The Senior Agentic Engineer (Client Apps) will design, build, and productionize AI-assisted and agentic capabilities across client applications, turning customer and service journeys into reliable tool-using workflows. They will integrate LLMs, retrieval/context patterns, backend APIs, analytics, and monitoring into performant mobile and web experiences while maintaining strong engineering discipline across testing, observability, release controls, and guardrails. This role also champions continuous improvement through reusable agentic patterns, evaluation practices, and adoption of emerging AI and client-app engineering best practices.
Key Responsibilities
Design, develop, and maintain agentic features for client applications using LLMs, tool/function calling, workflow orchestration, and app integrations.
Translate customer and service journeys into AI-assisted experiences across mobile and web channels while preserving usability, accessibility, and performance.
- Implement prompt, context, memory, and retrieval patterns with controlled data access, reusable components, and clear ownership boundaries.
- Integrate agent workflows with REST APIs, GraphQL, Firebase, backend services, analytics platforms, and enterprise systems.
- Build efficient, reusable, and testable client-app and orchestration code while adhering to clean architecture and secure engineering practices.
- Establish and manage release pipelines for AI-enabled features, including configuration, prompt, model, and workflow changes.
- Implement and maintain automated tests and AI evaluation workflows for prompts, tools, API contracts, regression scenarios, and user journeys.
- Apply guardrails, fallback paths, human-in-the-loop controls, and monitoring to manage AI quality, safety, latency, and cost.
- Optimize client-app performance, model/tool latency, observability, crash reporting, analytics, and real-user monitoring post-launch.
- Stay updated with emerging trends in agentic AI, LLM application development, and client-app engineering best practices.
Required Qualifications
- Proven experience (2+ years) building production software for client-facing applications, with hands-on exposure to AI/LLM, automation, or agentic workflow delivery.
- Strong engineering foundation in Flutter/Dart, iOS/Android, or modern web client application development.
- Working knowledge of LLM APIs, prompt engineering, tool/function calling, structured outputs, retrieval-augmented generation, or context design.
- Strong knowledge of Firebase, REST APIs, GraphQL, backend integration, and secure data handling for client applications.
- Hands-on experience with CI/CD pipelines, automated testing, and AI evaluation or regression-testing practices.
- Familiarity with observability and performance tools such as OpenTelemetry, RUM, crash reporting, analytics, or similar platforms.
- Abilityto work with cloud-hosted services, orchestration platforms, or infrastructure patterns such as AWS, Kubernetes, queues, or serverless workflows.
Preferred Skills
- Experience with agent frameworks, workflow orchestration, RAG pipelines, evaluation harnesses, or production LLM application patterns.
- Knowledge of AI guardrails, privacy/security controls, human-in-the-loop flows, and operational risk management for AI-enabled products.
- Familiarity with Agile delivery, cross-functional collaboration, and translating product/service requirements into production-ready technical designs.
