AI Engineer
Indexed description
This role spans the full product lifecycle: discovery, experimentation, application delivery, and deployment. You'll work directly with customers and product teams, own technical calls, and see your product used at scale.
We expect technical rigor, architecture discipline, strong product judgment, and a track record of shipping. In return, you get autonomy and real customer impact.
What You’ll Do
- Design, build, and operate systems in customer-facing production environments
- Translate ambiguous business and customer problems into prototypes & technical specs
- Track AI capabilities and apply them where they create clear leverage
- Own the full application lifecycle: product discovery, experimentation, evaluation, deployment, and monitoring
- Own system design, tradeoffs, and long-term scaling and maintainability
- Build codebases that are legible to agents and other developers; drive the organization forward on tooling.
- Partner with product managers to enhance their product vision, including with AI-native solutions
- Strong applied AI and software engineering fundamentals
- Builders who can span tech, product, and design thinking with high autonomy
- Bias for shipping, iterating, and following customer feedback over polish
- High ownership & agency — measured by outcomes, not deliverables
- Curiosity to improve systems, products, and your own craft
- Python, C#, TypeScript, PostgreSQL;
- Frontier model ecosystems & agent frameworks (e.g., Anthropic, OpenAI)
- Docker, Terraform, and AWS
- 2+ years in software engineering or applied AI
- Experience working with AI development tools in full-stack applications
- Experience designing AI-based solutions to real workflows
- Working knowledge of cloud and frontier AI platforms
- Degree in Computer Science, Engineering, Data Science, or a related field
- Experience operating AI systems in production, with attention to evaluation, cost, and performance tradeoffs
- Background in high-ambiguity environments with proximity to customers (e.g., early-stage startups, forward-deployed engineering, internal product teams)
- Experience in large-scale Python, C#, and TypeScript codebases
- Experience integrating AI solutions into existing, established products.
- Experience working with healthcare, regulated, or sensitive data
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