Job Title: AI Platform Engineer
Job Type: Contract
Job Location: Hybrid

As part of the talented and driven technology team, the AI Platform Engineer will design and implement cloud-based AI solutions that power products and operations. Partnering closely across engineering, data, and product, you’ll build robust AI services, optimize pipelines, and accelerate the adoption of responsible AI to achieve business outcomes. You’ll keep up with the latest AI and platform trends to promote continuous improvement, scaling solutions from concept to production. The AI Engineer is a hands on builder who understands business and technology and advocates for pragmatic, secure AI solutions aligned to our mission, vision, and goals.

Your Mission

On your journey, you will face challenges such as:

• Designing and delivering cloud AI solutions—building cloud based APIs, microservices, and event-driven components that integrate models with platforms, data, documents and products.
• Evaluate AI platforms—Evaluate and recommend AI platform providers and options.
• Implementing LLM Ops—automating training, evaluation, deployment, and monitoring; establishing repeatable CI/CD for models and prompts; enabling safe rollback and A/B testing.
• Operationalizing retrieval-augmented generation (RAG) and other AI patterns—curating knowledge sources, indexing with vector search, and tuning prompts/evaluations to improve accuracy.
• Building reliable data pipelines—ingesting, transforming, and serving features with observability, lineage, and governance, in partnership with data engineering.
• Embedding responsible AI—privacy-by-design, model risk assessment, bias testing, PII handling, guardrails, and secure key/secret management; collaborating with security and governance.
• Scaling for production—capacity planning, performance optimization, caching, failover, and cost management; instrumenting telemetry to track business impact.
• Partnering across teams—working with product managers, architects, and salon-facing stakeholders to translate needs into solutions and roadmaps; documenting designs and runbooks.
• Advocating adoption—creating starter kits, templates, and reference implementations that help teams ship AI features faster while meeting standards.

Your Expertise

To land this job you will need:

• Bachelor’s Degree in Computer Science, Engineering, Data Science, or related field.
• 7–10+ years of progressive experience building production software, with 3–5+ years focused on ML/AI engineering (or equivalent).
• Strong programming skills in Python (preferred) and one or more of: C#, Java, or JavaScript; expertise with REST APIs.
• Cloud AI on Azure: Azure Machine Learning, Azure OpenAI Service, Azure AI Search (vector), Cognitive Services, Azure Functions, Event Hub/Service Bus, Key Vault.
• Data & storage: SQL (e.g., SQL Server), NoSQL, data lakes, parquet/Delta, feature stores; vector databases/search systems; performance tuning.
• MLOps/LLMOps: Azure ML pipelines, model/package registries, version management, offline/online evaluation, drift and quality monitoring.
• DevOps: Git, Azure DevOps, CI/CD, infrastructure as code (Bicep/Terraform).
• Security & governance: threat modeling for AI systems, secret rotation, RBAC, network isolation, compliance; familiarity with secure data integration and web services.
• Bonus: Experience with Power Platform (Power Automate, Copilot Studio/agents), D365, SharePoint, Databricks/Synapse/Fabric; Azure AI Engineer or Solutions Architect certifications.
• Well-developed communication skills to interact effectively with business partners and vendors; leadership traits including creativity, problem solving, influence, and negotiation.