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AI Engineering Manager

Acunor InfotechNJ🇺🇸United StatesPosted 26 Aug 2026

Quick Overview

Seniority
Mid Senior
Work mode
Remote
Location
NJ, United States
Posted
15 hours ago
AWSHIPAALLM

Job Description

AI Engineering Manager / Lead AI Engineer
Location: Remote United States only
Work Hours: Must work Pacific Time (PST/PDT) business hours
Employment Type: Long-Term Contract
Openings: 3
About the Role
We are seeking an experienced AI Engineering Manager / Lead AI Engineer who can operate as a true player-coach, combining engineering leadership with hands-on technical expertise.
This role will manage engineers across a central AI platform team and multiple delivery pods, including both internal employees and contractors. The environment is AWS-native, with Amazon Bedrock serving as the standard foundation-model layer.
The successful candidate will own engineering execution, technical quality, team effectiveness, and production readiness while remaining technically credible enough to review AI architectures, prompts, evaluation suites, and code.
Key Responsibilities
  • Manage engineers across the central AI platform team and delivery pods, including internal employees and contractors.
  • Own engineering quality standards across AI/LLM applications, agents, integrations, and supporting services.
  • Establish and enforce code review practices, agent quality standards, Definition of Done, and production-readiness criteria.
  • Manage engineering performance, coaching, staffing, and contractor performance.
  • Partner with platform leadership to establish and drive adoption of reusable templates, CI/CD pipelines, evaluation harnesses, and guardrail patterns.
  • Review AI agent architectures built using Amazon Bedrock, including Bedrock Agents, Knowledge Bases, Guardrails, and foundation-model selection.
  • Provide technical leadership across LLM agents, RAG, prompt/context engineering, evaluation frameworks, and production AI architectures.
  • Unblock engineering teams and help delivery pods maintain a fast development and release cadence.
  • Stay technically hands-on through code reviews, prompt reviews, evaluation-suite reviews, technical problem solving, and occasional coding.
  • Maintain consistent engineering and production-quality standards across multiple delivery teams.
Required Qualifications
  • 8+ years of software engineering experience.
  • 3+ years managing engineers delivering AI/ML or LLM systems into production.
  • Experience managing blended engineering teams consisting of contractors and full-time employees.
  • Strong hands-on understanding of LLM-powered agents, RAG, tool/function calling, and production GenAI applications.
  • Ability to review agent architectures, prompt/context engineering implementations, and LLM evaluation suites.
  • Working knowledge of AWS cloud services and modern AI/LLM application architectures.
  • Ability to ramp quickly on Amazon Bedrock, including Bedrock Agents, Knowledge Bases, and Guardrails.
  • Strong engineering leadership combined with a hands-on player-coach mentality.
  • Comfortable operating in a fast-moving and relatively flat engineering organization.
  • Ability to work full Pacific Time (PST/PDT) business hours.
Preferred Qualifications
  • Direct production experience with Amazon Bedrock, Amazon SageMaker, or the broader AWS AI/ML ecosystem.
  • Healthcare or regulated-industry experience, including exposure to HIPAA, PHI handling, or clinical workflows.
  • Experience scaling an engineering organization from fewer than 10 engineers to 30+ engineers.

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