Senior AI Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 5h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 3d ago
The date the source published, not the day we noticed it (2026-09-28). Last seen at its source 1h ago.
We have tracked this listing since 28 Sep 2026 (3 days). The employer's own board has carried it every time we have read it, most recently 1 hour ago.
Is it remote?
US Remote
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $156.1k–212.5k/yr
Middle 50% of 1272 listings that do state pay — Engineering · Senior · United States · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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greenhouse employer's own board first seen 3d ago · last seen 1h ago
The listing
We’re looking for a Senior AI Engineer to design, build, and deliver production AI/ML systems. This role is ideal for an engineer with several years of experience who can confidently own features end-to-end, contribute to architectural decisions, and bring strong technical judgment to the problems they take on.
In this role, you will work as a key contributor on a cross-functional team, designing and implementing models, building the data pipelines and training workflows around them, and deploying systems to production environments. You’ll be joining real, in-flight work where reliability, performance, and scalability matter. You’ll collaborate with experienced engineers to enhance existing systems, deliver new capabilities, and contribute to the technical decisions that shape how our AI work scales over time.
Why This Role Matters
At Robots & Pencils, we design AI systems for a human world. Our name says it all. Robots and pencils means engineering paired with creativity, because every agent we ship has to work for real people in real workflows. That balance is baked into how we operate.
Every role here contributes directly to that mission. Here, you shape how AI systems integrate into enterprise operations, how teams move at real velocity, and how products create measurable impact for clients and the people they serve. We ship production-ready AI in 30 to 45 days. That pace demands people who take ownership, lead with craft, and care deeply about what they put their name on.
What You’ll Do
Craft & Delivery
- Design, implement, and deploy ML/AI models end-to-end, from concept through production, including data pipelines, training workflows, and optimization for performance, accuracy, and efficiency
- Maintain and evolve AI systems in production, monitoring for drift, debugging issues, and driving ongoing improvements to reliability and scalability
- Bring an AI-forward coding mindset to your daily work, using tools like Claude and Cursor to ship higher-quality work at pace
Collaboration & Communication
- Partner closely with product, engineering, and data teams to align AI work with broader product and business goals
- Translate technical tradeoffs, model behavior, and constraints into terms non-specialists can act on
- Participate actively in code reviews and design discussions, raising concerns and offering constructive feedback
Leadership & Influence
- Contribute to AI architecture decisions with thoughtful perspective on tradeoffs and long-term implications
- Take ownership of meaningful work end-to-end, including the unglamorous parts of getting AI into production
- Raise the bar on engineering practices through your own work and by supporting more junior engineers when opportunities arise
What You’ll Bring
- 4+ years professional software engineering experience, with 2+ years focused on AI/ML systems in production and hands-on experience with generative AI development
- Strong software engineering background (Python or similar)
- Working knowledge of cloud platforms, preferably with in-depth understanding of AWS services and AWS GenAI offerings
- Proven ability to design and ship agentic systems
- Experience with AI frameworks and orchestration tools
- Experience with evaluation frameworks, and observability tools for LLM apps
- Understanding of AI safety, responsible AI principles, prompt injection defenses, and PII handling
- Hands-on experience building RAG pipelines: chunking strategies, embedding models, vector databases
- API development experience, including designing and integrating with internal and third-party services
- Cost optimization expertise: token economics, caching strategies, model routing, quantization
- Working knowledge of Docker and Kubernetes for containerized deployments
- Demonstrable, day-to-day usage and knowledge of AI-forward coding tools such as Claude Code and Cursor
- Strong problem-solving skills and the ability to navigate ambiguous technical challenges with sound judgment
Helpful Extras and Unique Skills
You’ll Do Well Here if You Are
- A doer. You see something broken and fix it. You'd rather move on clarity than wait for certainty.
- A fast learner who knows you don't know everything. The AI landscape changes weekly. You're senior enough to know better and curious enough to keep learning anyway.
- Direct in a way that makes the work better. You give honest feedback. You'd rather have the hard conversation than blow smoke.
- Obsessed with craft. You know genius is in the details. You ship exceptional, not perfect, and you don't put your name on work you wouldn't stand behind.
- Built for ownership. You honor commitments, admit mistakes fast, and back your teammates when a decision costs something. No handoffs, no finger-pointing.