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Principal Software Engineer - AI Engineer

USA💼 Full-time💰 $61,000–$101,000🗓 2026-07-14 → 2026-07-17

Core

Designing and implementing agentic AI reference architectures, production-grade Python code, and LLM-powered APIs/microservices for internal productivity and business solutions.

Role type

Principal Software Engineer - AI Engineer

Builds

Agentic AI reference architectures, reusable components (prompt management, evaluators, safety filters, connectors, embedding pipelines, memory stores), and LLM-powered APIs/microservices.

Domain

Financial services / Agentic AI / LLM engineering

Deliverable

production ML models | product features | infrastructure

Required skills

Python engineering, PyTorch or TensorFlow, vector storage systems, agent memory design, long-running autonomous agents, LLM-based service deployment, MLOps (CI/CD, monitoring, incident response, model governance), cloud-native AI deployment (AWS/Azure), responsible AI practices, human-in-the-loop validation, secure data handling.

Preferred skills

fine-tuning, adapters, custom evaluation frameworks, operating AI systems in regulated environments (finance/healthcare), prompt engineering, LLM orchestration, safety filters, audit logging, explainability, mentoring senior engineers, influencing technical roadmaps.

Technologies

AWS, Azure, PyTorch, TensorFlow, Python, microservices

Responsibilities

Design and implement agentic AI reference architectures including orchestration, retrieval, memory, guardrails, and evaluation harnesses; write production-grade Python code and review critical-path code; build reusable components for prompt management, evaluators, safety filters, connectors, embedding pipelines, and memory stores; develop and operate LLM-powered APIs and microservices; own the full ML lifecycle including experimentation, CI/CD, automated testing, monitoring, drift detection, versioning, and rollback; optimize inference for latency, throughput, caching, batching, model selection, and cost per inference; partner with data teams on structured and unstructured pipelines, document ingestion, metadata, and access controls; set engineering standards for agentic AI systems and lead design reviews; influence roadmap direction and priorities; architect and govern agentic AI-enabled engineering workflows; hire, lead, and mentor a team of machine learning and software engineers.

Seniority

Principal, hands-on IC with mentorship and strategy

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