Senior Engineer, AI & Agentic Development
Listed on 2026-06-10
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Software Development
AI Engineer (Applied/Software), Cloud Engineer - Software, Software Engineer, DevOps
About the Role
We are hiring a Senior Engineer to build AI-powered and agentic features across Stav Pay. You will work closely with the Staff Engineer who leads AI technical direction, and take ownership of designing, building, and shipping features that bring intelligent automation to financial operations workflows.
This is a hands‑on building role. You will write production code daily—prompt chains, agent workflows, RAG pipelines, API integrations, and frontend components—while also contributing to architectural decisions, evaluation frameworks, and engineering standards for AI features.
You will work across the full stack:
Python on the backend, Angular on the frontend, and LLM orchestration in between, integrating with existing platform services built in C# / .NET. You should be comfortable moving between these layers and making pragmatic decisions about where and how AI fits into existing product workflows.
You will work across the following stack. You don’t need deep expertise in every layer, but you should be comfortable working in a polyglot codebase and building features that span multiple technologies.
- Cloud - Microsoft Azure (App Services, Functions, Storage, Service Bus, Key Vault)
- Backend - Python (primarily for AI features); existing platform services in C# / .NET/Python
- Frontend - Angular / Type Script
- Database - SQL Server
- Architecture - Containerized microservices (Docker, Azure Container Apps / AKS) and Azure App Services
- Dev Ops - Azure Dev Ops (CI/CD pipelines, repos, boards)
- AI Tooling - Claude and Codex CLI and Cursor for agentic development workflows
- Integrations - MCP servers, REST APIs, file-based feeds (NACHA, ISO 20022, SWIFT), OCR/email ingestion
- Build AI-powered product features end-to-end: from prompt engineering and model integration through API development, data handling, and frontend delivery.
- Develop and iterate on prompt chains, RAG pipelines, and multi-step agent workflows for financial operations use cases such as invoice processing, approval routing, anomaly detection, and natural-language queries.
- Implement and maintain the integration layer between LLM providers (Anthropic, OpenAI, etc.) and Stav Pay’s backend—handling model calls, error recovery, cost tracking, and latency optimization.
- Build evaluation and testing infrastructure for AI outputs: automated quality scoring, regression detection, and production monitoring.
- Build and maintain MCP (Model Context Protocol) servers that expose Stav Pay’s capabilities as tools for AI agents and external platforms.
- Implement agent orchestration patterns: tool selection, context management, memory, and guardrails for autonomous financial workflows.
- Build human‑in‑the‑loop controls, approval gates, and escalation paths that make agentic workflows safe for production financial operations.
- Develop reusable components and libraries that accelerate AI feature development across the team.
- Write clean, well‑tested, production‑grade code. Maintain high standards for reliability, observability, and security in AI‑driven features.
- Contribute to technical design discussions, RFCs, and architectural decisions for AI systems.
- Participate in code reviews with a focus on AI‑specific concerns: prompt quality, model output handling, safety, and cost efficiency.
- Collaborate with product, design, and the implementation team to translate client workflows and pain points into well‑scoped AI features.
- Work with security and compliance to ensure AI features meet regulatory requirements for financial data handling and auditability.
- 5+ years of professional software engineering experience building production systems.
- 2+ years of hands‑on experience building AI/ML‑powered product features that shipped to real users, including 6+ months on LLM‑based features.
- Solid experience with LLM integration: prompt engineering, function/tool calling, RAG architectures, and agent workflows.
- Strong software engineering fundamentals: API design, data modeling, testing, and production operations.
- Proficiency in Python. Working…
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