Delivery Consultant, AWS Professional Services
Role details
Job location
Tech stack
Job description
We are seeking a hands-on Senior Consultant with deep software engineering, Generative AI, and cloud architecture expertise to deliver complex technical consulting engagements within AWS Professional Services. The ideal candidate will combine strong technical depth with proven engineering capabilities, having both the software development background to work with complex architectures and code, and the curiosity to invent on behalf of our customers using AWS services. You develop using agentic tools and services - AI-powered coding assistants, agentic IDEs, and AI-driven development workflows are part of how you build every day. You understand how to design and orchestrate AI agents, work with protocols like MCP and A2A, and build autonomous systems using services like Amazon Bedrock. You'll work directly with customers to deliver innovative AWS solutions, applying your technical expertise to ensure successful outcomes while maintaining the highest standards of quality and security.
You'll work directly with customers to deliver innovative AWS solutions, leveraging your technical expertise to ensure successful outcomes while maintaining the highest standards of quality and security.
Key job responsibilities Full-Stack Development - Design, build, and ship cloud-native applications end-to-end. Develop responsive frontend interfaces (e.g., React, Next.js, Vue) and scalable backend services (e.g., Python, TypeScript, Java), deploying on AWS with infrastructure as code and CI/CD pipelines.
AI-Assisted Software Development - Use AI-powered development tools as part of your daily workflow. Champion agentic software development methodologies - leveraging AI to accelerate coding, testing, code review, and delivery.
Agentic Development - Design and implement AI agent architectures and multi-agent systems. Work with emerging protocols (e.g., MCP, A2A) and orchestration frameworks to build autonomous and semi-autonomous AI workflows that solve real customer problems.
Solution Delivery - Work directly with customers to understand requirements, architect solutions, and deliver working software. Build distributed systems, modernize existing applications, and implement best practices across cloud environments.
Technical Leadership - Guide customer and partner teams on software engineering best practices, software architecture decisions, and code quality. Conduct code reviews, mentor developers, and ensure solutions meet security and operational excellence standards.
Requirements
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., TypeScript, JavaScript, Python, Java, Kotlin, .NET)
- 5+ years of cloud architecture and solution implementation experience on AWS or comparable cloud platforms
- Experience using AI-assisted development tools as part of the software development workflow
- Experience with Infrastructure as Code (e.g., AWS CDK, CloudFormation, Terraform), CI/CD pipelines and DevOps practices, Understanding 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
- Understanding of background in API design and implementation (REST, GraphQL, gRPC) and identity protocols (OpenID Connect, OAuth 2.0)
- Hands-on experience with containerization and orchestration (e.g., Docker, Amazon ECS, Kubernetes)
- Experience with distributed systems, event-driven architectures, and microservices patterns at scale
- Familiarity with observability and monitoring practices (e.g., OpenTelemetry, CloudWatch, Datadog) with a focus on operational excellence
- Experience building applications that integrate generative AI or large language model capabilities (e.g., RAG, chat interfaces, agent workflows, LLM-powered features)