Lead AI Engineer

at Bedrock Talent

Remote, remote, lead, full time, USD 1,80,000–2,00,000 / year, 6+ years

posted 22 Jul 2026

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Event-driven systems
Model Context Protocol
Generative AI
LLMOps
Full-stack web application development
LLM
Microservices
Cloud infrastructure
MLOps
AI coding tools
Claude Code
CI/CD
Relational database design

About the role

The Lead AI Engineer will own end-to-end engineering execution, AI/ML system development, and technical leadership during a pivotal stage of the company’s growth.

This person will lead the design and delivery of the company’s AI-first platform, including agent-based architectures, data pipelines, model orchestration, and production systems supporting advanced cohort analysis and longitudinal insight generation.

This is a hands-on builder and technical leadership role. The Lead AI Engineer will translate product requirements, data science models, and scientific frameworks into scalable, secure, and production-ready systems.

The role works closely with Data Science, Product, Operations, Medical, and Research leaders to ensure the platform delivers clinically meaningful, explainable, and high-performing AI-driven insights.

What you would do

PLATFORM AND AGENT-BASED ARCHITECTURE

- Lead the design and implementation of the company’s AI-first platform architecture, including:

- Agent-based systems, such as matching, reasoning, and orchestration agents

- Model orchestration layers and inference pipelines

- Data ingestion, transformation, and feature pipelines

- Build and operationalize systems supporting:

- Proprietary analytical framework execution

- Cohort matching and comparative analysis

- Longitudinal and temporal data analysis

- Ensure systems are modular, extensible, and designed to support future scale

ENGINEERING EXECUTION AND DELIVERY

- Own engineering execution and delivery across product initiatives and company milestones, including work completed with external resources and partners

- Translate product requirements, PRDs, and user stories into clear technical plans and deliverables

- Drive sprint planning, execution, and delivery in close partnership with Product

- Establish a predictable release cadence while balancing speed, quality, and technical debt

- Quickly understand, improve, and take ownership of existing production systems

Read from jobs.ashbyhq.com, last seen 1d ago.

What they are looking for

REQUIRED

- 6+ years of software engineering experience, including full-stack web application development, relational database design, event-driven systems, and cloud-based production environments

- Recent, meaningful experience using AI coding tools and agents, such as Claude Code or comparable platforms

- Bachelor’s or master’s degree in computer science, or equivalent practical experience

- Experience working on highly collaborative, small engineering teams within high-growth startup environments

- Interest in helping lead and mentor a small team while remaining deeply hands-on

- Experience building and productionizing LLM, generative AI, or other AI-driven applications

- Experience in healthcare technology, digital health, or another regulated environment

- Demonstrated success delivering production SaaS or platform-based products

- Strong knowledge of modern software development practices, CI/CD, microservices, cloud infrastructure, and production operations

- Ability to quickly understand and take ownership of existing production systems

- Proven ability to operate effectively amid ambiguity, rapid change, and evolving priorities

- Exceptional communication skills and genuine enthusiasm for working in a mission-driven environment

- Enjoys collaborating closely with Product and Design

- Experience working with Model Context Protocol tools or MCP-based environments

- Familiarity with healthcare security, compliance, and audit requirements

- Experience partnering with Product, Data Science, Medical, or Research teams

- Experience helping a startup scale through the Series A or Series B stage

- Experience with healthcare data sources, including claims, EHR, clinical, genomic, or longitudinal datasets

SUCCESS IN THE FIRST 12–24 MONTHS

- MVP and early product milestones are delivered on time

- The company has a stable and reliable platform supporting early customers

- QA, testing, and release discipline are embedded throughout the engineering lifecycle

- Product, Data Science, Operations, and Engineering work together effectively

- AI and analytical systems are explainable, testable, observable, and production-ready

- The company has strong technical and operational foundations in place for Series A growth

About the role

What you would do

What they are looking for

What comes with it