrics, and continuous quality improvement across the product lifecycle.
Demonstrated expertise using AI-powered development tools (e. g., Claude, GitHub Copilot, ChatGPT, AI code-review/test-generation tools) and defining AI SDLC standards for engineering teams.
Experience with version control systems (Git), branching strategies, and code review practices at scale.
Strong architecture documentation skills: ADRs, system design documents, sequence diagrams, and quality engineering playbooks.
Excellent communication and stakeholder management skills; ability to articulate technical decisions to both engineering and business audiences.
Proven ability to mentor and lead engineers across multiple teams; strong track record of raising the technical and quality bar.
You may have other skills, including:
Experience with the following technologies is a plus.
Experience with AWS cloud services (EC2 Lambda, S3 RDS, ECS/EKS, AWS) or equivalent cloud platforms (Azure, GCP).
Experience with containerisation and orchestration tools Docker and Kubernetes and infrastructure-as-code (Terraform, CloudFormation).
Familiarity with GitLab CI/CD, TeamCity, Octopus Deploy, or similar build/release tooling.
Experience with API management platforms such as Apigee and local development workflow tools like Tilt.
Experience with observability and monitoring platforms such as Datadog, Splunk, or similar, including defining SLIs, SLOs, and alerting strategies.
Knowledge of AI/ML frameworks or platforms and their application in software engineering and quality engineering workflows.
Experience with cloud-native architectural patterns: serverless, service mesh, CQRS, event sourcing.
Familiarity with security architecture principles OWASP, secure coding practices, and DevSecOps integration.

Experience
11-15 yrs

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