> Markdown version of [/jobs/ext/459246-senior-platform-engineer-data-ai-infrastructure](https://www.wearedevelopers.com/jobs/ext/459246-senior-platform-engineer-data-ai-infrastructure). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Platform Engineer, Data & AI Infrastructure - **Company:** MCKINNEY AND COMPANY, INC. - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $140,000.0 - $160,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Build Automation, Microsoft Azure, BigQuery, Code Review, Databases, Data Validation, Document-Oriented Databases, Identity and Access Management, Python (Programming Language), MongoDB, Performance Tuning, Software Engineering, SQL Databases, Management of Software Versions, Web Application Frameworks, AI Infrastructure, Data Logging, Cloud Monitoring, Large Language Models, Build Server, Backend, Fastapi, Build Management, Pytest, AI Platforms, Git Flow, Kubernetes, Graphql, Machine Learning Operations, Front End Software Development, Api Design, Oracle Cloud Infrastructure, Software Version Control, Data Pipelines, Api Management, Docker - **Published:** June 5, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=fad3b7a6b278561a ## About the Role Do you have experience in SQL?, * 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., * Strong experience building backend services and APIs in Python (any modern web framework) * Experience with document databases (e.g., Firestore, MongoDB). * Containers & CI/CD: Docker/OCI image authoring, multi-stage builds, image scanning/SBOMs, Artifact Registry; automated builds and deployments. * Cloud: GCP first (Cloud Run and Compute Engine; Secret Manager, Artifact Registry, Cloud Build/Deploy, Monitoring/Logging); Kubernetes familiarity welcome; equivalent AWS/Azure experience acceptable. * AI/LLM: Agentic architectures (tool/function use, multi-step orchestration, retrieval/RAG, planners, memory), evaluation/guardrails/safety; experience with OpenAI, Anthropic, Google Gemini, and open-weight models; familiarity with enterprise AI platforms that unify access to multiple model types. * APIs & Services: REST/GraphQL, schema/versioning, authentication/authorization. * Reliability: Testing (Pytest or similar), observability, performance tuning. * Frontend: Able to handle simple UI needs using modern web technologies; framework agnostic. * Process: Git-based workflows and agile practices., * Communicates and collaborates effectively with creative, operations, strategy, and data partners. * Outcome-oriented problem solving; balances speed, quality, and security. * Ownership and accountability; follows through and documents decisions. * Growth mindset; receptive to feedback and continuous learning. * Uses AI assistants responsibly with validation: evaluates outputs critically, adds tests, and adapts code to team conventions before submission. Experience * 4+ years of professional software engineering with a backend focus. * Proven and demonstrable experience building Python (FastAPI/Starlette) services and APIs for cloud deployment (GCP preferred). * Hands-on SQL experience in BigQuery; document database experience; Dataform exposure is a plus. * Prior experience integrating LLMs in an agentic manner into production apps or adjacent ML systems., You must be authorized to work in the US for any employer. At this time, we are not sponsoring or providing assistance with obtaining work authorization. ## Description 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., * 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, safety, and guardrails. * Utilize our enterprise AI platform (Abacus.ai) that provides unified access to multiple language, image, and short-form video models, plus prompt/version management, safety, and analytics; help define reusable patterns and abstractions for it across products. * Collaborate with data partners on ELT pipelines; use BigQuery and Dataform for transformations and analytics use cases. * Define and version API contracts (REST/GraphQL); document systems and interfaces. * Apply security and privacy best practices (authn/z, IAM least-privilege, secret handling, input validation, rate limiting). * Establish observability (metrics, logs, traces) and conduct performance tuning; participate in pragmatic on-call as needed. * Write tests (unit/integration/e2e); maintain CI/CD pipelines; conduct code reviews; mentor junior engineers ## Related Videos - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [pytest: Simple, rapid and fun testing with Python](https://www.wearedevelopers.com/videos/213-pytest-simple-rapid-and-fun-testing-with-python) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [GraphQL + Apollo + Next.js: A Lovely Trio](https://www.wearedevelopers.com/videos/311-graphql-apollo-next-js-a-lovely-trio) - [Automagic Configuration in Python](https://www.wearedevelopers.com/videos/363-automagic-configuration-in-python) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)