AI-Native Full-Stack Backend Engineer Forward Deployed Engineering
- Advanced and proven experience designing, leading, and controlling agentic software development as a primary way of delivering complex software. You should be able to demonstrate how you structure the work of AI coding agents across the SDLC — providing them with the right specifications, context, tools, environments, orchestration, guardrails, and feedback mechanisms — to reliably deliver production-quality software while retaining engineering oversight and accountability.
- Approximately 5+ years of professional software engineering experience, preferably including consulting, client-facing engineering, solution engineering, or similar roles.
- Strong backend or full-stack engineering experience in one or more ecosystems such as Java, C#, Python, Node.js/TypeScript, Go, or similar, combined with the ability to work effectively outside a primary technology stack.
- Experience designing and delivering APIs, integrations, distributed systems, event-driven architectures, and data-intensive applications.
- Strong knowledge of relational and non-relational databases and experience with cloud platforms such as Azure, AWS, or Google Cloud.
- Strong understanding of software architecture, security, scalability, reliability, performance, and maintainability.
- Hands-on experience with Git, automated testing, CI/CD, containers, observability, and modern software delivery practices.
- Ability to independently investigate unfamiliar systems, operate effectively with incomplete or evolving requirements, and rapidly become productive in new technical environments.
- Strong problem-solving, client communication, and stakeholder-management skills, including the ability to explain technical decisions and trade-offs to technical and non-technical audiences.
Additional experience that will help you succeed:
- Frontend experience with React, Angular, Vue, or similar frameworks.
- Experience with Kubernetes, Docker, serverless architectures, microservices, and infrastructure as code.
- Knowledge of enterprise platforms such as Salesforce, Microsoft platforms, Creatio, or comparable systems.
- Experience delivering AI agents, copilots, workflow automation, or intelligent enterprise applications.
- Familiarity with API management, enterprise integration platforms, event streaming, and advanced observability practices.
This person will work closely with clients, architects, product teams, and business stakeholders to rapidly understand problems, design practical solutions, build prototypes, and deliver production-ready applications.
The ideal candidate is comfortable working in ambiguous environments, translating business needs into technical solutions, and using modern AI development tools to accelerate design, coding, testing, documentation, and delivery. A person who enjoys solving complex business problems rather than working with a predefined technology stack. ,[Design, develop, and maintain scalable backend services, APIs, integrations, and data-processing solutions., Build full-stack applications when required, with primary ownership of backend architecture and implementation., Work directly with clients and business stakeholders to understand challenges and translate them into working software., Rapidly prototype, validate, and roll out new solutions., Take end-to-end ownership, from requirements discovery and solution design to deployment and operational support., Integrate enterprise platforms, cloud services, databases, APIs, and AI capabilities., Use AI-assisted development tools for code generation, refactoring, testing, debugging, documentation, and rapid experimentation., Apply rapid "vibe coding" techniques responsibly while maintaining security, maintainability, testing, and engineering quality., Build AI-enabled applications using LLMs, agents, retrieval-augmented generation, tool calling, and structured data., Establish reusable development patterns, accelerators, templates, and engineering standards., Support CI/CD pipelines, automated testing, monitoring, observability, and production troubleshooting., Collaborate with architects, DevOps engineers, data engineers, frontend developers, and client delivery teams., Communicate technical decisions, trade-offs, risks, and recommendations clearly to both technical and non-technical audiences.] Requirements: Prototypes, AI, Testing, Java, C#, Python, Node.js, TypeScript, REST API, Relational database, Cloud, Azure, AWS, Google Cloud, Security, Git, CD, GitHub, ChatGPT, React, Angular, Vue.js, Kubernetes, Docker, Microservices, Salesforce, Infrastructure as Code, API
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