HED (hed.co) Logo

HED (hed.co)

AI Platform Engineer

Posted 5 Days Ago
In-Office
Boston, MA, USA
120K-170K Annually
Senior level
In-Office
Boston, MA, USA
120K-170K Annually
Senior level
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.
The summary above was generated by AI

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.

Similar Jobs

3 Days Ago
Remote or Hybrid
USA
195K-290K Annually
Senior level
195K-290K Annually
Senior level
Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
Lead design, build, and deploy of large-scale data platforms for LLMs, RAG, and agentic AI systems. Hands-on coding, architecting fault-tolerant pipelines, establishing MLOps/DataOps best practices, mentoring engineers, and operationalizing research into production across Exabyte-scale distributed systems.
Top Skills: AirflowAWSBigQueryDaskDevsecopsDockerFlinkGCPGoJvmKafkaKubeflowKubernetesLangchainLlamaindexLlmsMlflowOciPulsarPythonRetrieval-Augmented Generation (Rag)RustSagemakerSnowflakeSparkVertex Ai
6 Days Ago
Hybrid
Boston, MA, USA
170K-337K Annually
Expert/Leader
170K-337K Annually
Expert/Leader
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Lead design, roadmap, procurement, and scaling of Mastercard's on‑premise AI infrastructure. Architect compute, GPU, storage, and networking for training and low‑latency inference at petabyte scale; run RFIs/RFPs; define data center and cooling requirements; partner with data science, MLOps, security, and governance; influence executives and evaluate emerging AI infrastructure technologies.
Top Skills: Agentic AiCpuData Center Power Dense Rack DesignGenerative AiGpuHigh Performance StorageHigh Speed NetworkingLiquid CoolingMlopsOn-Premise Data CenterPrivate Cloud
16 Days Ago
Hybrid
Cambridge, MA, USA
230K-286K Annually
Senior level
230K-286K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Lead design, build, and operate scalable GenAI platform components including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Collaborate cross-functionally, invent LLM optimization techniques, and shape long-term technical vision for foundational AI systems.
Top Skills: AWSAws UltraclustersAzureC#C++GoGCPHugging FaceJavaLlmsNemo GuardrailsPythonPyTorchScalaVectordbs

What you need to know about the Boston Tech Scene

Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.

Key Facts About Boston Tech

  • Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
  • Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
  • Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
  • Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account