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Salary
$120k – $170k per year
Location
Hybrid (Boston, United States)
Seniority
Senior · 5+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Feb 9, 2026. HED scores A on the Alion truth index.

Overview
Company
Impact
Profile match

HED

HED is a US architecture and design firm offering engineering services for sectors such as healthcare, higher education, science and technology and mission critical facilities. Its job ads seek fire protection engineers and designers, mechanical engineers and designers and project managers, with offices including Los Angeles, Chicago, Boston and Royal Oak. The firm is based in the United States.

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.

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