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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Engineering Manager, AI Platform - **Company:** SEQUENCING LLC - **Location:** United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Bioinformatics, Mobile Application Development, Cloud Computing, Configuration Management, Data Systems, Distributed Systems, Rapid Prototyping Process, Software Engineering, Large Language Models, Generative AI, AI Platforms, Data Management, Data Pipelines - **Published:** August 24, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=6dbed2521e61c784 ## About the Role * You have 8+ years of software engineering experience, including 3+ years managing or leading high-performing engineering teams. * You have at least 2 years of experience building production LLM, generative-AI, or agentic products. * You have designed or shipped systems involving tool use, orchestration, memory, retrieval, prompts or skills, evaluation loops, and human review. * You are technically credible across distributed systems, data pipelines, APIs, cloud infrastructure, and production reliability. * You can engage deeply on system design and failure modes while empowering senior engineers to own architecture and implementation. * You have built strong engineering cultures grounded in ownership, growth mindset, direct feedback, and continuous improvement. * You are comfortable operating in the POC and MVP phase, learning through prototypes, and evolving systems toward production scale. * You know how to balance speed with guardrails, particularly when system outputs affect health decisions or other high-consequence outcomes. * You communicate clearly across Engineering, Product, Bioinformatics, Design, and Customer Success. * You are based in the United States and comfortable operating autonomously in a fast-moving, fully remote environment. Helpful experience * Healthcare, genomics, or another regulated and high-consequence domain. * Consumer conversational products or longitudinal personalization. * Evaluation infrastructure, prompt management, agent observability, or human-in-the-loop systems. * Data platforms, developer platforms, or internal tooling. * Leading remote teams across multiple disciplines and time zones. ## Description As Engineering Manager, AI Platform, you will lead the engineering team building the connected intelligence system behind Sequencing's current and future AI-powered products. Reporting to the Senior Director, AI & Emerging Technologies, you will turn clear product direction into focused engineering execution across data, retrieval, memory, integrations, agent orchestration, evaluation, observability, and reliability. This is a technically engaged engineering leadership role. You will manage and develop engineers, help the team break ambiguous problems into shippable increments, and act as a credible technical partner without becoming a bottleneck or displacing engineering ownership. You should be comfortable moving quickly through prototype and MVP stages while building the guardrails required for a high-consequence health product. What you'll own * Lead, coach, and develop the engineers responsible for Sequencing's AI platform, creating clear ownership, tight feedback loops, and a high bar for technical quality. * Translate approved product intent into sequenced engineering plans with clear owners, dependencies, risks, test criteria, and completion gates. * Guide delivery across retrieval, memory, integrations, prompts and skills, agent orchestration, evaluation, observability, and supporting data systems. * Partner with engineers and architecture owners on system design, technical tradeoffs, and boundaries between deterministic and probabilistic components. * Build a rapid prototype-to-production loop that allows the team to learn quickly without compromising scientific accuracy, privacy, reliability, or maintainability. * Establish evaluation as a release gate using deterministic validation, golden sets, LLM-as-judge methods, human annotation, scientific review, and clearly defined failure behavior. * Improve prompt and configuration management, trace quality, latency, cost visibility, failure classification, and production observability. * Create guardrails that enable engineers to move with autonomy, use AI-native development tools effectively, and take end-to-end ownership of their work. * Partner closely with Product, Bioinformatics, Design, Customer Success, and other engineering teams to turn reusable platform capabilities into polished member and partner experiences. * Help the platform mature from an early agentic system into reliable infrastructure that can support multiple products and surfaces across Sequencing. ## Related Videos - [This App Reached 10,000 Users in One Week. 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