About the role
Responsibilities:
- Build and develop technical work outputs for each work package.
- Implement user interfaces and integration layers for AI agents.
- Develop APIs and data pipelines connecting AI systems to operational platforms.
- Build monitoring and observability solutions for AI applications.
- Implement DevOps automation and CI/CD pipelines.
- Support SDLC automation initiatives and tooling integration.
Requirements:
- Full-stack + React, Python, AWS 300 + CICD Infra as Code + DevOps + App unit testing + Python + Database (MS SQL, Postgres, cloud DB, etc. ).
- Some proficiency in GenAI and AI tools is a plus.
- 5+ years of software development experience designing and building full-stack applications, with hands-on work across frontend (e. g., React, Next.js, Angular, Vue) and backend (e. g., APIs, microservices, data layers).
- 5+ years of hands-on development with modern programming languages (e. g., Python preferred, FastAPI, TypeScript, JavaScript, and Kotlin).
- 5+ years of cloud architecture and solution implementation experience on AWS or comparable cloud platforms.
- 3+ years of experience with Infrastructure as Code (e. g., Terraform preferred, AWS CDK, and CloudFormation), CI/CD pipelines, and DevOps practices.
- 5+ years of background in asynchronous API design and implementation (REST, GraphQL, gRPC) and identity protocols (OpenID Connect, OAuth 2.0).
- 5+ years of experience with distributed systems, event-driven architectures, and microservices patterns at scale.
- 3+ years of familiarity with observability and monitoring practices (e. g., OpenTelemetry, CloudWatch, Datadog, AppInsight, and Log Analytics) with a focus on operational excellence.
- 3+ unit testing frameworks (e. g., pytest, NUnit); integration testing and end-to-end. (backend testing).
- 5+ Application security frameworks (e. g., Blackbox).
- 3+ Role-based authentication and authorization: JWT token, EntraID, Active Directory.
- 3+ DB optimization, session management.
- Experience building applications that integrate generative AI or large language model capabilities (e. g., RAG, chat interfaces, agent workflows, LLM-powered features).
- Experience using AI-assisted development tools as part of the software development workflow (ub Copilot).
- Experience of AI agent architectures, orchestration patterns, and emerging protocols (e. g., MCP, A2A), with hands-on experience building multi-agent systems.
- Experience with agentic software development methodologies using AI agents to accelerate development workflows, including coding, testing, debugging, and code review.
Technical Skills:
- Strong experience with modern web frameworks (React) and backend development (Python, Node.js ).
- Proficiency in API development (REST, GraphQL) and microservices architectures.
- Knowledge of AWS services (Lambda, ECS, API Gateway, CloudFormation, CDK).
- Experience with DevOps tools and CI/CD pipelines (Bonus).
- Familiarity with AI/ML application integration patterns.