Engineering Manager AI

Jobgether SRL; United States; Remote; USD 170,000 - 230,000; Full time

Benefits offered by this job

Vacation time

Remote work from anywhere

Health insurance support

Internet stipend

Mobile stipend

Stock options

Learning platform access

Diverse, dynamic team

Job summary

Jobgether SRL, on behalf of a partner in the United States, seeks an Engineering Manager AI to lead a team of 7–8 engineers focused on AI/ML, backend, and platform systems. The role blends hands-on technical depth with team leadership to guide architecture, delivery, and best practices in a fast-moving startup environment.

You will own scoping, costing, sequencing, and execution while aligning with Product, Operations, Modeling, and senior leadership.

Qualifications

• 8+ years of software engineering experience with 2–3 years in leadership.
• Proven experience building and shipping backend and/or ML systems at scale.
• Experience hiring, developing, and retaining engineers while balancing delivery objectives.
• Hands-on familiarity with modern AI/ML systems, including model training and serving.

Responsibilities

• Lead and grow a team of AI/ML, backend, and platform engineers, including hiring, performance management, coaching, retention, and career development.
• Coach engineers through technical designs, architecture decisions, code reviews, and complex engineering trade-offs.
• Establish and maintain high engineering standards across code quality, testing, CI/CD, and development practices.
• Own delivery planning for the team, including accurate costing, estimation, sequencing, prioritization, and accountability for commitments.
• Guide architecture for ML model lifecycle processes, including training, evaluation, monitoring, and retraining.
• Oversee LLM-powered workflows such as agent orchestration, RAG pipelines, vector database integrations, and related AI systems.
• Provide technical oversight for inference services supporting live payment routing, ensuring strict latency, reliability, and scalability requirements are met.
• Ensure AWS infrastructure, CI/CD, observability, dashboards, tracing, and on-call practices meet strong reliability and operational standards.
• Apply PCI-DSS and data-handling considerations to systems that interact with payment data.
• Translate product vision into executable technical roadmaps with timelines, scope, and trade-offs.
• Partner with Product, Operations, and Modeling leadership to align and feedback loops.
• Represent AI/ML engineering progress, priorities, risks, and blockers to senior leadership.

Skills

AI/ML systems

Backend architectures

Team leadership

Hiring & coaching

Go

Python

gRPC

REST APIs

Distributed systems

AWS (ECS/EKS)

CI/CD

LLM workflows

LangChain

RAG pipelines

Vector databases

Prompt engineering

Monitoring & observability

PCI-DSS / payments security

Payments systems

Tools

Terraform

Prometheus

Grafana

OpenTelemetry

CI/CD tooling

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Engineering Manager AI based in United States .

This is a hands-on engineering leadership opportunity focused on building intelligent systems that optimize payment performance and power AI-driven products. You'll lead a team of approximately 7--8 engineers across AI/ML, backend, and platform engineering. The role combines people leadership with enough technical depth to guide architecture, challenge technical decisions, and help unblock complex engineering problems. You'll own delivery across scoping, costing, sequencing, and execution while establishing strong standards for quality and engineering practices. You'll work closely with Product, Operations, Modeling, and senior leadership to turn business priorities into an actionable technical roadmap. The environment is fast-moving, multicultural, and startup-oriented, with a strong emphasis on innovation, ownership, and continuous growth.

Accountabilities:

• Lead and grow a team of AI/ML, backend, and platform engineers, including hiring, performance management, coaching, retention, and career development.
• Coach engineers through technical designs, architecture decisions, code reviews, and complex engineering trade-offs.
• Establish and maintain high engineering standards across code quality, testing, CI/CD, and development practices.
• Own delivery planning for the team, including accurate costing, estimation, sequencing, prioritization, and accountability for commitments.
• Guide architecture for ML model lifecycle processes, including training, evaluation, monitoring, and retraining.
• Oversee LLM-powered workflows such as agent orchestration, RAG pipelines, vector database integrations, and related AI systems.
• Provide technical oversight for inference services supporting live payment routing, ensuring strict latency, reliability, and scalability requirements are met.
• Ensure AWS infrastructure, CI/CD, observability, dashboards, tracing, and on-call practices meet strong reliability and operational standards.
• Apply appropriate PCI-DSS and data-handling considerations to systems and services that interact with payment data.
• Translate product vision and business priorities into executable technical roadmaps with clear timelines, scope, and trade-offs.
• Partner closely with Product, Operations, and Modeling leadership to maintain alignment and create short feedback loops.
• Represent the AI/ML engineering team's progress, priorities, risks, and blockers to senior leadership.

Requirements

• 8 years of professional software engineering experience, including 2--3 years managing and leading engineering teams.
• Proven experience building and shipping backend and/or machine learning systems at scale.
• Experience hiring, developing, retaining, and managing engineers while balancing people development with delivery objectives.
• Hands-on familiarity with modern AI/ML systems, including model training and serving, LLM-powered workflows, agents, RAG, orchestration, or related technologies.
• Practical experience with LLM-based systems in production, particularly agents, RAG pipelines, or AI workflow orchestration.
• Strong technical understanding of backend systems, distributed architectures, APIs, and production engineering practices.
• Experience with technologies such as Go, Python, gRPC, REST APIs, event streaming, and distributed systems is valuable.
• Familiarity with AWS infrastructure and services, including ECS/EKS, Terraform, RDS/Aurora, and S3.
• Experience with AI/ML technologies such as PyTorch, TensorFlow, XGBoost, scikit-learn, MLflow, or Weights & Biases is beneficial.
• Knowledge of LLM and agent technologies such as LangGraph, LangChain, RAG, vector databases, prompt engineering, and LLM evaluation is valuable.
• Familiarity with observability technologies and practices, including Prometheus, Grafana, OpenTelemetry, structured logging, and on-call runbooks.
• Payments, fintech, or experience in another regulated and latency-sensitive industry is a strong plus, including familiarity with PCI-DSS, tokenization, or payment service provider integrations.
• Strong communication and stakeholder management skills, with the ability to communicate clearly with both technical and non-technical partners.
• Comfortable operating in a rapidly changing startup environment, with the ability to adapt scope, priorities, and communication while maintaining team trust.
• Strong growth mindset, self-awareness, and commitment to continuous improvement.

Benefits

• Vacation and additional paid time off.
• Remote work from anywhere.
• Financial support for health insurance, internet, and mobile phone expenses.
• Stock options.
• Access to a learning and development platform.
• Multidisciplinary, diverse, and dynamic team environment.
• Opportunities for professional growth and career development.
• Exposure to modern AI, ML, cloud, observability, and payments technologies.
• Opportunity to contribute to a high-impact payments platform serving a broad regional market.
• Startup environment characterized by agility, innovation, ownership, and continuous development.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.