Company:MercerDescription:

Applications Development (Level E)

Location: Gurgaon / Noida
Work Model: Hybrid — at least three days a week in the office

What can you expect?

As a Senior Principal Engineer – Applications Development (Level E) at Mercer, you will serve as a senior technical leader responsible for shaping engineering strategy, driving enterprise-scale architecture decisions, and leading the design, development, testing, and modernization of highly scalable, resilient, and secure software platforms. This role requires deep hands-on expertise, strong architectural judgment, and the ability to influence engineering direction across multiple teams, products, and platforms.

You will work closely with product, engineering, architecture, security, data, and platform teams to deliver high-quality business solutions aligned with enterprise goals. You will also play a key role in embedding AI-assisted engineering and Generative AI capabilities throughout the Software Development Life Cycle (SDLC) to improve delivery speed, code quality, testing effectiveness, developer productivity, and operational intelligence.

This is a highly collaborative leadership role within a Scaled Agile environment, requiring a self-driven, delivery-focused engineering leader with broad full-stack, cloud, platform, and AI engineering expertise.

We will count on you to:

• Provide technical leadership and architectural direction across multiple applications, products, or engineering streams.
• Design and deliver scalable, resilient, secure, and maintainable enterprise applications aligned with domain and enterprise architecture standards.
• Lead the engineering lifecycle from solution design through development, testing, deployment, observability, and production optimization.
• Drive adoption of modern engineering practices, including domain-driven design, event-driven architecture, API-first design, microservices, cloud-native engineering, and platform automation.
• Define and implement comprehensive quality engineering strategies, including unit, integration, contract, end-to-end, performance, security, and resiliency testing.
• Establish and evolve engineering standards, reusable frameworks, reference implementations, and best practices across teams.
• Lead the development of high-quality automated testing frameworks and quality gates to improve release confidence and reduce regression risk.
• Partner with DevOps and platform engineering teams to strengthen CI/CD pipelines, Infrastructure as Code, release governance, and environment automation.
• Embed security-by-design principles into engineering practices, including proactive remediation of SAST, DAST, dependency, secrets, and container vulnerabilities.
• Drive modernization and optimization initiatives for legacy applications, development toolchains, deployment pipelines, and runtime architectures.
• Mentor senior and junior engineers, fostering a culture of technical excellence, innovation, accountability, and continuous improvement.
• Influence and guide teams on technology choices, platform strategy, engineering trade-offs, and implementation approaches.
• Collaborate with stakeholders to break down complex business requirements into robust, scalable technical solutions.
• Analyze production issues, system bottlenecks, and test failures, and lead root cause analysis and long-term corrective actions.
• Stay current with emerging trends in software engineering, cloud platforms, developer tooling, AI engineering, and intelligent automation, and evaluate their practical adoption.

AI and Intelligent Engineering Responsibilities in SDLC

• As a Level E engineering leader, you will be expected to actively leverage and promote AI, ML, and Generative AI capabilities across the SDLC, including:
• Driving adoption of AI-assisted software development for code generation, code review, refactoring, documentation, and developer productivity acceleration.
• Applying Generative AI in test engineering, including automated test case generation, synthetic test data creation, intelligent test prioritization, defect prediction, and self-healing test automation.
• Using AI tools to improve requirements analysis, story refinement, impact assessment, and traceability across business and technical artifacts.
• Incorporating AI-driven approaches for application observability, anomaly detection, incident triage, root cause analysis, and operational optimization.
• Defining engineering patterns for integrating LLMs, SLMs, agentic AI systems, RAG architectures, prompt orchestration, vector stores, and AI workflow frameworks into enterprise applications.
• Ensuring responsible implementation of AI solutions through governance, security, privacy, explainability, bias awareness, model evaluation, and compliance controls.
• Identifying opportunities to embed AI into developer platforms, enterprise workflows, business processes, and customer-facing solutions.
• Leading engineering teams in the safe and scalable use of AI accelerators across design, build, test, release, and support functions.

What you need to have:

• Proven experience operating at a senior engineering leadership level, delivering complex enterprise applications across multiple teams, products, and platforms.
• Strong experience in full-stack software engineering, solution architecture, quality engineering, and enterprise delivery.
• Proven ability to lead technical implementation across a broad mix of languages, frameworks, platforms, and cloud environments.
• Strong communication and stakeholder management skills, with the ability to influence both technical and non-technical audiences.
• Deep experience with Agile, Lean, DevSecOps, Continuous Integration, Continuous Delivery, Test-Driven Development, and Infrastructure as Code.
• Proven experience with cloud-native architectures, distributed systems, asynchronous/event-driven patterns, and modern integration approaches.
• Strong experience in secure software engineering and remediation of vulnerabilities identified via SAST, DAST, open-source dependency scanning, and runtime/container security checks.
• Experience driving engineering quality through CI/CD, automation, policy controls, code quality gates, and release governance.
• Strong leadership capability as a self-starter, technical mentor, and cross-functional engineering influencer.
• Demonstrated experience integrating or enabling AI/ML/Generative AI capabilities within engineering workflows, products, or enterprise solutions.

Technical Skills or Qualifications Required:

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience; BTech / MCA preferred.
• Extensive experience as a Senior Engineer, Lead Engineer, Principal Engineer, or equivalent role, with strong expertise in software development, architecture, and test engineering.
• Advanced proficiency in one or more programming languages such as JavaScript/TypeScript, C#, Python, with strong experience in enterprise-scale application delivery.
• Strong hands-on experience with modern frameworks and technologies such as:
  • Angular
  • Node.js
  • Express.js
  • .NET / .NET Core
  • MEAN / MERN stack
  • Less / Sass
• Deep expertise in unit testing, integration testing, API testing, end-to-end testing, performance testing, 
• Strong experience in building and maintaining automated testing frameworks, reusable test utilities, and quality engineering accelerators.
• Expertise in CI/CD pipelines and engineering toolchains, including:
  • Azure DevOps
  • GitHub Actions
  • Docker
  • Kubernetes
  • Artifact and package management tools
• Strong experience with containerization, orchestration, and cloud deployment patterns using Docker and Kubernetes.
• Proven knowledge of application architecture, design patterns, refactoring, system design, secure coding, and engineering best practices.
• Strong experience with ORM frameworks, relational and NoSQL databases, and data access design, including:
  • T-SQL
  • MS SQL Server
  • MongoDB
  • NoSQL data modeling practices
• Strong knowledge of SDLC processes, engineering governance, and collaboration tooling, including:
  • Confluence
  • JIRA
  • Azure DevOps
  • GitHub
• Experience designing, deploying, and supporting applications on AWS and Microsoft Azure.
• Strong analytical, troubleshooting, and problem-solving capabilities, including the ability to resolve highly complex production and engineering issues.

Advanced AI / GenAI Skills Required for Level E

• Strong knowledge of Generative AI, AI engineering, and applied machine learning concepts, including:
  • Large Language Models (LLMs)
  • Small Language Models (SLMs)
  • Agentic AI
  • Prompt engineering
  • Retrieval-Augmented Generation (RAG)
  • Embeddings and vector databases
  • Fine-tuning and model adaptation concepts
  • NLP and semantic search
  • Knowledge representation and reasoning
  • AI orchestration frameworks
• Experience with AI/ML and GenAI ecosystems, tools, or libraries such as:
  • TensorFlow
  • PyTorch
  • LangChain / LangGraph / LangFlow
  • Semantic Kernel
  • Hugging Face
  • OpenAI / Azure OpenAI patterns
  • Vector databases and retrieval frameworks
• Experience designing or contributing to AI-enabled applications, copilots, intelligent assistants, knowledge search, summarization, workflow automation, or decision-support systems.
• Understanding of AI governance, model evaluation, responsible AI, prompt safety, security, privacy, and compliance controls.
• Ability to identify and implement AI use cases across the SDLC, including:
  • AI-assisted coding
  • Automated documentation generation
  • Intelligent code review
  • Test generation and optimization
  • Defect triage
  • Release risk prediction
  • Incident summarization and operational support
• Familiarity with MLOps / LLMOps concepts, model lifecycle considerations, and enterprise AI platform integration.
• Basic to working knowledge of Databricks and AI/data engineering ecosystems is highly desirable.

What makes you stand out?

• BTech / MCA or equivalent advanced technical background.
• Proven experience leading enterprise-scale engineering modernization initiatives.
• Strong expertise in AI/ML and Generative AI-enabled software delivery.
• Demonstrated success in building or scaling engineering platforms, reusable components, and quality engineering practices.
• Experience driving adoption of AI across the SDLC to improve developer productivity, software quality, and delivery outcomes.
• Strong knowledge of cloud, security, observability, automation, and platform engineering.
• Ability to balance hands-on engineering depth with strategic technical leadership across multiple squads or domains.

Join us

Join us at Mercer, where you will have the opportunity to lead innovative engineering initiatives, shape modern software architecture, and accelerate the adoption of AI-powered engineering practices across the SDLC. We look forward to your application.

Marsh (NYSE: MRSH) is a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information, visit corporate.marsh.com, or follow us on LinkedIn and X.Marsh is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law.Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person.