Senior Engineer, AI Platform

OneMagnify India; Detroit (MI); In loco; USD 140.000 - 190.000; Tempo pieno

Descrizione del lavoro

OneMagnify seeks a Senior Engineer, AI Platform to build AI-enabled infrastructure powering its products and client programs. You’ll shape agent workflows, retrieval pipelines, and enterprise integrations while ensuring security, governance, and scale.

You’ll collaborate with product, engineering, and client teams to translate AI capabilities into production-ready solutions that deliver measurable business value.

Competenze

• Bachelor's degree in Computer Science, Engineering, or related field; or equivalent practical experience.
• 5+ years of professional software engineering experience.
• Experience building and operating production services on AWS, Google Cloud, or Azure, including containers and infra as code.
• Experience with observability, monitoring, logging, tracing, alerting, and on-call support.
• Hands-on experience building LLM-powered applications or AI agents including orchestration and tool integrations.
• Experience with AI platforms such as Bedrock, Vertex AI, or similar.
• Experience with retrieval-augmented generation, embeddings, vector databases or vector search, and API design.

Mansioni

• Build AI-powered engineering capabilities and integrate AI tooling into CI/CD.
• Create reliable agent workflows and enterprise context with data services and APIs.
• Deliver safe, auditable, and measurable AI systems with guardrails and testing.
• Operate and scale cloud infrastructure, pipelines, and platform services.
• Contribute to engineering excellence through architecture discussions and best practices.

Conoscenze

AI platforms

Cloud infrastructure

DevOps

LLM-powered apps

MCP

Formazione

Bachelor's degree in CS/Engineering

Strumenti

AWS

Google Cloud

Azure

Descrizione del lavoro

OneMagnify is an AI native, platform-enabled B2B digital agency operating at the intersection of data, technology, and creativity. We help complex organizations drive measurable business outcomes by building smarter customer experiences and delivering highly integrated solutions across digital, media, and technology. By combining deep industry expertise with advanced analytics and artificial intelligence, we enable our clients to make better decisions, move faster, and compete more effectively in dynamic markets.

Role Summary

As a Senior Engineer, AI Platform, you'll help build the foundation that powers AI across OneMagnify’s products, delivery teams, and client programs. Working alongside our AI Platform team, you’ll create the systems that enable AI agents to operate reliably, securely, and at scale in real-world business environments. This role sits at the intersection of software engineering, AI platforms, and cloud infrastructure, with direct influence on how teams develop, deploy, and evolve AI-powered solutions.

The Impact You’ll Have

The platform you help build will shape how AI is applied across customer experience, marketing technology, data, and digital solutions delivered to some of the world’s most recognized brands. From accelerating software delivery to enabling new AI-driven capabilities, your work will directly affect how quickly teams can move from idea to production. You’ll play a key role in making AI trustworthy and practical at scale. The agent workflows, retrieval systems, evaluation frameworks, and guardrails you create will help ensure that AI solutions deliver consistent business value while meeting the reliability and governance expectations of enterprise clients. Because OneMagnify brings together strategy, technology, analytics, and delivery teams, you’ll work closely with engineers, product leaders, and client-facing teams to translate emerging AI capabilities into production-ready solutions that drive measurable outcomes.

What You’ll Do

• Build AI-Powered Engineering Capabilities Develop tooling that enables AI agents to participate in coding, testing, and code review workflows with appropriate human oversight. Integrate AI-assisted development capabilities into CI/CD pipelines and engineering practices. Help improve software quality, delivery speed, and developer productivity through practical AI applications.
• Create Agent Workflows and Enterprise Context Build reliable agent orchestration capabilities, including multi-agent workflows, tool integrations, MCP servers, and approval checkpoints. Develop retrieval pipelines, APIs, and data services that connect AI agents to enterprise knowledge sources. Partner with product and engineering teams to apply platform capabilities to real business and client use cases.
• Deliver Safe and Measurable AI Systems Implement guardrails that help ensure agent actions remain secure, auditable, and aligned with business requirements. Build evaluation frameworks and automated testing approaches for prompts, models, and agent workflows. Establish quality controls that help teams confidently move AI-powered solutions into production.
• Operate and Scale the Platform Build and maintain cloud infrastructure, deployment pipelines, and platform services using modern infrastructure-as-code practices. Improve platform reliability through observability, monitoring, tracing, and alerting. Participate in on-call rotations, incident response, and continuous improvements that strengthen platform performance.
• Contribute to Engineering Excellence Participate in architecture discussions, design reviews, and engineering standards that shape the evolution of the AI platform. Collaborate with engineering, product, and delivery teams to support adoption across the organization. Share knowledge and help establish best practices for building and operating AI-powered systems.

What You’ll Need

• Experience in integrated marketing, digital agency, marketing services, or consulting environments.
• Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
• 5+ years of professional software engineering experience.
• Experience building and operating production services on AWS, Google Cloud, or Azure, including containers, serverless technologies, managed databases, and infrastructure as code.
• Experience with production operations, including observability, monitoring, logging, tracing, alerting, incident response, and on‑call support.
• Hands‑on experience building LLM‑powered applications or AI agents, including orchestration, tool integrations, context engineering, and the Model Context Protocol (MCP).
• Experience with Amazon Bedrock, Google Vertex AI, Azure AI Foundry, or comparable AI platforms.
• Experience with retrieval‑augmented generation (RAG), embeddings, vector databases or vector search, and GraphQL or REST APIs.
• Experience building automated evaluation frameworks, testing LLM outputs, and implementing guardrails for AI s