Experience : 7 to 10 years

Location : Bengaluru, Gurgaon, Pune

Job code : 101523

Posted on : Jun 08, 2026

About Us: Job Summary: This role requires expertise in full-stack development, AI-enabled engineering practices, MCP (Model Context Protocol) development, context engineering, CI/CD automation, cloud-native architectures, and modern software delivery methodologies. You will work closely with engineering, architecture, DevOps, and product teams to embed AI into every stage of software development.

Key Responsibilities:

1. AI-Powered SDLC Enablement

- Design and implement AI-driven SDLC accelerators for code generation, code review, documentation, testing, and deployment automation.
- Identify opportunities to improve engineering productivity through intelligent workflows and automation.
- Integrate AI capabilities into software delivery pipelines and developer platforms.
- Establish best practices for AI-assisted software development.

- MCP Engineering & Developer Tooling

- Develop MCP-based extensions and plugins to enhance developer productivity.
- Build reusable context-aware tools that integrate seamlessly with engineering workflows.
- Create modular AI capabilities that can be reused across projects and teams.
- Design capability registries and standardized tooling frameworks.

- Context Engineering

- Develop structured context frameworks that improve AI reasoning and task execution.
- Design mechanisms for grounding, memory management, and context orchestration.
- Optimize prompts, system instructions, and contextual data flows.
- Improve AI output quality through effective context management strategies.

- LLM Integration & Automation

- Integrate OpenAI, Azure OpenAI, Amazon Bedrock, or equivalent LLM platforms into enterprise engineering ecosystems.




- Develop intelligent assistants for coding, debugging, documentation, testing, and deployment support.
- Implement function calling, tool-use patterns, and workflow automation.
- Optimize AI performance, reliability, and operational costs.

- AI-Enabled CI/CD Engineering

- Build LLM-powered CI/CD workflows supporting automated validation and deployment decisions.
- Integrate AI-driven quality gates, code analysis, security scanning, and testing automation.
- Develop deployment intelligence capabilities that improve release confidence.
- Automate software quality assurance and compliance checks.

- Intelligent Testing & Quality Engineering

- Implement AI-assisted test generation and test maintenance strategies.
- Develop intelligent test automation frameworks.
- Improve test coverage through AI-generated scenarios and edge-case analysis.
- Support continuous quality engineering practices across development teams.

- Collaboration & Adoption

- Partner with engineering, architecture, DevOps, security, and product teams to drive AI adoption.
- Provide guidance on AI engineering best practices and implementation approaches.
- Support proof-of-concepts, pilot programs, and enterprise-scale rollouts.
- Promote a culture of innovation and continuous improvement.

Role Requirements and Qualifications

- Strong software engineering experience in Java, Python, Kotlin, and modern full-stack development.




- Strong understanding of MCP (Model Context Protocol) concepts and implementation.
- Experience building AI-powered development tools and workflow automation solutions.
- Knowledge of Retrieval-Augmented Generation (RAG) architectures.
- Experience with embeddings, vector search, and vector databases.
- Strong understanding of REST APIs, microservices, and distributed systems.
- Experience with Docker, Kubernetes, and Terraform.
- Familiarity with modern DevOps and CI/CD platforms.
- Experience implementing intelligent test automation solutions.
- Strong analytical, troubleshooting, and problem-solving capabilities.
- Excellent communication and stakeholder engagement skills.

Preferred Skills:

- Experience with OpenAI, Azure OpenAI, Amazon Bedrock, or equivalent AI platforms.
- Knowledge of LangChain, LlamaIndex, Semantic Kernel, CrewAI, or similar frameworks.
- Experience with GitHub Copilot, Copilot Studio, or AI-assisted engineering platforms.
- Familiarity with observability, monitoring, and AI governance frameworks.
- Experience with platform engineering and internal developer platforms.
- Understanding of software security, compliance, and secure development practices.
- Exposure to enterprise-scale digital transformation programs.

Why Join Us:

- Opportunities to work on transformative projects, cutting-edge technology and innovative solutions with leading global firms across industry sectors.
- Continuous investment in employee growth and professional development with a strong focus on up & re-skilling.
- Competitive compensation & perks, ESOPs and international assignments.
- Supportive environment with healthy work-life balance and a focus on employee well-being.
- Open culture that values diverse perspectives, encourages t

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