The posting
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 Lead Engineer, AI Platform, you will own the architecture and evolution of the enterprise AI platform that powers AI agents across OneMagnify products and client solutions. This role sits at the center of engineering, product, data, and AI delivery, translating emerging AI capabilities into reliable, production-ready systems. You'll guide both technical direction and execution, helping teams deploy AI workflows that are secure, measurable, and trusted at scale. Your work will shape how OneMagnify builds, governs, and operates AI across the organization.
The Impact You'll Have
AI agents are becoming a core part of how businesses automate work, deliver customer experiences, and make decisions. You'll create the platform foundation that enables product and engineering teams to move AI solutions from experimentation into reliable, enterprise-grade production environments.
Your work will directly support client-facing applications, AI-powered workflows, and digital platforms where reliability, safety, and performance matter. From connecting agents to enterprise knowledge to establishing evaluation frameworks and governance controls, you'll help ensure AI solutions deliver measurable business outcomes while operating within clear guardrails.
This role also plays a critical part in OneMagnify's integrated delivery model. You'll collaborate with product, engineering, data, security, and delivery teams to create shared capabilities that accelerate innovation while maintaining the scalability, governance, and operational discipline expected of enterprise software platforms.
What You'll Do
Shape the AI Platform Strategy
- Own the architecture for agent orchestration, multi-agent workflows, tool integrations, and human approval processes across the enterprise AI platform.
- Evaluate models, frameworks, platforms, and vendors, making decisions that balance scalability, reliability, quality, and cost.
- Partner with product and engineering leaders to ensure the platform supports current and future AI use cases.
Build Enterprise Knowledge & Context Systems
- Design and implement retrieval pipelines and vector-based knowledge systems that connect AI agents to enterprise data and content.
- Determine when prompting, retrieval-augmented generation, or model customization delivers the best business outcome.
- Enable product teams to build AI experiences grounded in accurate, relevant enterprise knowledge.
Establish AI Quality, Safety & Governance
- Create the frameworks used to evaluate AI performance, including offline and online evaluations, regression testing, red teaming, and release quality gates.
- Design safeguards such as least-privilege access, sandboxing, audit trails, approval workflows, and usage controls.
- Define measurable standards that allow teams to confidently deploy AI solutions into production environments.
Operate a Scalable Enterprise Platform
- Lead the operation of a multi-region cloud platform with accountability for availability, performance, disaster recovery, security, and cost management.
- Build observability capabilities including metrics, tracing, telemetry, alerting, and service-level objectives.
- Lead incident response practices, on-call operations, escalation processes, and continuous improvement through post-incident reviews.
Lead Engineering Excellence
- Mentor and develop engineers on the AI Platform team while establishing engineering standards and best practices.
- Collaborate with engineering, product, and delivery teams to accelerate platform adoption and successful implementation.
- Serve as a trusted technical leader for complex architectural decisions and cross-functional trade-offs.
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 experience.
- 10+ years of software engineering experience, including 3+ years as a technical lead, architect, or similar leadership role supporting production systems.
- Experience building and operating 24x7, multi-region enterprise SaaS platforms on AWS, Google Cloud, or Azure, including infrastructure as code and disaster recovery planning.
- Strong production operations expertise, including observability, metrics, logging, distributed tracing, alerting, service-level objectives, incident response, and postmortem practices.
- Experience designing and operating production AI and LLM-based systems, including agent orchestration, multi-agent architectures, tool integrations, context engineering, and Model Context Protocol (MCP) implementations.
- Expertise with AI platforms such as Amazon Bedrock, Google Vertex AI, Azure AI Foundry, or similar enterprise AI ecosystems.
- Experience building retrieval-augmented generation (RAG) solutions and working with vector databases and knowledge retrieval systems.
- Deep understanding of AI evaluation, testing, governance, and safety practices, including evaluation datasets, LLM-as-judge frameworks, regression testing, and agent containment strategies.
- Hands-on experience incorporating AI-assisted development workflows into CI/CD pipelines, including validation, review, and approval processes.
- Experience integrating enterprise data platforms and designing secure multi-tenant SaaS environments with identity management, role-based access controls, and tenant isolation.
- Fluency in Python, TypeScript, SQL, and Git-based CI/CD practices.
- Proven ability to influence technical direction and collaborate effectively across engineering, product, security, and delivery teams.
Future-Ready Skills (Nice to Have)
- Experience building self-service or low-code platforms that enable governed AI agent creation and deployment.
- Familiarity with managed agent runtimes and agent frameworks from major cloud providers.
- Knowledge of security, governance, and AI risk frameworks such as SOC 2, ISO 27001, NIST AI RMF, or ISO/IEC 42001.
- Experience working within agency, consulting, client delivery, or automotive-focused environments.
- Working knowledge of fine-tuning approaches, including supervised fine-tuning, LoRA/PEFT, and preference tuning.
- Experience with additional backend languages such as Java, Go, or C#.
- Experience using AI-enabled engineering workflows, automation, and platform engineering practices to improve development velocity and quality.
Benefits
We believe great work happens when people have the support and flexibility they need to thrive. Our benefits include medical, dental, and vision coverage, a 401(k) retirement plan, paid holidays, and Flexible Time Off (FTO) so you can take time away to recharge when you need it. We also offer additional programs focused on wellness, financial security, and professional growth.
We are an equal opportunity employer
We believe that innovative ideas and solutions start with unique perspectives. That's why we're committed to providing every employee a workplace that's free of discrimination and intolerance. We're proud to be an equal opportunity employer and actively search for like-minded people to join our team.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform job functions, and to receive benefits and privileges of employment. Please contact us to request accommodation.
