Engineering Manager
Listed on 2026-07-11
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Software Development
AI Engineer (Applied/Software), Software Architect, Backend Developer
Pelago is the leading specialty substance use care provider, built on the belief that effective treatment means matching care intensity to what each member actually needs rather than defaulting to the most expensive intervention. Our programs guide members through every stage of the substance use spectrum, from unhealthy habits to active use disorders, delivering personalized treatment for tobacco, alcohol, opioid, cannabis, and stimulant use based on individual health, habits, genetics, and goals.
With Sona, our voice‑first AI Mental Health Specialist, Pelago now applies that same clinically‑driven model to mental health, pairing deep clinical expertise with technology to expand access without compromising care quality. Technology should make clinical care more precise and more human, not replace the judgment behind it.
Our engineering team operates as empowered, outcome‑oriented problem solvers, working in close partnership with product, design, and clinical teams to improve member outcomes AI transforms how software is built, we are intentionally evolving our development lifecycle so we spend less time on mechanical implementation and more time on system design, judgement, and impact.
How We Work- Outcome‑driven:
Engineers are given problems to solve, not just features to build. Success is measured by learning, impact, and outcomes—not velocity alone. - AI‑native:
We use AI across the SDLC to accelerate implementation, testing, and review. Engineers focus on defining intent, validating behaviour, and designing resilient systems. - High autonomy, high accountability:
Teams have real ownership over their domains. With autonomy comes responsibility for quality, safety, and results. - Cross‑functional by default:
Engineers partner deeply with Product, Design, Data, and Clinical. Discovery, experimentation, and delivery are shared responsibilities. - Quality and safety matter:
We build in a regulated, member‑impacting domain. Reliability, observability, and correctness are first‑class concerns.
Instead of task lists, anchor on ownership:
- Own meaningful problem spaces end‑to‑end, from discovery through delivery and iteration.
- Design and evolve systems that support safe, scalable, AI‑augmented development.
- Use data and experimentation to validate whether solutions actually work.
- Collaborate cross‑functionally to balance member impact, clinical constraints, and technical tradeoffs.
- Shape how we work—our tools, processes, and culture.
We explicitly assess for empowerment:
- You start with "why" before diving into "how".
- You're energized by ambiguity and collaborative problem‑shaping.
- You use AI to amplify your judgement and move faster on what matters.
- You think in systems and anticipate second‑order effects.
- You want to own outcomes, not just ship features.
The Role
Pelago is looking for an Engineering Manager to lead and grow a high‑performing team building AI‑native products that improve outcomes for people living with substance use challenges. You’ll lead from the front: pairing with engineers, architecting systems, and setting a high bar for technical excellence and curiosity across the team. You will be in the trenches with them, prototyping, debugging, and helping turn ambitious product ideas into robust, user‑facing features.
InThis Role You Will
- Lead and grow a high‑autonomy, high‑accountability engineering team, mentoring engineers and fostering a culture of ownership, curiosity, and excellence.
- Lead from the front as a hands‑on builder, pairing with engineers to prototype, debug, and deliver robust, user‑facing product experiences.
- Drive end‑to‑end execution of AI initiatives, from rapid experimentation through secure, reliable production deployment with a high bar for quality and trust.
- Help grow and strengthen our NYC engineering presence while collaborating closely with our London team, serving as a culture carrier and talent magnet as Pelago scales globally.
- Shift the team from output to outcomes, framing ambiguous problem spaces, running fast learning loops, and ensuring work is measured by real member and business impact.
- Set technical direction…
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