Note: The job is a remote job and is open to candidates in USA. Albano Systems, Inc. is seeking a Generative AI Engineer to join its AI Technology Platform and Solutions team within Enterprise Architecture. The role designs, builds, evaluates, and operates production AI systems, including agentic workflows and retrieval-augmented generation pipelines, while developing reusable components and ensuring security, governance, reliability, observability, and responsible AI readiness.
Responsibilities
- Design, build, and operate agentic workflows, retrieval-augmented generation pipelines, and tool-calling systems using LangGraph, LangChain, and related frameworks, taking them from prototype to production
- Build end-to-end AI solutions, including data models, integrations, services, model and agent components, and user-facing experiences needed to deliver business value
- Apply the right technical approach for each problem, using agentic workflows, targeted model calls, or deterministic software based on value, risk, and fit
- Build and maintain evaluation harnesses, test datasets, and regression suites for prompts, models, and agents, and define acceptance thresholds and production-readiness criteria before go-live, building for auditability, traceability, and responsible adoption
- Instrument AI systems with tracing and monitoring for quality, token cost, and latency, and tune them for cost and performance in production
- Build security, privacy, data governance, responsible AI, reliability, observability, and supportability into solutions from the start, partnering with control and platform teams to meet production requirements
Skills
- • 4+ years of professional software engineering experience, including 2+ years of hands-on experience building LLM-based systems in production, spanning prompt and context design, retrieval-augmented generation, tool use including Model Context Protocol (MCP), and agent orchestration with LangGraph and LangChain (or an equivalent framework such as Semantic Kernel or Microsoft Agent Framework)
- • Production depth in stateful, multi-step agent workflows, including state management, human-in-the-loop checkpoints, error handling, and recovery
- • Experience building evaluation and observability for LLM systems, such as test datasets, automated and LLM-as-judge evaluations, and tracing with LangSmith or an equivalent tool
- • Strong Python skills and hands-on development experience across enterprise services and modern web applications. Experience with C#/.NET, TypeScript, and React or Angular is also relevant
- • Cloud-native architecture experience on Azure across compute, data, integration, identity, and AI services, including the tradeoffs among them
- • Event-driven architecture, microservices, API-first platform design, or data platform experience such as Databricks or Fabric
- • Insurance domain knowledge across underwriting, submission intake, policy administration, claims, or reinsurance, or delivery experience in another regulated industry such as healthcare or financial services where auditability was a first-class requirement
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