Senior Applied AI Engineer — Agent Platform (Remote)

eBSI Export Academy; United States; Remote; USD 220,000 - 250,000; Full time

Benefits offered by this job

Company-subsidized medical, dental, &

401(k) match plans

Annual bonus

Flexible PTO

Job summary

PrizePicks is building an Applied AI engineering team to convert ML/LLMs into reliable product capabilities. This senior IC role focuses on building and shipping an agent platform, tooling, and production AI features across the software lifecycle.

You’ll partner with product, design, and data/ML teams to operationalize AI, implement guardrails, and raise engineering standards while shaping AI strategy for the platform. Remote-friendly across the U.S.

Qualifications

• 6+ years of professional software engineering experience.
• Direct experience on an Applied AI/product AI team building LLM- or ML-powered features.
• Demonstrated judgment in agent-driven development: knowing what to delegate and how to scope.
• Strong backend/system design skills: APIs, distributed systems, queues/workflows, observability.
• Comfort navigating ambiguity and driving outcomes with cross-functional partners.
• Track record of mentoring peers and elevating engineering quality.

Responsibilities

• Build the agent platform and tooling for AI-enabled features.
• Design primitives like orchestration, tool calling, evaluation harnesses, tracing and safety guards.
• Operationalize AI across the SDLC and integrate with day-to-day engineering workflows.
• Partner with product/design/data to deliver customer-facing AI outcomes.
• Own prototypes through production: data needs, system design, rollout plans, monitoring and iteration.

Skills

Backend design

Distributed systems

APIs

Observability

Performance

Mentoring peers

Engineering leadership

Job description

PrizePicks is building an Applied AI engineering team to convert ML/LLMs into reliable product capabilities. This senior IC role focuses on building and shipping an agent platform, tooling, and production AI features across the software lifecycle.

You’ll partner with product, design, and data/ML teams to operationalize AI, implement guardrails, and raise engineering standards while shaping AI strategy for the platform. Remote-friendly across the U.S.