Sr Software Engineer : AI--Development,QA & Delivery | 6+ Yrs | Remote

Working Timing (6:30 pm - 2:30 am)
Work Mode: Remote
Experience Required: 6 + Years
Salary Package: 20- 30 LPA

About the Role:
We're looking for a hands-on senior engineer who can both build and rigorously evaluate software, while owning end-to-end delivery across the SDLC. This person will work extensively with AI-assisted development tools and will be accountable for ensuring every deliverable whether built internally, by vendors, or with AI assistance meets high standards of correctness, quality, security, and compliance. You'll be the connective tissue between development, QA, the AI SDLC framework, vendors, and clients driving execution while holding the line on engineering excellence.

Key Responsibilities:

Development
   Write, review, and refactor production-grade code across the stack as needed
   Leverage AI-assisted development tools to accelerate delivery without compromising quality or introducing technical debt
   Set and model engineering best practices: clean architecture, maintainability, performance, and scalability

Quality & Security
   Review deliverables with a QA mindset functional correctness, edge case coverage, regression risk, and test adequacy
   Conduct security-focused code reviews (secure coding practices, common vulnerability classes, dependency risk, data handling)
   Define and enforce quality gates and Definition-of-Done criteria across the SDLC
   Ensure compliance with relevant coding, security, and regulatory standards

Delivery & Orchestration
   Own the complete SDLC lifecycle planning, development, testing, deployment, and release
   Coordinate across development teams, QA, and the AI SDLC framework/tooling to keep delivery on track
   Act as the primary technical point of contact for vendors and clients, translating requirements and validating vendor deliverables against internal quality bars
   Identify bottlenecks or risks across teams/departments and drive them to resolution proactively
   Report on delivery health, quality metrics, and risk status to stakeholders

Required Skills:

• Programming Languages: Proficiency in at least one modern programming language (e.g., JavaScript/TypeScript, Java, Python, C#, Go, or similar); ability to read and reason about code in adjacent languages is a plus
     Software Design & Architecture: Solid grasp of design patterns, clean code principles, and system/API design
     Testing & QA Practices: Familiarity with unit, integration, and end-to-end testing frameworks; ability to assess test coverage and quality, not just write tests
     Test Automation Frameworks: Hands-on experience with at least one automated testing framework such as Playwright, Selenium, Cypress, or similar — able to write, review, and evaluate automated test suites as part of the quality gate 
     Security Fundamentals: Working knowledge of secure coding practices and common vulnerability classes (e.g., OWASP Top 10), plus basics of dependency and data-handling risk
     AI-Assisted Development Tools: Hands-on experience with tools like GitHub Copilot, Claude Code, Cursor, or similar
     Version Control & CI/CD: Practical experience with Git-based workflows and CI/CD pipelines (e.g., Jenkins, GitHub Actions, GitLab CI, or similar)
     Cloud & Infrastructure Basics: Working familiarity with at least one cloud platform (AWS, Azure, or GCP) and containerization basics (Docker)
     Code Review & Static Analysis: Comfort using or setting up static analysis, linting, and code quality tools (e.g., SonarQube, ESLint, or similar)
     Communication & Stakeholder Coordination: Ability to clearly communicate technical decisions and trade-offs to both technical and non-technical stakeholders (dev, QA, vendors, clients)
  

Required Qualifications:
   6+ years of professional software development experience, with strong hands-on coding ability in at least one modern stack
   Demonstrated experience reviewing others' code for quality, logic correctness, and security — not just writing code
   Solid understanding of secure coding practices and common vulnerability patterns (e.g., OWASP Top 10 or equivalent)
   Experience working with or evaluating AI-assisted development tools (e.g., Copilot, Claude Code, Cursor, or similar)
   Proven experience coordinating cross-functional stakeholders — development, QA, vendors, and clients
   Strong understanding of SDLC methodologies (Agile/Scrum, CI/CD pipelines, release management)
   Excellent communication skills to bridge technical and non-technical stakeholders

Preferred Skills:

Prior experience in a technical ownership, architect, or cross-team coordination capacity
   Experience working within an AI-augmented SDLC framework (AI-assisted pipelines with human review checkpoints)
   Vendor management or client-facing delivery experience
What Success Looks Like
   Deliverables consistently meet quality, security, and compliance bars before release
   Cross-team handoffs (dev QA vendor client) happen with minimal friction or rework
   AI tooling is used effectively to boost velocity without introducing quality or security regressions
   Stakeholders (internal and client-side) trust this person as the final technical checkpoint before sign-off