Software Engineering Manager jobs are leadership roles that oversee teams building reliable, scalable platforms and AI products. On Rex.zone, this job entity spans modern SDLC and MLOps with a direct link to AI/ML training workflows: LLM training pipelines, data labeling operations, RLHF experimentation, prompt evaluation, QA evaluation, and model governance. Managers steer the technical roadmap, ensure training data quality, enforce annotation guidelines compliance, and drive model performance improvement across NLP, computer vision, and content safety systems. Explore remote, contract, freelance, full-time, entry-level, and senior openings. Rex.zone helps candidates navigate opportunities at AI labs, tech startups, BPOs, and annotation vendors and apply with confidence.
As a Software Engineering Manager, you lead engineering teams to deliver high-quality software and AI platforms that meet product and compliance requirements. You align architecture decisions with business goals, integrate MLOps into the software delivery lifecycle, and coordinate cross-functional work spanning data labeling, model training, RLHF cycles, and safety evaluations.
Own technical roadmap and execution, establish engineering best practices and CI/CD, manage scalable microservices and cloud-native architecture, partner with ML engineers on LLM training pipelines, supervise data labeling and QA evaluation workflows, ensure observability, SRE, and model governance, collaborate on privacy and security compliance, hire and mentor talent, and drive agile delivery and OKRs.
Engineering leadership, system design, SDLC mastery, cloud platforms (AWS, GCP, Azure), container orchestration (Kubernetes), CI/CD, infrastructure-as-code, monitoring and incident response, data platform familiarity, MLOps literacy, and ability to map RLHF, prompt evaluation, named entity recognition, computer vision annotation, and content safety labeling to production workflows.
Hands-on programming in Python, Java, or Go, microservices and event-driven architecture, feature flagging and A/B testing, cost optimization, governance and compliance frameworks, building training data pipelines, managing annotation vendors, running model performance improvement experiments, and scaling teams from entry-level to senior engineers.
Roles available across remote, hybrid, and on-site. Employment types include full-time, contract, freelance, and interim. Career levels range from entry-level team leads to senior and director-level engineering management. Many teams operate globally with flexible schedules and distributed collaboration practices.
Common domains include NLP, computer vision, content safety, and LLM training. Typical employers on Rex.zone: AI labs, tech startups, BPOs, and annotation vendors supporting training data quality, annotation guidelines compliance, and model governance in production environments.
Cloud-native platforms, Kubernetes, Docker, Terraform, GitHub/GitLab CI, observability tools, feature stores, data lakes, model registries, and workflow orchestration. Integrations with labeling platforms, prompt and QA evaluation tools, and experiment tracking systems essential for reliable AI delivery.
Compensation varies by region, seniority, and contract type. Packages may include base salary, performance bonuses, equity, learning budgets, and remote work stipends. Contract and freelance engagements often offer flexible terms aligned to milestones and deliverables.
Create a profile on Rex.zone, highlight engineering leadership outcomes, MLOps experience, and examples of model performance improvement. Filter jobs by remote, contract, freelance, full-time, entry-level, and senior modifiers, then apply to roles at AI labs, startups, BPOs, and annotation vendors.
They lead teams to build and operate platforms that power LLM training pipelines and ML products, integrate MLOps into the SDLC, and coordinate workflows like data labeling, RLHF, prompt and QA evaluation, and model governance to ensure training data quality and model performance improvement.
NLP, computer vision, and content safety are common domains, alongside platform engineering for LLM training. Employers include AI labs, tech startups, BPOs managing labeling operations, and annotation vendors working on named entity recognition and computer vision annotation.
Yes. Many listings on Rex.zone offer remote, contract, freelance, hybrid, and full-time options. Filters let you target entry-level leadership tracks or senior roles with broader scope.
Direct hands-on is helpful, but managers must at minimum understand RLHF cycles, data labeling quality controls, annotation guidelines compliance, and how these impact model performance and production reliability.
Show impact: technical roadmap delivery, reduced incident rates via SRE, faster CI/CD, cost optimization, measurable model performance improvements, and successful collaboration with data labeling and ML teams. Include artifacts like postmortems, design docs, and OKR results.
Expect leadership and system design interviews, execution and roadmap reviews, cross-functional collaboration scenarios, and domain discussions covering MLOps, LLM training pipelines, QA evaluation, and compliance. Some roles include take-home architecture exercises.
Create or update your Rex.zone profile, search for ‘Software Engineering Manager jobs,’ use modifiers like remote or contract, review role requirements, and submit tailored applications directly through the platform.
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