Java FSD Technical Architect

Greetings!

TCS India presents excellent opportunities for IT professionals.

Role :- Java Full Stack Technical Architect

Experience:- 10+ years

Location:- Mumbai/BBSR

Required Technical Skill Set:-Java, Spring boot and Angular

Position Overview

We are seeking an experienced Engineering Lead with a strong engineering mindset to lead technical initiatives, resolve delivery challenges across the Software Development Life Cycle (SDLC), and drive process efficiencies and automation. This role requires a strategic thinker who can bridge technical excellence with operational improvements while managing product enhancements and technical debt. The ideal candidate will have expertise in modern full-stack development and emerging technologies including Generative AI.

Key ResponsibilitiesLeadership & Technical Direction

• Lead and mentor development teams to deliver high-quality solutions on schedule.
• Establish technical standards, best practices, and coding guidelines aligned with modern full-stack development.
• Provide architectural guidance and technical decision-making for complex projects.
• Champion a culture of continuous improvement and engineering excellence.

SDLC Optimization & Delivery

• Identify bottlenecks and inefficiencies across all SDLC phases (requirements, design, development, testing, deployment).
• Implement solutions to accelerate delivery timelines without compromising quality.
• Establish clear metrics and KPIs to track delivery performance and quality indicators.
• Collaborate with cross-functional teams (QA, DevOps, Product) to streamline workflows.

Product Enhancement & Innovation

• Partner with product management to translate business requirements into technical roadmaps.
• Lead the design and implementation of new features and product enhancements.
• Ensure product enhancements align with technical architecture and scalability requirements.
• Drive user-centric development practices and gather feedback for continuous improvement.
• Balance feature delivery with technical sustainability.

Technical Debt Management

• Identify, prioritize, and manage technical debt across the codebase and infrastructure.
• Develop a strategic plan to systematically reduce technical debt without impacting feature delivery.
• Establish guidelines for acceptable technical debt and paydown schedules.
• Conduct code reviews and refactoring initiatives to improve code quality and maintainability.
• Advocate for technical debt remediation in sprint planning and roadmap discussions.

Generative AI Integration & Innovation

• Evaluate and integrate Generative AI practices and tools into development workflows.
• Lead initiatives to leverage GenAI for code generation, testing automation, and productivity enhancement.
• Develop best practices for responsible AI usage and governance within the engineering team.
• Mentor teams on GenAI development patterns, prompt engineering, and AI-assisted development.
• Explore opportunities for GenAI-powered features and enhancements in product offerings.

Automation & Process Improvement

• Design and implement automation solutions for repetitive tasks (testing, deployment, monitoring).
• Evaluate and recommend tools and technologies to enhance productivity.
• Drive adoption of CI/CD pipelines and infrastructure-as-code practices.
• Establish automated quality gates and regression testing frameworks.
• Optimize build, test, and deployment processes.

Problem Resolution

• Proactively identify and resolve technical and process-related delivery issues.
• Conduct root cause analysis on production incidents and implement preventive measures.
• Troubleshoot complex technical challenges and guide teams toward solutions.
• Manage escalations and ensure timely resolution of critical issues.

Collaboration & Communication

• Work closely with stakeholders, product teams, and business leaders to align technical delivery with business objectives.
• Present findings, recommendations, and progress updates to senior management.
• Foster knowledge sharing and documentation across teams.
• Communicate trade-offs between feature delivery, technical debt, and process improvements.

Required Qualifications/Experience

• 10+ years in software development with 4+ years in a technical leadership role.
• Proven experience with full-stack development across frontend and backend technologies.
• Deep understanding of SDLC phases and best practices.
• Experience managing both product enhancements and technical debt in production environments.
• Demonstrated experience with Generative AI practices, tools, and development methodologies.

Technical Expertise - Full Stack Development

• Frontend: Advanced proficiency in Angular (versions 8+); experience with TypeScript, RxJS, and reactive programming patterns.
• Backend: Strong expertise in Spring Boot and Java (Java 8+); experience with microservices architecture, REST APIs, and enterprise application development.
• Cloud Platform: Hands-on experience with Microsoft Azure (App Services, Azure SQL, Azure DevOps, Azure Functions, Container Registry).
• Database: Proficiency with relational databases (SQL Server, PostgreSQL) and NoSQL databases.
• DevOps & Deployment: Experience with containerization (Docker), orchestration, CI/CD pipelines, and infrastructure-as-code.

Generative AI & Modern Development

• Practical knowledge of GenAI models, APIs, and frameworks (OpenAI, Azure OpenAI, LangChain, etc.).
• Experience integrating AI-powered features into applications.
• Understanding of prompt engineering, fine-tuning, and responsible AI practices.
• Familiarity with AI-assisted development tools and code generation platforms

Monitoring & Observability

• Hands-on experience with Azure Monitoring (Application Insights, Azure Monitor, Log Analytics).
• Proficiency with Dynatrace for application performance monitoring and observability.
• Ability to design comprehensive monitoring strategies and establish SLOs/SLIs.

Core Competencies

• Strong analytical and troubleshooting capabilities with focus on root cause analysis.
• Engineering mindset with passion for efficiency, scalability, and continuous improvement.
• Excellent verbal and written communication skills; ability to influence across levels.
• Automation skills and proven experience implementing automation frameworks and testing automation.

Preferred Qualifications

• Experience with Agile/Scrum methodologies and sprint planning.
• Knowledge of additional cloud platforms (GCP).
• Experience with API gateway patterns and service mesh technologies.
• Background in financial services or regulated industries.
• Certifications: Azure Solutions Architect, Azure Developer Associate, Spring Professional, PMP, or equivalent.
• Experience with performance optimization and scalability challenges.
• Published articles, open-source contributions, or speaking engagements on AI/ML or engineering practices.
• Experience with advanced GenAI use cases (RAG, fine-tuning, multi-agent systems).

Key Competencies

Competency Description Technical Acumen

Deep full-stack technical knowledge with ability to make sound architectural decisions across Angular, Spring Boot, Java, and Azure. AI/GenAI Expertise

Understanding of Generative AI practices, development patterns, and ability to lead AI-driven initiatives.

Leadership

Ability to inspire, mentor, and guide teams toward technical excellence and innovation.

Strategic Thinking

Ability to balance feature delivery, technical debt, and process improvements aligned with business goals.

Process Improvement

Passion for identifying inefficiencies and implementing scalable, automated solutions.

Product Mindset

Understanding of product development lifecycle and ability to translate business requirements into technical solutions.

Technical Debt Management

Ability to assess, prioritize, and systematically address technical debt. Observability & Monitoring

Expertise in designing and implementing comprehensive monitoring strategies using Azure and Dynatrace.

Resilience

Ability to handle pressure, manage competing priorities, and drive results.

Collaboration

Strong interpersonal skills and ability to work across silos with product, QA, and DevOps teams.

Success Metrics

• Reduction in delivery cycle time by 20-30% within first year.
• Improvement in code quality metrics and reduction in production defects by 25%+.
• Successful implementation of 2-3 major automation initiatives.
• Measurable reduction in technical debt (tracked through code quality tools and refactoring metrics).
• Timely delivery of product enhancements aligned with roadmap.
• Successful integration of 1-2 GenAI-powered features or development practices.
• Team satisfaction and retention improvements.
• On-time delivery of committed projects with improved quality.
• Reduced production incidents and faster mean-time-to-resolution (MTTR).
• Improved observability and monitoring coverage across applications.