Senior Full-Stack Engineer - Mental Health Care

ABOUT TRUELOGIC

At Truelogic we are a leading provider of nearshore staff augmentation services headquartered in New York. For over two decades, we’ve been delivering top-tier technology solutions to companies of all sizes, from innovative startups to industry leaders, helping them achieve their digital transformation goals.

Our team of 600+ highly skilled tech professionals, based in Latin America, drives digital disruption by partnering with U.S. companies on their most impactful projects. Whether collaborating with Fortune 500 giants or scaling startups, we deliver results that make a difference.

By applying for this position, you’re taking the first step in joining a dynamic team that values your expertise and aspirations. We aim to align your skills with opportunities that foster exceptional career growth and success while contributing to transformative projects that shape the future.

OUR CLIENT

Our client is a national provider of pediatric mental health for kids, teens, young adults, and their families. They believe whole-family mental health starts with a strong foundation of resilience to cope with whatever life blows your way.

They are revolutionizing the treatment of mental health conditions for kids and teens through a novel data-driven technology platform and evidence-based collaborative care model that enables the first scalable and integrated care solution in mental health. Through coaching, therapy and reduced time to evaluation and treatment by licensed pediatric psychiatry experts, our approach achieves better outcomes and results in happier, healthier kids and teens, while ensuring stigma, cost, and logistics are no longer barriers to care.

Job Summary

The role sits within an AI transformation initiative that supports teams outside the technology organization and finds ways to improve their workflows with AI. Our client is also integrating and re-architecting parts of its platform, so the engineering org is busy and growing. The project duration is for 6 months.

• Reports to: the engineering manager leading this new team, with a Director of Engineering as executive sponsor.
• How work is chosen: the business generates a large list of AI opportunities. Management and stakeholders prioritize them, and the engineer receives a high-level project.
• How work is done: the engineer meets the stakeholders, works out what needs to be built, designs the architecture, builds it, and reports progress to engineering on a daily or weekly basis.
• Project size: varies widely. Some projects take about a week, others about two months. Some are solo, some are paired with another engineer. The engineer moves between teams and projects rather than owning one product for years.
• Solutions vary: an autonomous agent, a web application that connects internal tools, or a microservice. Not every solution includes an LLM; sometimes AI is used in the coding workflow to prototype quickly so users can give feedback early.
• Support: the manager acts as a sounding board, and a platform team supports production deployment.

RESPONSIBILITIES

• Work directly with stakeholders outside engineering to understand their workflows and identify where AI can help.

• Design the architecture of each solution yourself and own it from start to finish: application, infrastructure, tooling and deployment.

• Build and ship AI-enabled internal tools, including integrations between existing systems and, where it fits, LLM-powered features or agents.

• Use AI coding tools to prototype fast, put working versions in front of users, and iterate on their feedback.

• Explain technical decisions and progress in plain language to non-technical stakeholders.

• Report progress to engineering management on a daily or weekly basis and flag gaps early.

• Set up and run your own environments locally, and work with the platform team to take solutions to production.

• Follow our clients' existing data privacy, security, and governance control