AI Platform Engineer
About The Position
The Junior AI Platform Engineer assists with building, testing, and supporting enterprise AI solutions that use Retrieval-Augmented Generation (RAG), vector search, Azure AI services, and large language model (LLM) integration. Under the guidance of experienced engineers, the role contributes to chatbots, virtual assistants, self-service analytics, intelligent automation, and natural language interfaces across enterprise applications. The position supports assigned AI pipeline components, including embedding generation, vector indexing, retrieval workflows, LLM orchestration, API integration, monitoring, and usage tracking. It follows established architecture, security, compliance, and deployment standards in a regulated enterprise environment, escalating design decisions and complex issues to experienced team members. The Junior AI Platform Engineer contributes to AI solutions that integrate with enterprise data pipelines, APIs, reporting platforms, collaboration tools, and business applications. The role completes defined development tasks, tests and documents changes, and assists with troubleshooting under technical guidance and review. It collaborates with IT, data, reporting, compliance, and business teams while developing practical skills in reliable, secure, and cost-effective AI delivery aligned with organizational governance standards.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience through technical training, projects, or relevant work.
- 2–4 years of relevant experience in software development, AI, platform development, or related technical work; internships, academic projects, and personal projects may count.
- Foundational Python programming skills demonstrated through coursework, projects, or work experience.
- Basic understanding of backend development, REST APIs, and application integration; exposure to .NET, Node.js, or equivalent technologies.
- Foundational understanding of LLM concepts and prompt development, with exposure to Azure OpenAI or similar platforms through learning or projects.
- Basic awareness of RAG, embeddings, and vector search concepts, with willingness to learn Azure AI Search or equivalent technologies.
- Basic understanding of cloud application concepts and Microsoft Azure, with the ability to contribute to defined API and application tasks under guidance.
- Basic awareness of token consumption, usage-based LLM pricing, and the importance of monitoring performance and cost.
- Foundational understanding of secure development and access control concepts, with willingness to learn enterprise RBAC, identity management, Entra ID, and secure access patterns.
- Ability to follow required training and documented procedures for handling PHI, PII, audit logs, and traceability in a regulated enterprise environment.
- Foundational problem-solving skills, clear communication, collaboration, and willingness to learn and apply technical feedback.
Nice To Haves
- Hands-on exposure to LLM-based applications, vector search, or RAG through internships, coursework, personal projects, or work experience.
- Exposure to Azure Data Factory or similar pipeline orchestration tools.
- Exposure to Power BI, enterprise reporting platforms, or self-service analytics.
- Exposure to Copilot Studio, chatbot frameworks, or conversational AI platforms.
- Introductory familiarity with Infrastructure as Code tools such as Bicep or Terraform.
- Awareness of responsible AI principles or governance frameworks such as NIST AI RMF.
- Exposure to prompt testing, response validation, citation-based grounding, or AI quality assurance through learning or projects.
- Exposure to healthcare, finance, insurance, or another regulated industry through coursework, internships, or work experience.
Responsibilities
- Assist with implementing and testing assigned RAG pipeline components, including embedding generation, vector storage, retrieval logic, ranking, context injection, and LLM response generation using established designs.
- Support Azure OpenAI integrations and apply established practices for prompt engineering, grounding, validation, citation-based responses, and traceable outputs under technical guidance.
- Assist with configuring, testing, and maintaining vector search solutions using Azure AI Search or equivalent technologies.
- Support document chunking, segmentation, and metadata enrichment; test hybrid, semantic, and keyword search; document retrieval results; and assist experienced engineers with relevance, accuracy, and latency improvements.
- Develop and maintain assigned API integrations and orchestration components connecting data pipelines, vector search, LLM services, reporting platforms, and enterprise applications, following established patterns and code review practices.
- Implement defined error handling, logging, monitoring, and reusable service patterns; maintain technical documentation and follow established production support procedures.
- Assist with testing and deploying AI applications through established Azure DevOps CI/CD pipelines under review, and use Azure Monitor, Log Analytics, and related tools to check application health.
- Perform initial troubleshooting of AI pipelines, APIs, retrieval systems, and LLM integrations using documented procedures; capture findings and escalate complex issues to experienced engineers.
- Track token consumption, API utilization, and response performance; assist with testing approved prompt, caching, and request-throttling changes and report opportunities to improve cost efficiency.
- Communicate assigned work, test results, and questions clearly to technical and non-technical stakeholders.
- Follow responsible AI, auditability, enterprise governance, reliability, traceability, security, compliance, and support procedures; seek guidance when needed and contribute to continuous improvement.
- Collaborate with AI, backend, cloud, platform engineering, reporting, compliance, and business teams while developing knowledge of their systems and processes.
Benefits
- Benefits, bonuses, and commission may be available.
- Competitive compensation package.
- Medical, dental, supplemental health, life, and vision coverage for employees and dependents, with no waiting period.
- Life and disability insurance.
- 401(k) with company match.
- Tuition assistance.
- Paid parental leave.
- Backup family care.
- Flexible time off.
- Flexible work location policies.
- Dynamic, modern work environments that promote collaboration and creativity.
- Employee Resource Groups that advocate for inclusion and diversity.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
