AI Platform Engineer

Posted 2 Days Ago
Boston, MA, USA
In-Office
120K-170K Annually
Senior level
Design
An Integrated A&E Company
The Role
Build and operate production-grade AI agent systems and connectors into governed data (Bronze layer). Design multi-agent workflows, enforce data contracts, implement observability, guardrails, cost controls, governance, and durable documentation while collaborating with stakeholders.
Summary Generated by Built In

AI Platform Engineer

HED is hiring an AI Platform Engineer to build durable, production-grade AI agent systems that integrate with governed data. 

About HED

We are a team that is full of ideas, experience, creativity, passionate opinions, insatiable curiosity, uncompromising integrity, commitment, and skill. Our culture is about aspiration, embracing change and challenges, listening to (and learning from) each other, encouraging continual learning, and inspiring collective growth. As an inclusive, integrated architecture and engineering practice, we value the diversity of perspectives, experiences, abilities, and expertise that advance both the work we do, and the world we share.

Position Summary

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.

Requirements

• 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.

The office is a professional, open-space environment designed for collaborative and independent work.

Other Duties

Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.

Skills Required

  • Bachelor's degree in computer science, data engineering, or 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, 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 (retries, idempotency, schema/version management, reliability patterns, alerting).
  • Strong Python engineering skills; comfortable working with APIs, data stores, and workflow/orchestration tooling.
  • Operational discipline: logging, audit trails, debugging methodology, cost/token controls, rollback mindset.
  • Documentation-first habits (design notes, runbooks, interface contracts) and ability to communicate tradeoffs to non-technical stakeholders.
  • Comfortable using AI-enabled productivity tools for meetings and knowledge capture while maintaining privacy and compliance boundaries (e.g., Fireflies AI).
  • Databricks/lakehouse and medallion architecture familiarity.
  • Experience implementing governance and audit requirements.
  • AEC or project-based domain exposure.
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The Company
HQ: Royal Oak, Michigan
680 Employees
Year Founded: 1908

What We Do

At HED, we believe great design is about more than aesthetics—it’s about solving complex challenges, enriching communities, and building a better future. As an integrated design firm, we combine architecture, engineering, consulting, and planning to deliver sustainable, impactful solutions. Guided by a shared purpose to create positive change, we foster collaboration, diversity, and continuous learning, where bold ideas and fresh perspectives drive innovation. With nine offices across the U.S., we pair national resources with localized expertise to serve diverse markets, including education (Higher Ed and Pre K-12), healthcare, mission critical, workplace, housing and mixed-use, science and advanced manufacturing, community, and federal and transportation. Discover how HED advances your world at www.hed.design.

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