AI Systems Engineer

ABC Legal Services•Seattle, WA

About The Position

ABC is hiring an AI Systems Engineer to design and stabilize the end-to-end AI systems so that complex video processing and compliance workflows are reliable, auditable, and scalable, while safely integrating multiple AWS AI services, rules, and human review into a single production-ready platform.

Requirements

4+ years of experience in backend or systems engineering, with strong proficiency in Python.
Experience designing, building, and operating AWS-based, event-driven systems (e.g., Lambda, Step Functions, S3).
Hands-on experience integrating AI services such as transcription, computer vision, and large language models into production systems.
Experience managing model and prompt lifecycles, including versioning, evaluation, and iteration.
Strong understanding of monitoring, reliability, security, and operational best practices for production systems.
Ability to collaborate closely with product, compliance, and operations partners in regulated or high-risk environments.

Nice To Haves

Experience with ML Ops or AI systems engineering in production environments.
Familiarity with regulated industries such as legal, compliance, healthcare, or financial services.
Experience working with vector databases, embeddings, and similarity search.
Exposure to LLM frameworks or local inference tools (e.g., Ollama or similar).
Experience with observability tooling, CI/CD pipelines, and infrastructure-as-code practices.
Prior work on ethical, auditable, or governance-focused AI systems.

Responsibilities

Design and build end-to-end AI systems by integrating models, rules, and data pipelines into reliable, auditable workflows that support compliance and training needs.
Manage the full lifecycle of AI components including models, prompts, and datasets—covering versioning, deployment, monitoring, rollback, and documentation.
Ensure system reliability, observability, and security through monitoring, alerting, access controls, and privacy-conscious data handling.
Collaborate closely with product and engineering partners to translate product goals into technical architectures, evaluation pipelines, and responsible AI practices.