> Markdown version of [/jobs/ext/2735816-ai-platform-engineer](https://www.wearedevelopers.com/jobs/ext/2735816-ai-platform-engineer). 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). --- # AI Platform Engineer - **Company:** Harley Ellis Devereaux HED - **Location:** Boston, MA, United States (Remote available) - **Experience:** Expert - **Salary:** $120,000.0 - $170,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Audit Trail, Information Engineering, Data Stores, Software Debugging, Python (Programming Language), Knowledge Management, Productivity Software, Runbook, Software Engineering, Workflow Management Systems, Data Logging, Data Processing, Data Ingestion, Large Language Models, AI Platforms, Information Technology, Api Design, Software Version Control, Databricks - **Published:** September 5, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/15751344?backUrl=%2Fcareer%2F15751344%2FAi-Platform-Developer-Massachusetts-Boston ## About the Role * Bachelor's degree in computer science, data engineering, or a related field (or equivalent experience). * 5+ years of software engineering and/or data engineering experience, including building and operating production services. * Demonstrated experience deploying and supporting AI/LLM systems in production (monitoring, incidents, iteration, and measured improvement). * Hands-on multi-agent orchestration experience (e.g., LangChain, AutoGen, CrewAI, or similar), including workflow design and failure handling. * Experience owning connectors/ingestion pipelines (reliability patterns such as retries, idempotency, schema/version management, and alerting). * Strong Python engineering skills; comfort working with APIs, data stores, and workflow/orchestration tooling. * Operational discipline: logging, audit trails, debugging methodology, cost/token controls, and rollback mindset. * Documentation-first habits (design notes, runbooks, interface contracts) and the ability to communicate tradeoffs to non-technical stakeholders. * Preferred: Databricks/lakehouse + medallion familiarity; experience implementing governance/audit requirements; AEC or project-based domain exposure. * Comfortable using AI-enabled productivity tools for meetings and knowledge capture (e.g., Fireflies AI Note Taker) while maintaining privacy and compliance boundaries. Physical Requirements * Prolonged periods of sitting at a desk and working on a computer. * Ability to communicate effectively in writing and verbally via phone, video conferencing, and in person. * Visual acuity to perform responsibilities. Work Environment We embrace a hybrid model that promotes both autonomy and collaboration, including the freedom to work from home, with regular in-office days to connect with teammates and build culture. ## Description You own the operational foundations that make AI safe and maintainable-connectors into the Bronze layer, versioned interfaces, logging and auditability, evaluation, cost controls, and guardrails. This is an engineering role focused on reliability and lifecycle thinking, not a "light automation" position. You collaborate directly with internal stakeholders to translate needs into systems that hold up under real usage and evolve with the business. Essential Functions * Design, build, and orchestrate multi-agent workflows (handoffs, coordination, retries/fallbacks, and failure handling) for business-critical use cases. * Develop agents with role-appropriate personas, boundaries, and context so outputs are consistent, trustworthy, and aligned to business intent. * Own Bronze-layer ingestion: build and maintain connectors/interfaces; manage schema drift, reliability, change handling, monitoring, and alerting. * Treat data inputs/outputs as contracts-versioned, traceable, testable-and implement validation at data boundaries. * Implement observability across the AI lifecycle (structured logs, traces, evaluation artifacts, and audit trails) so systems are debuggable and reviewable. * Implement guardrails and controls: budgets, rate limits, model selection strategy, safe defaults, and kill-switches to prevent runaway behavior. * Apply governance and access boundaries early (permissions, sensitive data handling, traceability, compliance posture) rather than bolting it on later. * Produce durable documentation (architecture notes, runbooks, interface contracts) and enable others to operate and extend the platform. * Provide evidence-based buy vs. build recommendations, and advocate for responsible sunsetting when systems reach end-of-life. ## Related Videos - [API Design - Getting Started](https://www.wearedevelopers.com/videos/33-api-design-getting-started) - [Technical Documentation - How Can I Write Them Better and Why Should I Care?](https://www.wearedevelopers.com/videos/681-technical-documentation-how-can-i-write-them-better-and-why-should-i-care) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [Rest API Antipatterns](https://www.wearedevelopers.com/videos/100208-rest-api-antipatterns) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [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) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [13 AI Tools You Have to Try](https://www.wearedevelopers.com/magazine/219-13-ai-tools-you-have-to-try) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care)