Engineering Manager, AI Platform (Hands-On)

Engineering Manager, AI Platforms (Hands-On) Boston, MA Onsite 4 days per week Role Summary Our client's AI Studio is seeking a hands-on Engineering Manager to lead the engineering execution of their AI systems and platform services. This role combines technical leadership, people management, and hands-on engineering. You will manage a team of AI engineers (U.S. and India) while contributing directly to architecture, code, and delivery of production AI systems. You will focus on raising engineering rigor, improving system architecture quality, ensuring scalable, reliable AI services, and driving consistent delivery execution. This role reports to the VP, Artificial Intelligence, and partners closely with Product and Domain leaders. Scope of Responsibility:Engineering execution qualityPlatform architecture implementationTeam technical mentorshipDelivery predictabilityOffshore team coordinationResponsibilities: AI Systems Engineering LeadershipGuide the team in building production-grade RAG pipelines and agentic systemsEstablish practical patterns for multi-model orchestration and inference reliabilityEnsure AI systems include cost controls, fallback strategies, and evaluation frameworksReview and improve agent safety, tool invocation patterns, and guardrailsArchitecture & Distributed Systems QualityLead architecture reviews for new AI services.Improve API design standards, versioning practices, and event-driven patternsEnsure proper handling of retries, idempotency, and asynchronous workflowsDrive adoption of observability and monitoring best practicesIdentify and remediate architectural debt.Team LeadershipDirectly manage AI engineers in the U.S.Provide technical oversight and structured guidance to offshore India engineersConduct code reviews and system design reviewsCoach engineers in distributed systems thinking and production hardeningImprove sprint execution discipline and technical accountabilityDelivery & Operational ExcellenceEnsure AI solutions move from prototype to production reliablyPartner with Product and Domain AI leads to translate requirements into well-architected systemsCoordinate closely with DevOps on deployment, CI/CD, and infrastructure standardsImprove predictability in delivery timelines and system reliabilityQualifications8 years of professional software engineering experience2+ years developing enterprise AI applications2+ years of people management or technical team leadershipHands-on experience building LLM-integrated applicationsExperience with RAG pipelines, vector databases and agentic stacksStrong background in backend and distributed systems designStrong AWS experience (Lambda, ECS/EKS, API Gateway, SQS/SNS, Step Functions, Bedrock)Proven ability to lead offshore or distributed teamsStrong coding proficiency in Python and one of Java, NodeJS, Rust or Kotlin