IMPORTANT: At the moment we are only considering candidates located in Latin America. Please do not apply if you are not located in Latin America.
About Empirical
Empirical empowers early and growth-stage tech companies to create the right products in the right way by providing two pivotal services:
Product & Technology Leadership: Our clients entrust critical decisions to our network of top-tier US-based CTOs and CPOs. We provide fractional, project, or advisory-based support, combining highly experienced talent with a flexible approach.
Product Development Teams: We provide our clients with high-performing, senior product development talent through a scalable staff augmentation model and ongoing support. We focus on Latin America to find exceptional talent, with time zone and cultural compatibility.
We are proud to be a people-first company, where we prioritize building meaningful, long-lasting human connections with clients and team members alike, while embracing diversity and uniqueness.
We are seeking a Staff Full Stack Engineer to join an innovative Startup Studio that is building and scaling AI-native products in highly regulated markets, including healthcare and insurance.
You’ll be working across multiple early-stage portfolio companies—some in stealth mode—on mission-driven platforms that integrate AI, automation, and modern web technologies. This is a hands-on role with high visibility and impact, requiring both technical depth and adaptability. You’ll collaborate closely with design, product, and engineering leads to bring products from concept to launch.
The work spans internal tools, HIPAA-compliant production systems, and greenfield ventures—offering variety, ownership, and opportunities to build reusable components and platform infrastructure that accelerate startup spinouts.
What You’ll Be Doing
Build and maintain AI-powered, full stack applications across a suite of early-stage products
Contribute to internal low-code tools, developer workflows, and reusable frameworks
Work with cross-functional stakeholders to define and deliver scalable technical solutions
Integrate LLMs and agentic workflows (e.g., LangChain, CrewAI) into real-world products
Lead architecture decisions, write high-quality code, and promote engineering best practices
Support secure, compliant deployments in HIPAA-regulated environments using Aptible
Participate in agile ceremonies, code reviews, technical planning, and mentoring
8+ years of professional experience in full stack software engineering
Strong proficiency with TypeScript, Node.js, and React
Experience building and maintaining HIPAA-compliant systems
Familiarity with Aptible or similar HIPAA-compliant cloud platforms
Proficiency with PostgreSQL, Redis, and API design
Experience with Docker and modern CI/CD pipelines
Strong automated testing skills (e.g., Jest, Supertest, or similar)
Ability to work independently in fast-paced, ambiguous environments
Excellent communication skills and fluent English (written and verbal)
Experience working with Startup Studios, early-stage startups, or venture-backed teams
Exposure to agentic AI tools and LLMs (e.g., GPT-4o, Claude, HuggingFace)
Familiarity with LangChain, DSPy, CrewAI, or similar orchestration frameworks
Experience with low-code platforms (e.g., Retool, Make.com, Superblocks)
Knowledge of tools like BullMQ, TypeORM, Zod, Material UI, or ExcelJS
Background in HealthTech, InsurTech, or other regulated B2B2C domains
Familiarity with Medicare or pharmacy workflows is a plus
Remote/flexible work environment
Highly competitive compensation in USD
Long-term, full-time (40 hours/week) engagement
Access to exciting AI-powered projects across multiple verticals
Opportunities for mentorship, learning, and professional growth
A multicultural, values-driven community of senior engineers
Care about people first
Strive to add value always
Lead with integrity
Have fun every step of the way
Empirical is more than a talent network—we’re a trusted partner to founders and innovators. If you’re a senior engineer who loves building real-world products, thrives in early-stage ambiguity, and is excited about the potential of AI in healthcare and beyond, we’d love to connect.
