Software Engineer III - Python LLM Engineer

About the job

Responsibilities

• Design and build agentic AI workflows for multi-step reasoning, tool orchestration, and task execution, including fallback behavior and human approvals.
• Develop and productionize LLM-powered applications like conversational interfaces, intelligent search, and summarization services.
• Implement patterns for tool integration (APIs, internal services, data sources) with authentication, authorization, audit logging, and least-privilege access.
• Build and maintain RAG components (ingestion, indexing, retrieval, grounding/citations, reranking) and tune for quality and latency.
• Produce architecture/design artifacts for distributed systems, covering service boundaries, data flows, scalability, resiliency, and non-functional requirements.
• Establish evaluation and monitoring processes, including offline test sets, automated regression checks, prompt/version management, hallucination/grounding checks, and runtime observability.
• Apply data engineering/analytics skills for AI features, including data cleaning, normalization, deduplication, exploratory analysis, and KPI reporting.
• Leverage enterprise-authorized AI coding assist tools to improve code quality, delivery speed, and productivity, validating outputs through peer review and automated testing.
• Apply knowledge of the Software Development Life Cycle toolchain, including AI-assisted development and automation capabilities, to enhance value realization.
• Collaborate with product, design, and stakeholders to translate requirements into technical solutions, delivery plans, and iterative releases, ensuring security, privacy, and responsible AI expectations are met.
• Mentor engineers and contribute to shared standards, reusable components, and engineering best practices across AI delivery.

Requirements

• Formal training or certification on software engineering concepts and 3+ years of applied experience.
• Experience in software engineering, including delivering production applications and services.
• Strong proficiency in Python and experience with APIs/microservices.
• Hands-on experience building LLM/RAG/agentic applications (prompting, structured outputs, tool/function calling, state management, error handling).
• Familiarity with agent frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or similar.
• Working knowledge of data handling basics: data cleaning, joins/aggregations, simple statistics, exploratory analysis; comfortable with SQL and/or pandas-style workflows.
• Experience with cloud platforms (AWS or Azure), CI/CD, observability, and operational reliability practices.
• Hands-on experience using enterprise-authorized AI-assisted software development tools, with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs.
• Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs/outputs, and adherence to resiliency and security expectations.
• Strong understanding of secure development practices and validation of AI outputs (correctness, performance, and security).
• Familiarity with vector search and retrieval tuning (embeddings, reranking, query rewriting).
• Experience working in regulated environments or building applications with strict audit/security requirements.