Senior AI Platform Engineer: Backend & Agentic Systems

Seeq Corporation

United States

Remote

USD 188,000 - 220,000

Full time

9 days ago

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Benefits offered by this job

Competitive salary, equity, and cash

Unlimited PTO

Internet and mobile phone reimbursese

Annual company meetups

4-week paid sabbatical every 7 years

Vacation bonus program

Generous home office allowance

The best co-workers

Pet-friendly workspace

A job you'll love!

Job summary

Seeq Corporation is hiring an AI Software Engineer to shape and scale backend platforms and agentic AI systems for enterprise analytics applications. This senior, hands-on role requires leading ambiguous initiatives, setting architectural direction, and delivering production-ready software.

You will work remotely with a global team, collaborating with customers during early deployments, mentoring engineers, and building reusable platform capabilities to enable multiple teams to deploy AI

Qualifications

10+ years of professional software engineering at staff or equivalent scope.
Recent focus on generative AI or agentic systems.
Proven track record leading complex AI/platform initiatives.
Hands-on experience building agentic systems including routing, tool use and sandboxing.
Deep expertise in Python and backend engineering for large-scale distributed systems.
Experience designing shared platform services and APIs used by multiple teams.
Experience with modern AI/LLM frameworks and orchestration tooling.
Experience developing evaluation and observability for AI/agentic systems.
Familiarity with SQL and PostgreSQL.
Experience deploying production systems in Kubernetes.

Responsibilities

Set architecture and patterns for scalable AI backend and platform.
Lead high-impact AI/platform initiatives from concept to production.
Architect agentic systems including routing, tool use, evaluations, runtimes, sandboxing.
Build shared platform infrastructure and APIs used by multiple teams.
Develop reliable distributed and data-intensive backend services.
Create reusable AI platform capabilities for multi-team deployment.
Define evaluation, monitoring, and reliability strategies for AI systems.
Design integrations with internal services and third-party platforms.
Translate emerging AI tech into pragmatic production software.
Collaborate with customers during early deployments and mentor engineers.