Senior Applied AI Engineer – Enterprise Systems
About The Position
At TubeScience, we build software systems that combine AI, engineering, and automation to solve complex operational problems at scale. We’re looking for an engineer who has evolved from systems engineering into applied AI—someone who enjoys designing reliable production systems, integrating modern AI capabilities, and owning them in production. This is an internal Forward Deployed Engineering role. Rather than building products for external customers, you’ll work directly with internal stakeholders to identify operational bottlenecks, architect AI-powered solutions, deploy them rapidly, and continuously improve them based on real business needs. This is not an AI research or model-training position. We apply state-of-the-art AI models to solve enterprise problems through software engineering.
Requirements
- 3–6+ years of professional software or systems engineering experience.
- Experience building and operating production software used by real users or internal business teams.
- Strong Python engineering experience.
- Experience integrating modern LLMs into production systems using frameworks such as OpenAI, Anthropic, LangGraph, MCP, or similar.
- Experience designing systems that coordinate multiple APIs, databases, services, and enterprise applications.
- Strong understanding of distributed systems, debugging, logging, monitoring, and production operations.
- Experience deploying, operating, troubleshooting, and improving production systems after launch.
- Strong architectural thinking with the ability to design complete end-to-end solutions.
- Comfort working independently in a fast-paced startup environment.
Nice To Haves
- Multi-agent systems
- LangGraph, MCP, Temporal, or similar orchestration frameworks
- Event-driven architectures
- Docker and Kubernetes
- AWS, GCP, or Azure
- CI/CD pipelines
- Observability platforms (Datadog, Grafana, OpenTelemetry, etc.)
- Internal developer platforms
- Enterprise integrations
- Experience at a large technology company building production systems is highly valued.
Responsibilities
- Own the design, implementation, deployment, and operation of AI-powered enterprise systems that automate business processes across the company.
- Design and build production AI applications that automate complex enterprise workflows.
- Architect agent-based systems that coordinate LLMs, APIs, internal services, databases, and business logic.
- Build reliable orchestration layers that integrate multiple tools and enterprise platforms.
- Deploy production-ready AI systems with observability, monitoring, rollback strategies, and operational safeguards.
- Investigate production issues, analyze logs, debug failures, and restore system reliability when incidents occur.
- Design scalable architectures that prioritize maintainability, resiliency, and operational excellence.
- Partner closely with Product, Operations, Creative, Engineering, and Business teams to identify high-impact automation opportunities.
- Rapidly prototype, validate, deploy, and iterate solutions based on production performance and business outcomes.
- Continuously improve existing AI systems for reliability, speed, and business impact.
Benefits
- High-impact internal systems where your software is deployed quickly, used daily across the business, and has measurable operational impact.
- Engineers who take ownership from architecture through production, iterate rapidly, and continuously improve the systems they build.
- Applying AI to solve real enterprise problems—and owning those systems long after deployment.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
