Senior Manager

V2 Solutions; Hinoba-an; On-site; PHP 2,000,000 - 4,200,000; Full time

Job summary

V2 Solutions is seeking a senior AI engineer/architect to lead the design and development of full-stack AI‑integrated applications and microservices. You will oversee agentic workflows and AI API integrations, while managing both cloud-native and on‑prem deployments, including local LLM setups.

The role requires 14+ years in AI engineering or related fields, strong experience in architecture, RAG platforms, and observability, plus expertise in CI/CD, Docker, Kubernetes, and RESTful APIs.

Qualifications

• 14+ years of experience in AI engineering or related fields.
• Proven experience in application architecture and microservices.
• Strong knowledge of agentic frameworks and AI API integrations.
• Expertise in cloud and on-prem solutions, including local LLM setups.
• Proficiency in RAG platforms and observability techniques.
• Experience with CI/CD, containerization, and serverless platforms.
• Knowledge of event-driven architectures and RESTful API design.

Responsibilities

• Lead the design and development of full stack AI‑integrated applications and microservices.
• Oversee agentic workflows, including agent-to-agent interactions and AI API integrations.
• Manage cloud-native and on‑prem deployments, including local LLM setups (HuggingFace, Ollama).
• Develop and optimize RAG platforms, focusing on vector databases, embeddings, retrieval, prompting, and evaluation.
• Ensure observability, telemetry, and optimization of AI applications.
• Implement CI/CD pipelines, containerization, and orchestration using Docker, Kubernetes, and serverless platforms.

Skills

AI engineering

Microservices architecture

AI API integrations

Cloud/on-prem deployments

CI/CD DevOps

Event-driven architecture

RESTful API design

Leadership

Python

Node.js

Tools

Docker

Kubernetes

Azure

AWS

GCP

Job description

Role & responsibilities

Lead the design and development of full stack AI-integrated applications and microservices. Oversee the implementation of agentic workflows, including agent-to-agent interactions and AI API integrations. Manage cloud-native and on-prem deployments, including local LLM setups (HuggingFace, Ollama). Develop and optimize RAG platforms, focusing on vector databases, embeddings, retrieval, prompting, and evaluation. Ensure observability, telemetry, and optimization of AI applications. Implement CI/CD pipelines, containerization, and orchestration using Docker, Kubernetes, and serverless platforms (Azure Functions, AWS Lambda). Design and manage event-driven architectures using Azure Service Bus, RabbitMQ, and Kafka. Ensure best practices for RESTful API design, security, and documentation.

Collaborate with engineering, data science, and machine learning teams to drive project success. Make architecture decisions, execute roadmaps, and maintain quality standards.

Preferred candidate profile

Qualifications:

• 14+ years of experience in AI engineering or related fields.
• Proven experience in application architecture and microservices.
• Strong knowledge of agentic frameworks and AI API integrations.
• Expertise in cloud and on-prem solutions, including local LLM setups.
• Proficiency in RAG platforms and observability techniques.
• Experience with CI/CD, containerization, and serverless platforms.
• Knowledge of event-driven architectures and RESTful API design.
• Excellent leadership and collaboration skills.
• Strong problem-solving abilities and attention to detail.

Preferred Skills:

• Experience with Azure, AWS, or GCP.
• Familiarity with AI coding tools and frameworks.
• Strong communication and interpersonal skills.
• Knowledge of machine learning algorithms and techniques.
• Understanding of data privacy and security regulations.
• Proficiency in programming languages such as Python and Node.
• Experience with DevOps practices and tools.
• Ability to mentor and guide junior engineers.
• Strong analytical and problem-solving skills