Senior Full

Role Overview:

• Create technical work outputs aligned with specific project packages.
• Develop user interfaces and integration layers specifically designed for AI agents.
• Construct APIs and data pipelines that bridge AI systems with operational platforms.
• Establish robust monitoring, observability solutions tailored for AI applications in Bangalore, Gurgaon, or Pune.
• Implement DevOps automation strategies and CI/CD pipelines to streamline deployment.
• Support initiatives aimed at automating the Software Development Life Cycle (SDLC) through advanced tooling integration.

Key Requirements:

• Proven full-stack expertise with React, Python, AWS, and a strong foundation in CI/CD infrastructure as code and DevOps practices. Knowledge of MS SQL, Postgres, or other cloud databases is essential; proficiency in Generative AI (GenAI) tools is highly valued.
• A minimum of 5+ years designing and building full-stack applications with hands-on experience across modern frontend frameworks like React, Next.js, Angular, Vue, and backend technologies including Python, FastAPI, TypeScript, JavaScript, and Kotlin.
• Substantial cloud architecture skills (AWS preferred) for implementing scalable solutions; at least 3+ years working with Infrastructure as Code such as Terraform, AWS CDK, or CloudFormation.
• Expertise in asynchronous API design using REST, GraphQL, gRPC, along with identity protocols like OpenID Connect and OAuth 2.0.
• Solid background (5+ years) in distributed systems, event-driven architectures, and microservices patterns optimized for scale.
• Familiarity with observability tools including OpenTelemetry, CloudWatch, Datadog, AppInsights, and Log Analytics to ensure operational excellence.
• Experience applying unit testing frameworks like pytest or NUnit alongside integration and end-to-end backend testing strategies.
• Knowledge of application security frameworks such as Blackbox; experience with role-based authentication using JWT tokens, EntraID, and Active Directory (3+ years).
• Skill in database optimization and session management.
• Hands-on building applications integrating Generative AI or Large Language Model capabilities including RAG systems, chat interfaces, agent workflows, and LLM-powered features.
• Utilization of AI-assisted development tools like GitHub Copilot within the daily software workflow.
• Mastery of AI agent architectures, orchestration patterns, and emerging protocols such as MCP (Model Context Protocol) and A2A (Agent-to-Agent), with practical experience constructing multi-agent systems.
• Adoption of agentic software development methodologies to accelerate workflows in coding, testing, debugging, and code review using AI agents.