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Ai Automation Engineer Jobs in Boston, MA (NOW HIRING)

1 point system

Senior AI/Automation Engineer

Boston, MA · On-site

$113K - $148K/yr

Requirement - Senior AI/Automation Engineer Location- Boston, MA and Minneapolis, MN(4 days a week on-site) Mode of Interview : 3 rounds, all virtual Contract W2 We are seeking a Senior AI Automation ...

Wilmerhale

AI Automation Engineer

Boston, MA · On-site

What You Will Be Doing The Automation Engineer is responsible for leading the design, implementation, and maintenance of automated and AI based solutions to improve legal workflows. This role ...

WorkHero

AI Automation Engineer

Cambridge, MA · On-site +1

WorkHero is building the AI-powered back office for the skilled trades, starting with the $50B+ HVA ... As our product continues to advance, the reach of each automation engineer multiplies and the scope ...

Later

Senior AI Automation Engineer

Boston, MA · On-site +1

$113K - $148K/yr

About this position: We're hiring an AI Automation Engineer to embed across teams at Later, Operations, Finance, Marketing, Customer Success, and beyond, and replace manual, repetitive work with ...

C-4 Analytics

AI Automation Specialist

Wakefield, MA · On-site

$100 - $130/hr

AI Automation Specialist, Wakefield, MA - C-4 Analytics The ideal candidate understands the ... Engineering Mindset: Thinks in systems (inputs/outputs/failure modes), is fluent in APIs and data ...

Hasbro

Automation Engineer

Boston, MA · On-site

The Automation Engineer sits in the Power Platform space and is responsible for designing, building ... AI & Copilot Solutions * Design and deploy conversational agents and AI-powered workflows using ...

Hasbro

Automation Engineer

Boston, MA · On-site

The Automation Engineer sits in the Power Platform space and is responsible for designing, building ... AI & Copilot Solutions * Design and deploy conversational agents and AI-powered workflows using ...

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All JobsAi Automation Engineer JobsAi Automation Engineer Jobs in Boston, MA

Ai Automation Engineer information

See Boston, MA salary details

$40.2K

$116.4K

$177.1K

How much do ai automation engineer jobs pay per year?

As of Aug 28, 2026, the average yearly pay for ai automation engineer in Boston, MA is $116,368.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,000.00 and $134,200.00 per year, depending on experience, location, and employer.

What is an AI automation engineer?

AI Automation Engineers are professionals who design, develop, and implement artificial intelligence solutions to automate tasks and workflows within organizations. They combine expertise in AI, machine learning, and software engineering to create systems that can perform repetitive or complex tasks efficiently with minimal human intervention. Their work often involves building and integrating AI models, optimizing processes, and ensuring the reliability and scalability of automated solutions. These engineers collaborate closely with data scientists, software developers, and business stakeholders to align automation initiatives with organizational goals.

What skills and qualifications are needed to thrive as an AI automation engineer?

To thrive as an AI Automation Engineer, you need strong programming skills (such as Python), a solid understanding of machine learning concepts, and typically a degree in computer science, engineering, or a related field. Familiarity with automation frameworks, cloud platforms (like AWS, Azure, or GCP), and machine learning libraries (such as TensorFlow or PyTorch) is often required. Problem-solving ability, adaptability, and effective communication are crucial soft skills for collaborating across teams and addressing complex technical challenges. These skills ensure the successful design, implementation, and scaling of automated AI solutions that drive business efficiency and innovation.

What are common challenges faced by AI automation engineers during project implementation?

AI Automation Engineers often encounter challenges such as integrating new AI models with existing legacy systems, ensuring data quality for accurate model outputs, and managing stakeholder expectations regarding automation outcomes. They must also address issues related to model scalability and robustness, especially when deploying solutions in dynamic production environments. Collaboration with cross-functional teams—including data scientists, software engineers, and business analysts—is essential to navigate these complexities and deliver effective automation solutions.

What is the difference between Ai Automation Engineer vs Data Scientist?

AspectAi Automation EngineerData Scientist
Required CredentialsBachelor's in Computer Science, Engineering, or related field; knowledge of AI, automation toolsBachelor's or higher in Statistics, Computer Science, or related; strong analytical skills
Work EnvironmentTech companies, automation firms, R&D labs; focus on developing AI-driven automation solutionsData analysis teams, research institutions; focus on data modeling and insights
Employer & Industry UsageUsed in manufacturing, software development, AI startupsUsed across finance, healthcare, marketing, and tech sectors
Common Search & Comparison IntentUnderstanding roles in AI automationExploring data analysis careers

While both roles involve working with data and AI, Ai Automation Engineers focus on developing automated AI systems and integrating AI into processes. Data Scientists analyze data to extract insights and build models. The roles overlap in AI knowledge but differ in application and focus areas.

Is AI automation a high paying job?

AI automation engineers typically earn higher-than-average salaries due to their specialized skills in machine learning, programming, and data analysis. Salaries vary based on experience, location, and industry, but the role is generally considered well-compensated within the tech field.

Is AI automation engineer in demand?

AI automation engineers are in high demand due to the increasing adoption of artificial intelligence and automation across industries. They are needed to develop, implement, and maintain AI-driven systems, often requiring skills in machine learning, programming, and data analysis. Job opportunities are growing as companies seek to improve efficiency and innovation through automation technologies.

What are popular job titles related to Ai Automation Engineer jobs in Boston, MA?

For Ai Automation Engineer jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Ai Automation Engineer jobs in Boston, MA look for?

The top searched job categories for Ai Automation Engineer jobs in Boston, MA are:

What cities near Boston, MA are hiring for Ai Automation Engineer jobs?

Cities near Boston, MA with the most Ai Automation Engineer job openings:

Ai Automation Engineer jobs near you
Infographic showing various Ai Automation Engineer job openings in Boston, MA as of August 2026, with employment types broken down into 76% Full Time, and 24% Contract. Highlights an 86% In-person, 5% Hybrid, and 9% Remote job distribution, with an average salary of $116,368 per year, or $55.9 per hour.

Senior AI/Automation Engineer

1 point system

Boston, MA • On-site

$113K - $148K/yr

Contractor

Re-posted 22 days ago

Job description

Requirement - Senior AI/Automation Engineer

Location- Boston, MA and Minneapolis, MN(4 days a week on-site)

Mode of Interview : 3 rounds, all virtual

Contract W2

We are seeking a Senior AI Automation Engineer to lead the next phase of AI-enabled SDLC maturity across Investment Technology. This role is responsible for defining, building, and scaling AI-driven automation across the software delivery lifecycle—leveraging Anthropic Cloud Code–based capabilities, agentic workflows, and enterprise-grade GenAI platforms.
The ideal candidate brings hands-on experience operationalizing LLMs at scale, deep understanding of modern SDLC practices, and a strong bias toward automation, governance, and measurable business outcomes. This role will directly influence how software is designed, built, tested, and deployed across Ameriprise.
AI-Enabled SDLC Transformation
· Define and execute a GenAI-augmented SDLC strategy, embedding AI across requirements, design, development, testing, deployment, and auditability.
· Drive spec-to-code, code-to-test, and test-to-deployment automation using LLM-powered workflows aligned to enterprise SDLC standards 1.
· Partner with Architecture, DevSecOps, Risk, and Compliance teams to ensure secure, governed, and auditable AI adoption.
Anthropic Cloud Code & Agentic Automation
· Serve as the subject matter expert for Anthropic Cloud Code capabilities, including:
o Prompt engineering standards
o Agent-based orchestration patterns
o Secure model invocation and policy enforcement
· Design and deploy agentic AI workflows to automate:
o Requirements for elaboration and decomposition
o Jira story and acceptance criteria generation
o Unit, integration, and UAT test generation
o SDLC artifact and control evidence creation
Enterprise Platform Enablement
· Integrate AI automation into existing enterprise platforms (e.g., CI/CD pipelines, SDLC tooling, cloud platforms).
· Establish reusable AI components, frameworks, and guardrails for product and engineering teams.
· Enable adoption through reference architectures, implementation patterns, and developer enablement.
Value Realization & Measurement
· Identify and quantify productivity, quality, and cycle-time improvements driven by AI.
· Define KPIs and success metrics tied to SDLC efficiency, developer experience, and risk reduction.
· Support executive visibility into AI-driven outcomes and maturity progress.
Preferred Qualifications
· Experience integrating GenAI into requirements management, testing automation, and SDLC controls.
· Familiarity with enterprise GenAI governance models, including model risk management and auditability.
· Experience working in financial services or highly regulated industries.
· Thought leadership in AI platforms, automation, or engineering productivity initiatives.
What Success Looks Like
· AI-driven automation measurably reduces SDLC cycle time and manual effort.
· Development teams consistently leverage AI-generated requirements, code, and tests within governed workflows.
· Anthropic Cloud Code capabilities are adopted as a standard, reusable enterprise platform capability.
· Ameriprise achieves a demonstrable increase in SDLC maturity, quality, and