About the job
In just under a year, strala-ai has achieved impressive multi seven-figure ARR and is experiencing rapid growth at 50% month-over-month. We are backed by top-tier investors, including Peter Thiel’s Founders Fund, and led by partners with strong ties to OpenAI, Cognition, and Scale AI. Our talented team hails from prestigious institutions such as Harvard, Berkeley, and Oxford, and includes professionals from leading firms like Optiver, AMD, and Palantir, many with backgrounds in ICPC and NeurIPS.
Key Responsibilities:
- Lead the deployment of multi-modal, agentic AI systems in production, ensuring significant business outcomes. You will manage client deployments from start to finish, being the key liaison for senior client stakeholders.
- Develop and nurture client relationships by understanding their challenges and aligning on priorities, establishing yourself as the trusted advisor for AI adoption.
- Create, build, and enhance AI agents that optimize claims outcomes through prompt engineering, model integration, and rapid prototyping using AI-assisted coding tools.
- Engage with applied AI daily, scoping and developing new features to support our customers in scaling and improving claims results.
- Integrate our solutions into client environments, collaborating directly with their technical teams on APIs and systems.
- Coordinate with our core platform team to facilitate smooth delivery, providing actionable insights for product enhancement.
- Document and share best practices in internal playbooks to scale our Forward Deployed Engineering efforts effectively.
Ideal Candidate:
- Exhibit a founder's mindset, taking ownership of challenges, acting swiftly, and finding solutions, whether that means engaging in client calls or executing quick integrations.
- Possess over 2 years of experience in a role that merges technical expertise with client-facing responsibilities (e.g., agent engineering, forward deployed engineering, growth engineer, or founding engineer/founder).
- Demonstrate a strong technical foundation with proficiency in Python, APIs, cloud platforms, and modern AI/ML tools.
- Familiarity with LLMs, prompt engineering, and agentic AI concepts, as well as comfortability with AI-assisted development workflows for rapid solution delivery.
- Excel in articulating complex concepts to non-technical stakeholders.

