This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a AI Infrastructure / Product Engineer, Mid-Level based in United States.
Join a distributed engineering team working at the intersection of AI research and product development.
You’ll transform experimental AI capabilities into reliable, production-ready products for legal workflows.
The role combines AI evaluation, backend engineering, cloud infrastructure, and product development.
You’ll build systems that measure accuracy, hallucinations, retrieval quality, latency, and cost.
You’ll also turn research prototypes into practical retrieval, drafting, document, and agent workflows.
Working closely with researchers and product stakeholders, you’ll help move applied AI from experimentation into production.
This is an opportunity to have meaningful technical impact in a fast-moving, AI-focused environment.
Accountabilities:
- Build repeatable benchmarks and evaluation pipelines that measure AI system performance across accuracy, hallucinations, retrieval quality, latency, and cost.
- Develop dashboards and monitoring systems that make changes in system performance visible and actionable for engineering and research teams.
- Transform experimental AI and research prototypes into maintainable product capabilities, including retrieval, drafting, document-processing, and agent-based workflows.
- Design and maintain backend services, APIs, internal tools, and deployment systems that support testing, iteration, and reliable product releases.
- Deploy and operate cloud infrastructure, including databases, monitoring, delivery pipelines, and other systems required for dependable production operations.
- Collaborate closely with AI research teams to translate experiments and emerging capabilities into robust technical solutions while remaining aligned with product and user needs.
- Contribute across the engineering stack as needed, helping bridge infrastructure, backend, AI systems, and product development.
Requirements
- 3+ years of professional experience as a software, infrastructure, or product engineer building and deploying production systems.
- Strong Python development skills combined with hands-on experience deploying and operating applications in cloud environments.
- Demonstrated experience creating evaluation pipelines, benchmarks, or assessment frameworks for machine learning or AI systems.
- Practical experience with APIs, databases, backend services, deployment pipelines, dashboards, and monitoring systems.
- Ability to take experimental code, ambiguous requirements, or early-stage ideas and turn them into maintainable, production-quality products.
- Interest or hands-on experience with LLMs, retrieval-augmented generation, AI agents, AI benchmarking, or document automation.
- Full-stack development experience is a plus, with familiarity with technologies such as FastAPI, Docker, React, Next.js, Postgres, or vector databases considered beneficial.
- Strong collaboration, problem-solving, and communication skills, with the ability to work effectively across research, engineering, and product functions.
Benefits
- Annual base salary of $180,000–$260,000 USD, depending on relevant skills, experience, and role scope.
- Full-time, fully remote position within the United States.
- Opportunity to work at the intersection of AI research, infrastructure, and product engineering.
- Exposure to applied AI technologies including LLMs, retrieval systems, agents, evaluation frameworks, and document automation.
- Opportunity to help transform experimental AI capabilities into reliable products used in real-world legal workflows.
- Visa sponsorship is not available for this position.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
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