Senior AI Engineer

• Design, build, and maintain backend services for GenAI and agent-based applications using Python 

• Develop APIs and services using FastAPI 

• Build and support AI solutions using the agentic framework 

• Design and integrate agent workflows, tool usage, orchestration, and workflow management patterns 

• Build and maintain services using PostgreSQL, Cosmos DB, and/or SQL Server 

• Containerize and deploy applications using Docker and Kubernetes 

• Develop secure, scalable, and production-ready AI systems on Azure 

• Build agentic harnesses, test frameworks, and evaluation pipelines 

• Implement observability, monitoring, logging, and quality checks for AI systems 

• Collaborate with cross-functional teams to deliver enterprise AI solutions 

• Use modern engineering tools and workflows including Azure DevOps (ADO), GitHub, Claude Code, Cowork, and automation-friendly development practices 

• Ensure adherence to Responsible AI, security, privacy, and governance requirements 

• Support document intelligence, OCR, and data processing workflows where needed 

Qualifications & Experience 

• 6+ years of software engineering experience, especially Python 

• 2+ years in GenAI, LLM, or agentic application development 

• Experience in enterprise or production AI environments preferred 

• Experience building backend services and APIs with FastAPI 

• Hands-on experience supporting or building GenAI / LLM-based applications 

• Experience with agent orchestration frameworks 

• Experience with Azure cloud resources and cloud-native application development 

• Experience with one or more databases: Postgres, Cosmos DB, SQL Server 

• Experience with Docker and Kubernetes 

• Experience with ADO, GitHub, and modern CI/CD workflows 

• Strong understanding of backend architecture, testing, debugging, and performance optimization 

• Experience with agentic engineering and agent-based solutions 

• Understands evals / evaluation frameworks 

• Strong understanding of secure design for AI systems, including access control, data handling, prompt safety, and system reliability 

• Experience integrating tools, APIs, and structured workflows into AI applications 

• Experience with workflow management and orchestration in enterprise environments 

• Strong understanding of MCP, SKILLS, plugins, tool calling, or reusable agent capabilities 

• Experience with OCR, document extraction, or document intelligence solutions 

• Experience with data wrangling, preprocessing, and unstructured data pipelines 

• Experience with RAG, search, retrieval pipelines, or knowledge integration 

• Knowledgeable about working with multi-agent systems 

• Familiarity with AI-assisted developer workflows and coding tools