McKinney
Marketing
SeniorPlatformEngineer,Data&AIInfrastructure
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“Senior Platform Engineer, Data & AI Infrastructure at McKinney. Skills: Platform Engineering, Data Infrastructure, AI Infrastructure, Backend Services. Build AI-powered platforms. Build tools and workflows”
Industry & Context.
Root cause analysis; Troubleshooting
On-call rotation
What They're Looking For.
Must Have
4+ years software engineering, Backend focus, Python (FastAPI/Starlette) services, Cloud deployment (GCP preferred), Hands-on SQL, Document database experience, Prior LLM integration experience
Nice to Have
Kubernetes familiarity, Dataform exposure
What You'll Do.
Build AI-powered platforms
Build tools and workflows
Design backend services
Build data-centric components
Integrate AI capabilities
Iterate on AI products
Use document databases
Build containerized services
Harden containerized services
Operate containerized services
Manage image versions
Enforce container security
Leverage Secret Manager
Leverage Artifact Registry
Leverage Cloud Build/Deploy
Leverage Cloud Monitoring/Logging
Integrate LLM/AI capabilities
Utilize enterprise AI platform
Define reusable patterns
Collaborate with data partners
Apply security best practices
Apply privacy best practices
Establish observability
Conduct performance analysis
Participate in on-call
Mentor junior engineers
How You'll Work.
Team & Collaboration
Cross-functional partners; Creative teams; Operations teams; Strategy teams; Data partners
Communication Scope
API documentation
Process & Methodology
Agile practices
Full Job Description
Purpose We’re looking for a backend-leaning, Senior, Full Stack Engineer who will build AI-powered platforms, tools, and workflows that create value for our clients and empower our creative, strategy, operations, and account teams. You’ll design and build backend services, data-centric components, and internal tools, with a strong focus on Python and modern cloud infrastructure. You will be hands-on with integrating large language models (LLMs) and other AI capabilities into real products, from early design through deployment, monitoring, and iteration. Ideal Candidate You’re a strong backend-focused engineer who thinks in terms of systems, data models, and APIs. You’re comfortable hopping into simple frontend tasks when needed. Enjoys collaborating closely with cross-functional partners. You can translate requirements into scalable software that balances speed, quality, and reliability. You’re curious about AI and other emerging technology and excited to integrate them responsibly into real products. You take ownership of products, from design through deployment and maintenance. Responsibilities Design, build and maintain backend services and APIs primarily in Python (FastAPI/Starlette), emphasizing clean design, performance, and reliability. Model data and write high‑quality SQL (primarily in BigQuery); use document databases (e.g., Firestore, MongoDB) where appropriate. Build, harden, and operate containerized services: author Dockerfiles (multi‑stage), manage image versions in Artifact Registry, and enforce container security/scanning. Deploy on GCP with Cloud Run and Compute Engine; leverage Secret Manager, Artifact Registry, Cloud Build/Deploy, and Cloud Monitoring/Logging; Kubernetes familiarity is a plus. Integrate LLM/AI capabilities with an agentic approach (tool/function calling, multi‑step orchestration/planning, retrieval/RAG, and memory) using providers such as OpenAI, Anthropic, and Google Gemini, as well as open‑weight models; implement evaluation, s
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