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About the Role
This is a hands-on engineering role with strong design responsibility, focused on designing, building, and delivering AI-powered applications that create measurable business impact. You will spend most of your time writing code, integrating systems, and taking solutions to production, while also shaping practical, scalable designs for enterprise-scale operation.
Responsibilities
- Play a lead technical role in designing and delivering AI-enabled solutions across the enterprise.
- Design, develop, and deploy AI-powered applications and workflows.
- Write production-quality code for backend services, APIs, AI orchestration layers, agents, and enterprise integrations.
- Rapidly prototype solutions and iterate them into scalable production systems.
- Own delivery end-to-end: build, test, deploy, monitor, and improve.
- Translate use cases into clear, implementable system designs.
- Make architecture decisions balancing speed of delivery, scalability, reliability, cost, and operational efficiency.
- Define patterns for API-first integrations, AI orchestration, workflows, and reusable services/components.
- Embed LLM capabilities into products, internal tools, and business processes.
- Build and maintain APIs and system integrations.
- Implement agent workflows and orchestration logic to solve operational problems.
- Optimize systems for performance, resilience, and cost efficiency.
- Work directly with stakeholders to understand problems and validate solutions.
- Translate requirements into working software quickly.
- Iterate based on feedback and usage to drive measurable impact.
- Build and contribute to shared libraries, templates, and services.
- Establish practical patterns based on real implementations.
- Help evolve internal platforms through code and working solutions.
- Implement secure and reliable AI solutions, including prompt safety, validation, injection/misuse prevention, and observability/traceability.
- Align implementations with enterprise security, privacy, and compliance requirements.
Requirements
- Proven ability to build and ship production systems at scale.
- Strong experience in backend development and API design.
- Strong experience in cloud-native systems (Azure preferred).
- Strong experience in integration-heavy, distributed applications.
- Comfortable operating in a high-output, hands-on environment.
- Ability to design clean, practical architectures that support real-world constraints.
- Experience making trade-offs across delivery speed vs scalability and simplicity vs flexibility.
- Ability to move fluidly between coding and design thinking.
- Hands-on experience building LLM-powered applications in production.
- Strong understanding of prompt design and evaluation.
- Strong understanding of agent-based workflows and orchestration.
- Strong understanding of integrating AI into production systems.
- Ability to debug, tune, and improve AI behavior in code.
- Bias toward shipping and learning from production usage.
- Comfortable moving from idea → prototype → production.
- Strong ownership: you build it, you run it.
Skills
- AI application engineering
- Orchestration and agent workflows
- Enterprise integrations
- Backend development
- API design
- Cloud-native systems
- Azure
- Distributed applications
- LLM-powered applications
- Prompt design
- Prompt evaluation
- Agent-based workflows
- AI integration
- Debugging AI behavior
- Tuning AI behavior
- Improving AI behavior
Experience Level
- Staff-level
About the Company
- We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.