Senior AI Engineer (Rapid Prototyping & Analytics )

Prompt

4d•Hybrid

About The Position

Prompt is a mission-driven startup looking for an experienced Senior AI Engineer to help push forward an ambitious set of AI initiatives in healthcare, with a particular emphasis on speech and language processing. Prompt delivers highly automated and modern B2B enterprise software to rehab therapy businesses, their teams, and most importantly the patients they serve. We’ve established ourselves as the go-to platform in the space and are rapidly growing our market share by delivering software people love. As we scale, AI is becoming increasingly central to how we build products and how we operate internally. We’re looking for a Sr. AI Engineer who can operate broadly across the team, with a particular strength in designing, evaluating, and monitoring end-to-end AI systems. Comfort choosing, implementing, and improving outcome metrics is essential. This role will contribute to product-facing AI as needed, while also playing a key role in rapidly ideating and developing internal AI tools that improve efficiency, decision-making, and quality across Engineering, Design, Sales, Marketing, Support, Finance, and Operations. This is a high-ownership role focused on iteratively building systems, partnering closely with stakeholders, and ensuring our AI tools deliver real value.

Requirements

4+ years of experience building AI/ML systems in industry or academia, with meaningful production ownership
Strong experience building and operating AI systems end-to-end, not just models in isolation
Strong experience with LLM-based systems (programmatic prompt optimization, evaluation, prompting, structured outputs, RAG, multi-step workflows)
Solid understanding of evaluation and measurement for AI systems (offline metrics, online monitoring, regressions, cost tracking)
Ability to work closely with non-technical stakeholders to translate workflows into effective AI solutions
Strong software engineering fundamentals and ability to ship maintainable, production-grade systems
Track record of benchmarking and iteratively improving accuracy, cost, and latency
Excellent communication skills, with the ability to explain complex AI concepts to non-technical stakeholders
Python (>3.9)
Docker (Basics)
AWS familiarity (S3, RDS, EC2) preferred
Strong problem-solving mindset and ability to operate effectively in ambiguous, fast-paced settings
Willingness to learn and deeply understand the healthcare sector, specifically physical therapy, occupational therapy, and speech therapy
Please only apply if you are interested in a heavy code contribution role; this is not an engineering management position, though growth opportunities exist over time

Nice To Haves

Experience building internal AI tools or platforms used across multiple business functions
Experience designing evaluation harnesses for LLM workflows (golden datasets, regression tests, human review loops)
Experience setting up analytics and dashboards to track AI usage, outcomes, and ROI
Familiarity with workflow automation and business systems (CRMs, support tools, analytics platforms)
Experience with FastAPI, Streamlit, Pydantic, SQLAlchemy, PostgreSQL
Experience with retrieval systems (vector search, hybrid search, grounding and citation strategies)
Experience building healthcare software and/or data processing pipelines

Responsibilities

Drive Prompt’s mission to improve healthcare through modern technology including AI
Lead AI projects from ideation → architecture → production → iteration until tools are widely adopted and loved!
Design, build, and deploy end-to-end AI systems across both traditional ML and LLM-based workflows
Partner with stakeholders across the company to understand workflows, define success criteria, and deliver practical solutions
Supporting internal as well as product-facing AI initiatives as needed
Design and implement evaluation, monitoring, and observability metrics (accuracy, cost, latency, and business impact)
Build guardrails around LLM pipelines including validation and human-in-the-loop workflows
Develop rapid proofs-of-concept and prototypes, then harden them into reliable systems
Help grow and lead the AI team, including training and development of junior team members