Top 301 Ai agent architect Jobs in Massachusetts

AI Agent Architect
Edisyl —Boston, MA
- Online Application
- Remote
- System design
- Databases
- APIs
AI Engineer
Rockland Trust —Massachusetts
- Azure
- 5 years
- SQL
- Wellness program
- Health insurance
AI Product Owner
Blue Cross Blue Shield of Massachusetts —Boston, MA
- $111,960 - $136,840 a year
- Full-time
- Azure
- Management
- Computer Science
- Health insurance
- Dental insurance
Lead Solutions & AI Enablement Architect
Humana —Boston, MA
- $142,300 - $195,700 a year
- Full-time
- Remote
- Computer science
- Computer Science
- HIPAA
- Paid parental leave
- Paid holidays
Staff Enterprise Data Architect
Ōura —Boston, MA
- $169,150 - $233,000 a year
- Remote
- Organizational skills
- Senior level
- Leadership
- Paid holidays
- Health insurance
Applied AI Engineer/Architect
West Monroe —Boston, MA
- $236,300 - $304,200 a year
- Email
- 7 years
- Azure
- Up to 50% travel
- Paid parental leave
- Paid holidays
Forward Deployed Engineer III, Generative AI, Google Cloud
Google —Cambridge, MA
- $174,000 - $253,000 a year
- Full-time
- Computer science
- Computer Science
- 5 years
- Paid holidays
- Disability insurance
Agentic AI Engineer — Healthcare AI
Deloitte —Boston, MA
- $110,700 - $372,900 a year
- Full-time
- Computer Science
- Up to 50% travel
- System design
AI Solution Architect
Blue Cross Blue Shield of Massachusetts —Boston, MA
- $175,860 - $214,940 a year
- Full-time
- Computer science
- Computer Science
- Office
- Health insurance
- Dental insurance
Presales Solutions Architect
Workato —Boston, MA
- Remote
- Computer Science
- Bachelor of Science
- Databases
Lead, Engineering Excellence
Bain & Co. —Boston, MA
- $179,875 - $203,925 a year
- Full-time
- Hybrid work
- Azure
- Computer Science
- Office
- Wellness program
- Paid holidays
Quick Apply
Partner Technical Architect
ServiceNow —Boston, MA
- $134,250 - $221,550 a year
- Online Application
- Remote
- Residential
- 8 years
- Fair chance
- Employee stock purchase plan
- Health insurance
Quick Apply
Expert Senior Manager, Engineering Excellence
Bain & Co. —Boston, MA
- $258,425 - $293,500 a year
- Full-time
- Hybrid work
- Azure
- Management
- Computer Science
- Wellness program
- Paid holidays
Quick Apply
Expert Senior Manager, AI Engineering
Bain & Co. —Boston, MA
- $258,000 - $293,500 a year
- Full-time
- System design
- Office
- Continuous improvement
- Wellness program
- Paid holidays
Quick Apply
Principal Analyst, CGT Agentic Solutions
Vertex Pharmaceuticals —Boston, MA
- $142,800 - $214,200 a year
- Full-time
- Hybrid work
- Computer science
- Azure
- Computer Science
- Loan repayment program
- Health insurance
Principal Software Engineer - AI
New Balance —Brighton, MA
- $120,000 - $180,000 a year
- Full-time
- Hybrid work
- Azure
- Computer Science
- System design
- Disability insurance
- Health insurance
Senior Principal AI Engineer
Vertex Pharmaceuticals —Boston, MA
- $188,000 - $282,000 a year
- Full-time
- Computer science
- Computer Science
- System design
- Loan repayment program
- Health insurance
12d
Software Architect
Motion Recruitment —Framingham, MA
- Azure
- Computer Science
- System design
4d
Senior Data Scientist - Worcester, Ma
Motion Recruitment —Worcester, MA
- Contract
- Hybrid work
- Master's degree
- 8 years
- Bachelor's degree
4d
Senior Machine Learning Engineer - Boston - Rag/Ai/LLM
Motion Recruitment —Boston, MA
- Contract
- Hybrid work
- Computer Science
- 11+ years
- AWS
- Health insurance
- Dental insurance
4d

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ai agent architect jobs near massachusetts

AI Agent Architect

Edisyl
Boston, MA

Apply Now

Job Details

Full-time

Qualifications

Application deployment
Enterprise software systems development
Databases
System deployment

Full Job Description

Who This Is For

Building an agent is easy. Getting it to produce the same right answer three times in a row — on real enterprise data, in a regulated environment, without a human checking every output — that's the actual problem.

You've shipped AI agent systems to production on real, unclean data. Not a demo dataset. You know the accuracy cliff. You know why prompting cannot fix semantic problems. You've built systems that don't rely on the model getting it right every time, and you've built the judgment to know when to ship anyway.

You're not looking for a well-defined architecture to implement. You're looking for the unsolved problem — and the mandate to build the solution that becomes the standard.

About edisyl

edisyl builds AI solutions that turn messy institutional data into decisions, workflows, and outcomes. We came out of blockchain data infrastructure — 8 years, 20+ chains, 700M+ resolved wallets — and now deploy that capability to enterprises navigating the same challenge: how to make their data work for them at scale, without armies of analysts.

We have active deployments with a financial institution and Interlochen, a proven architecture, and inbound from firms that need what we've built. The technology works. What we're building now is the enterprise motion around it.

The Role

You own the architecture that makes our agent fleets reliable: the harness, the tooling, the orchestration patterns, the semantic layers that keep outputs grounded in organizational context. You work on Forge (our agent framework), Lattice (fleet orchestration), and Stratum (semantic intelligence) — building and extending the systems that production deployments run on.

You care obsessively about output quality — not because someone told you to, but because you've seen what happens when agents drift. You solve for quasi-determinism: agents that use validated tools instead of guessing at raw data, producing consistent and auditable results at scale. This is a Staff-level role — you define the architecture, set the standards, and make principled decisions without waiting for a framework to be handed to you.

What You'll Actually Do

Design and build the architecture for AI agent workflows — planning loops, tool use, memory, retrieval, and human-in-the-loop checkpoints
Evaluate, integrate, and fine-tune foundation models and LLM APIs for specific enterprise use cases and data types
Define standards for agent reliability, observability, and failure modes in production deployments
Collaborate with Forward-Deployed Engineers to translate what's working in client environments into reusable platform components
Build internal tooling and eval harnesses to assess agent quality, hallucination rates, and task completion
Make principled, documented architectural decisions — and stay current enough with the ecosystem to know what to adopt and what to ignore

What Success Looks Like in Year One

You've shipped meaningful improvements to Forge, Lattice, or Stratum that are running in production. You've established the eval framework the team uses to assess agent quality. The Forward-Deployed Engineers trust the platform enough to focus on client problems instead of working around infrastructure limitations. At least one architectural decision you made is something we're still building on two years from now.

The measure isn't how sophisticated the architecture is. It's whether the agents produce the right outputs reliably enough that customers act on them without checking every result.

Compensation

Competitive base salary and meaningful early-stage equity. This is a foundational technical role and we price it that way. We'll be transparent about the full picture in our first conversation.

Who We're Looking For

Experience

6–10 years building production AI or data systems — not prototypes; systems that run reliably at scale under real conditions
Deep hands-on experience with multi-agent architectures: context windows, memory management, dependency graphs, and where things break in practice
Strong Python and familiarity with agent frameworks — LangChain, LlamaIndex, AutoGen, or equivalent — or a clear, documented opinion on why you built your own
Practical experience with RAG architectures, vector databases, and context window management in production settings
Experience deploying LLM-powered systems in enterprise contexts — data security, access controls, audit logging

The Stuff That's Harder to Teach

LLM failure mode literacy. You know the accuracy cliff. You know why prompting cannot fix semantic problems. You build systems that don't rely on the model getting it right every time.
Production instincts. You don't consider something done until it's been wrong three times and you've fixed it twice — and you've built the judgment to know when to ship anyway.
Strong opinions on agent design. You have a clear answer to why most agent architectures fail at enterprise scale — and you've built something that doesn't.
Systems thinking. You design for failure modes first. Happy paths are not the interesting problem.

Bonus (Genuinely Not Required)

ML research exposure — fine-tuning, RLHF, model evaluation methodology
Production AI deployments in regulated industries — financial services, insurance, healthcare
Familiarity with blockchain data infrastructure or institutional crypto

Why This, Why Now

edisyl is at the moment where the technology is proven and the enterprise problem is clear. The person who takes this role will define the architecture that production deployments run on — not inherit it. The platform is real, the customers are real, and the hard problems are still open. That's a rare place to work and a real chance to build something that matters.

To Apply

Complete the online application and include responses to: 1) why this role fits where you are in your career right now, and why you are the right person for it; and 2) one example of an agent system or AI infrastructure decision you made in production — what the constraints were, what broke, and what you built to fix it.

No template. Just tell us the story.

Apply Now

Refine Your Search

ai agent architect jobs in massachusetts

AI Agent Architect

AI Engineer

AI Product Owner

Lead Solutions & AI Enablement Architect

Staff Enterprise Data Architect

Applied AI Engineer/Architect

Forward Deployed Engineer III, Generative AI, Google Cloud

Agentic AI Engineer — Healthcare AI

AI Solution Architect

Presales Solutions Architect

Lead, Engineering Excellence

Partner Technical Architect

Expert Senior Manager, Engineering Excellence

Expert Senior Manager, AI Engineering

Principal Analyst, CGT Agentic Solutions

Principal Software Engineer - AI

Senior Principal AI Engineer

Software Architect

Senior Data Scientist - Worcester, Ma

Senior Machine Learning Engineer - Boston - Rag/Ai/LLM

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