Engineering Senior Manager Jobs in Massachusetts
Engineering Senior Manager jobs in Massachusetts are among the most actively recruited senior technical leadership roles in the state, concentrated in defense and aerospace systems, life sciences instrumentation, semiconductor design, and software-defined infrastructure. Boston, Cambridge, and Waltham anchor the largest share of openings, with major employers such as Raytheon Technologies, Boston Scientific, and Analog Devices maintaining deep engineering management pipelines across the region. The most in-demand specialties are systems engineering leadership, R&D program management, and hardware development oversight. Find a role that fits below and apply directly.
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Job Summary
Senior Director, Enterprise AI Platform EngineeringThe Senior Director, Enterprise AI Platform Engineering will define and lead Insulet’s enterprise AI platform vision, strategy, and architecture, enabling the scalable adoption of Microsoft Copilot, custom copilots, AI agents, intelligent automation, and advanced AI-driven services across the organization. This leader will own end-to-end accountability for AI platform engineering, operations, governance, architecture, observability, and AI service delivery, driving enterprise standards, risk management, and technology modernization.
The ideal candidate is a strategic enterprise leader who can influence at the executive level while building and leading high-performing, multidisciplinary teams that translate AI innovation into measurable business value.


Senior Director, Enterprise AI Platform Engineering
The Senior Director, Enterprise AI Platform Engineering will set the enterprise vision, strategy, architecture, and operating model for Insulet's AI platform ecosystem. This role will own the capabilities required to safely scale Microsoft Copilot, custom copilots, AI agents, knowledge retrieval, document intelligence, semantic intelligence, and AI-powered workflow automation across the enterprise.
As a senior leader within the Enterprise AI and Data organization, this role will have end-to-end accountability across AI platform engineering, AI operations, governance automation, enterprise AI architecture, enablement, FinOps, observability, and reusable AI services. The role will shape long-term platform investments, enterprise standards, risk controls, and technology modernization priorities.
The ideal candidate is an enterprise platform leader who can operate at CTO and ELT levels while building and leading a multi-layer, diverse organization of directors, senior managers, architects, engineers, product leaders, and technical specialists.
Key Responsibilities
1. Enterprise AI Platform Strategy, Architecture, and Investment
- Define and own a 5+ year enterprise AI platform vision, architecture strategy, capability roadmap, operating model, and investment plan aligned with company strategy and technology modernization priorities.
- Set the enterprise roadmap across Microsoft Copilot, Copilot Studio, Azure AI, large language models, RAG, agents, document intelligence, semantic search, vector stores, orchestration frameworks, model gateways, and reusable AI services.
- Establish enterprise decision frameworks, reference architectures, platform patterns, reusable blueprints, and engineering standards that balance speed, security, compliance, interoperability, performance, reliability, and cost.
- Present platform strategy, investment recommendations, build-versus-buy decisions, vendor choices, value cases, and risk assessments to the CTO, ELT, and senior business and technology leaders.
- Partner with enterprise executives and technology leaders to align AI platform investments with business priorities, risk expectations, and broader modernization roadmaps.
2. AI Operations, Copilot, Agentic AI, and Enterprise Enablement
- Own the enterprise capabilities and operating model for AI operations, LLMOps, platform reliability, AI enablement, developer experience, product onboarding, and production support.
- Lead engineering patterns and reusable assets for Microsoft 365 Copilot, Copilot Studio, Teams-based assistants, custom copilots, role-based business assistants, and enterprise AI agents embedded into workflows.
- Establish enterprise enablement services, including onboarding, reference implementations, prompt and agent libraries, connectors, integration adapters, evaluation harnesses, playbooks, and communities of practice.
- Drive adoption across Commercial, Customer Service, Finance, Supply Chain, Product, Quality, Regulatory, R&D, and enterprise functions while reducing fragmented or duplicative solutions.
3. Knowledge, Document, and Semantic Intelligence Platforms
- Own enterprise knowledge retrieval, document intelligence, and semantic architecture, including ingestion, metadata, access-aware retrieval, vector indexing, source attribution, citation quality, and lifecycle standards.
- Scale reusable document intelligence capabilities for classification, OCR, extraction, summarization, search, automation, and unstructured data processing.
- Establish semantic intelligence capabilities, including business glossaries, ontologies, semantic models, metadata catalogs, knowledge graphs, domain context layers, and reusable definitions.
- Define enterprise data-readiness standards for AI, including authoritative sources, permissions, lineage, freshness, retention, quality thresholds, and human validation.
4. Governance Automation, Responsible AI Operations, FinOps, and Risk
- Own governance automation and policy-as-code capabilities that embed responsible AI, privacy, security, quality, and compliance controls into the platform lifecycle.
- Establish enterprise AI FinOps, including consumption visibility, cost allocation, forecasting, capacity planning, model routing, caching, and cost-to-value reporting.
- Set LLMOps and AI observability standards for model and prompt performance, retrieval quality, hallucination risk, citation accuracy, latency, usage, incidents, user feedback, and production reliability.
- Partner with Security, Privacy, Legal, Compliance, Finance, Quality, Regulatory, and Data Governance to provide the CTO and ELT with platform risk assessments, control effectiveness, and remediation priorities.
5. Engineering Excellence and Enterprise Delivery
- Own a portfolio of reusable AI platform services, APIs, connectors, prompt modules, agent frameworks, model gateways, evaluation tools, monitoring capabilities, and semantic services.
- Set enterprise engineering standards for versioning, testing, CI/CD, deployment, monitoring, documentation, incident response, lifecycle management, resilience, and retirement.
- Establish portfolio governance, funding priorities, delivery mechanisms, service levels, adoption measures, and value realization across platform capabilities.
- Drive enterprise adoption of common platforms and reusable services, reducing duplicate builds, fragmentation, technical debt, and time from experimentation to trusted production.
6. Multi-Layer Organizational Leadership and Enterprise Influence
- Build, lead, and develop a multi-layer, diverse organization of directors, senior managers, architects, engineers, product leaders, and technical specialists accountable for enterprise AI platform outcomes.
- Define the platform organization design, talent strategy, workforce plan, leadership structure, and succession pipeline required to scale enterprise capabilities.
- Serve as the enterprise thought leader for AI platform engineering and influence technology strategy, architecture, investments, vendor decisions, risk posture, and modernization priorities at CTO and ELT levels.
- Provide formal leadership through direct management and enterprise leadership through influence across Technology, Cybersecurity, Data and Analytics, Product Development, R&D, Quality, Regulatory, Commercial, Digital, and Operations.
Required Qualifications
- Bachelor's or Master's degree in computer science, engineering, data science, information systems, analytics, or a related technical field.
- 18+ years of progressive experience leading enterprise-scale technology, data, analytics, AI, platform engineering, or cloud engineering organizations, including significant leadership of leaders and multi-disciplinary teams.
- Demonstrated experience setting multi-year enterprise platform strategy, owning complex investment portfolios, and delivering secure, reliable, reusable services at scale.
- Strong understanding of generative AI, large language models, RAG, AI agents, copilots, embeddings, vector databases, semantic search, document intelligence, knowledge graphs, MLOps/LLMOps, APIs, and cloud-native engineering.
- Demonstrated ability to influence executive stakeholders and communicate architecture choices, investments, value, and risk at CTO and ELT levels.
Preferred Qualifications
- Experience in healthcare, medical devices, life sciences, diabetes care, digital health, or other regulated industries.
- Hands-on experience with Microsoft 365 Copilot, Copilot Studio, Azure AI, Azure OpenAI, Databricks, Snowflake, Salesforce, ServiceNow, and enterprise integration ecosystems.
- Experience building or operating AI FinOps, governance automation, AI observability, model gateways, prompt management, evaluation frameworks, or enterprise guardrail services.
- Strong executive communication and influence skills, with the ability to translate complex platform choices into clear investments, operating models, and outcomes
.
Success Measures
- Enterprise adoption and reuse of common AI platforms, agents, knowledge retrieval, document intelligence, semantic services, and guardrails.
- Progress against the 5+ year platform roadmap, investment priorities, and strategic capability milestones.
- Reduction in duplicate AI builds, technology fragmentation, technical debt, and time to trusted production.
- Improved cost transparency, platform reliability, retrieval quality, citation accuracy, user trust, and responsible AI control effectiveness.
- Strength, engagement, and succession depth of the AI platform leadership organization.
NOTE: This position is eligible for hybrid working arrangements (requires on-site work from an Insulet office). #LI-Hybrid
Additional Information:


Compensation & Benefits:

For U.S.-based positions only, the annual base salary range for this role is $280,600.00 - $420,850.00

This position may also be eligible for incentive compensation.

We offer a comprehensive benefits package, including:
• Medical, dental, and vision insurance
• 401(k) with company match
• Paid time off (PTO)
• And additional employee wellness programs

Application Details:
This job posting will remain open until the position is filled.
To apply, please visit the Insulet Careers site and submit your application online.

Actual pay depends on skills, experience, and education.Insulet Corporation (NASDAQ: PODD), headquartered in Massachusetts, is an innovative medical device company dedicated to simplifying life for people with diabetes and other conditions through its Omnipod product platform. The Omnipod Insulin Management System provides a unique alternative to traditional insulin delivery methods. With its simple, wearable design, the tubeless disposable Pod provides up to three days of non-stop insulin delivery, without the need to see or handle a needle. Insulet’s flagship innovation, the Omnipod 5 Automated Insulin Delivery System, integrates with a continuous glucose monitor to manage blood sugar with no multiple daily injections, zero fingersticks, and can be controlled by a compatible personal smartphone in the U.S. or by the Omnipod 5 Controller. Insulet also leverages the unique design of its Pod by tailoring its Omnipod technology platform for the delivery of non-insulin subcutaneous drugs across other therapeutic areas. For more information, please visit insulet.com and omnipod.com.
We are looking for highly motivated, performance-driven individuals to be a part of our expanding team. We do this by hiring amazing people guided by shared values who exceed customer expectations. Our continued success depends on it!
At Insulet Corporation all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
( Know Your Rights )
Job Summary
Senior Director, Enterprise AI Platform EngineeringThe Senior Director, Enterprise AI Platform Engineering will define and lead Insulet’s enterprise AI platform vision, strategy, and architecture, enabling the scalable adoption of Microsoft Copilot, custom copilots, AI agents, intelligent automation, and advanced AI-driven services across the organization. This leader will own end-to-end accountability for AI platform engineering, operations, governance, architecture, observability, and AI service delivery, driving enterprise standards, risk management, and technology modernization.
The ideal candidate is a strategic enterprise leader who can influence at the executive level while building and leading high-performing, multidisciplinary teams that translate AI innovation into measurable business value.


Senior Director, Enterprise AI Platform Engineering
The Senior Director, Enterprise AI Platform Engineering will set the enterprise vision, strategy, architecture, and operating model for Insulet's AI platform ecosystem. This role will own the capabilities required to safely scale Microsoft Copilot, custom copilots, AI agents, knowledge retrieval, document intelligence, semantic intelligence, and AI-powered workflow automation across the enterprise.
As a senior leader within the Enterprise AI and Data organization, this role will have end-to-end accountability across AI platform engineering, AI operations, governance automation, enterprise AI architecture, enablement, FinOps, observability, and reusable AI services. The role will shape long-term platform investments, enterprise standards, risk controls, and technology modernization priorities.
The ideal candidate is an enterprise platform leader who can operate at CTO and ELT levels while building and leading a multi-layer, diverse organization of directors, senior managers, architects, engineers, product leaders, and technical specialists.
Key Responsibilities
1. Enterprise AI Platform Strategy, Architecture, and Investment
- Define and own a 5+ year enterprise AI platform vision, architecture strategy, capability roadmap, operating model, and investment plan aligned with company strategy and technology modernization priorities.
- Set the enterprise roadmap across Microsoft Copilot, Copilot Studio, Azure AI, large language models, RAG, agents, document intelligence, semantic search, vector stores, orchestration frameworks, model gateways, and reusable AI services.
- Establish enterprise decision frameworks, reference architectures, platform patterns, reusable blueprints, and engineering standards that balance speed, security, compliance, interoperability, performance, reliability, and cost.
- Present platform strategy, investment recommendations, build-versus-buy decisions, vendor choices, value cases, and risk assessments to the CTO, ELT, and senior business and technology leaders.
- Partner with enterprise executives and technology leaders to align AI platform investments with business priorities, risk expectations, and broader modernization roadmaps.
2. AI Operations, Copilot, Agentic AI, and Enterprise Enablement
- Own the enterprise capabilities and operating model for AI operations, LLMOps, platform reliability, AI enablement, developer experience, product onboarding, and production support.
- Lead engineering patterns and reusable assets for Microsoft 365 Copilot, Copilot Studio, Teams-based assistants, custom copilots, role-based business assistants, and enterprise AI agents embedded into workflows.
- Establish enterprise enablement services, including onboarding, reference implementations, prompt and agent libraries, connectors, integration adapters, evaluation harnesses, playbooks, and communities of practice.
- Drive adoption across Commercial, Customer Service, Finance, Supply Chain, Product, Quality, Regulatory, R&D, and enterprise functions while reducing fragmented or duplicative solutions.
3. Knowledge, Document, and Semantic Intelligence Platforms
- Own enterprise knowledge retrieval, document intelligence, and semantic architecture, including ingestion, metadata, access-aware retrieval, vector indexing, source attribution, citation quality, and lifecycle standards.
- Scale reusable document intelligence capabilities for classification, OCR, extraction, summarization, search, automation, and unstructured data processing.
- Establish semantic intelligence capabilities, including business glossaries, ontologies, semantic models, metadata catalogs, knowledge graphs, domain context layers, and reusable definitions.
- Define enterprise data-readiness standards for AI, including authoritative sources, permissions, lineage, freshness, retention, quality thresholds, and human validation.
4. Governance Automation, Responsible AI Operations, FinOps, and Risk
- Own governance automation and policy-as-code capabilities that embed responsible AI, privacy, security, quality, and compliance controls into the platform lifecycle.
- Establish enterprise AI FinOps, including consumption visibility, cost allocation, forecasting, capacity planning, model routing, caching, and cost-to-value reporting.
- Set LLMOps and AI observability standards for model and prompt performance, retrieval quality, hallucination risk, citation accuracy, latency, usage, incidents, user feedback, and production reliability.
- Partner with Security, Privacy, Legal, Compliance, Finance, Quality, Regulatory, and Data Governance to provide the CTO and ELT with platform risk assessments, control effectiveness, and remediation priorities.
5. Engineering Excellence and Enterprise Delivery
- Own a portfolio of reusable AI platform services, APIs, connectors, prompt modules, agent frameworks, model gateways, evaluation tools, monitoring capabilities, and semantic services.
- Set enterprise engineering standards for versioning, testing, CI/CD, deployment, monitoring, documentation, incident response, lifecycle management, resilience, and retirement.
- Establish portfolio governance, funding priorities, delivery mechanisms, service levels, adoption measures, and value realization across platform capabilities.
- Drive enterprise adoption of common platforms and reusable services, reducing duplicate builds, fragmentation, technical debt, and time from experimentation to trusted production.
6. Multi-Layer Organizational Leadership and Enterprise Influence
- Build, lead, and develop a multi-layer, diverse organization of directors, senior managers, architects, engineers, product leaders, and technical specialists accountable for enterprise AI platform outcomes.
- Define the platform organization design, talent strategy, workforce plan, leadership structure, and succession pipeline required to scale enterprise capabilities.
- Serve as the enterprise thought leader for AI platform engineering and influence technology strategy, architecture, investments, vendor decisions, risk posture, and modernization priorities at CTO and ELT levels.
- Provide formal leadership through direct management and enterprise leadership through influence across Technology, Cybersecurity, Data and Analytics, Product Development, R&D, Quality, Regulatory, Commercial, Digital, and Operations.
Required Qualifications
- Bachelor's or Master's degree in computer science, engineering, data science, information systems, analytics, or a related technical field.
- 18+ years of progressive experience leading enterprise-scale technology, data, analytics, AI, platform engineering, or cloud engineering organizations, including significant leadership of leaders and multi-disciplinary teams.
- Demonstrated experience setting multi-year enterprise platform strategy, owning complex investment portfolios, and delivering secure, reliable, reusable services at scale.
- Strong understanding of generative AI, large language models, RAG, AI agents, copilots, embeddings, vector databases, semantic search, document intelligence, knowledge graphs, MLOps/LLMOps, APIs, and cloud-native engineering.
- Demonstrated ability to influence executive stakeholders and communicate architecture choices, investments, value, and risk at CTO and ELT levels.
Preferred Qualifications
- Experience in healthcare, medical devices, life sciences, diabetes care, digital health, or other regulated industries.
- Hands-on experience with Microsoft 365 Copilot, Copilot Studio, Azure AI, Azure OpenAI, Databricks, Snowflake, Salesforce, ServiceNow, and enterprise integration ecosystems.
- Experience building or operating AI FinOps, governance automation, AI observability, model gateways, prompt management, evaluation frameworks, or enterprise guardrail services.
- Strong executive communication and influence skills, with the ability to translate complex platform choices into clear investments, operating models, and outcomes
.
Success Measures
- Enterprise adoption and reuse of common AI platforms, agents, knowledge retrieval, document intelligence, semantic services, and guardrails.
- Progress against the 5+ year platform roadmap, investment priorities, and strategic capability milestones.
- Reduction in duplicate AI builds, technology fragmentation, technical debt, and time to trusted production.
- Improved cost transparency, platform reliability, retrieval quality, citation accuracy, user trust, and responsible AI control effectiveness.
- Strength, engagement, and succession depth of the AI platform leadership organization.
NOTE: This position is eligible for hybrid working arrangements (requires on-site work from an Insulet office). #LI-Hybrid
Additional Information:


Compensation & Benefits:

For U.S.-based positions only, the annual base salary range for this role is $280,600.00 - $420,850.00

This position may also be eligible for incentive compensation.

We offer a comprehensive benefits package, including:
• Medical, dental, and vision insurance
• 401(k) with company match
• Paid time off (PTO)
• And additional employee wellness programs

Application Details:
This job posting will remain open until the position is filled.
To apply, please visit the Insulet Careers site and submit your application online.

Actual pay depends on skills, experience, and education.Insulet Corporation (NASDAQ: PODD), headquartered in Massachusetts, is an innovative medical device company dedicated to simplifying life for people with diabetes and other conditions through its Omnipod product platform. The Omnipod Insulin Management System provides a unique alternative to traditional insulin delivery methods. With its simple, wearable design, the tubeless disposable Pod provides up to three days of non-stop insulin delivery, without the need to see or handle a needle. Insulet’s flagship innovation, the Omnipod 5 Automated Insulin Delivery System, integrates with a continuous glucose monitor to manage blood sugar with no multiple daily injections, zero fingersticks, and can be controlled by a compatible personal smartphone in the U.S. or by the Omnipod 5 Controller. Insulet also leverages the unique design of its Pod by tailoring its Omnipod technology platform for the delivery of non-insulin subcutaneous drugs across other therapeutic areas. For more information, please visit insulet.com and omnipod.com.
We are looking for highly motivated, performance-driven individuals to be a part of our expanding team. We do this by hiring amazing people guided by shared values who exceed customer expectations. Our continued success depends on it!
At Insulet Corporation all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
( Know Your Rights )
See All 123+ Engineering Senior Manager Jobs in Massachusetts
Find roles in Massachusetts that match your experience and apply in just a few clicks.
Find JobsEngineering Senior Manager Jobs by City in Massachusetts
Where Massachusetts roles are concentrated, by current openings.
Engineering Senior Manager Job Market in Massachusetts
A snapshot from current Massachusetts openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
- Consulting & Professional Services
- Electronics & Hardware
- Insurance
- Manufacturing
What Massachusetts Employers Look For
The qualifications that appear most often in engineering senior manager jobs across Massachusetts.
- Bachelor's or master's degree in engineering required, with PE licensure preferred by many Massachusetts defense and infrastructure employers
- Minimum eight to twelve years of progressive engineering experience including direct team leadership
- Demonstrated experience managing cross-functional engineering teams of ten or more engineers
- Proven ability to own project budgets, schedules, and technical deliverables from design through release
- Experience with Massachusetts-relevant domains such as defense systems, medical devices, or semiconductor development strongly preferred
- Strong background in engineering program execution methodologies including Agile, EVMS, or stage-gate development frameworks
Engineering Senior Manager Jobs in Massachusetts: Frequently Asked Questions
How do you become a engineering senior manager in Massachusetts?
Most engineering senior managers in Massachusetts follow a path that begins with an accredited engineering degree and several years of individual contributor experience before moving into team lead or principal engineer roles. Massachusetts does not require a state license to hold a management title, but employers in civil infrastructure, public-sector projects, and some defense contracts favor candidates who hold a Professional Engineer license issued or recognized by the Massachusetts Board of Registration of Professional Engineers and Land Surveyors. An MBA or graduate engineering degree accelerates promotion at the state's large research-intensive employers.
Which companies hire engineering senior managers in Massachusetts?
Employers hiring engineering senior managers in Massachusetts right now include General Dynamics Mission Systems, CVS Health, and Amazon, based on current listings on Migrate Mate as of September 2026. Massachusetts's dense concentration of defense primes, medical device manufacturers, and semiconductor firms means engineering management openings appear consistently across both large corporations and well-funded growth-stage companies throughout Greater Boston and the Route 128 corridor.
Which Massachusetts cities have the most engineering senior manager jobs?
Boston, Cambridge, and Andover account for the largest concentration of engineering senior manager openings in Massachusetts. Boston and Cambridge lead because of the headquarters, R&D centers, and hospital-affiliated engineering operations clustered there, while Waltham and Burlington draw heavy demand from the Route 128 technology and defense corridor where companies like Raytheon, Analog Devices, and numerous medtech firms maintain substantial engineering workforces.
Are there remote engineering senior manager jobs in Massachusetts?
Yes, but they are less common than in purely software-focused roles, since engineering senior managers in Massachusetts frequently oversee lab teams, hardware programs, or manufacturing operations that require on-site presence. About 55% of engineering senior manager openings tied to Massachusetts are remote or hybrid as of September 2026, with hybrid arrangements being far more prevalent than fully remote. The portions of the role most likely to be performed remotely include stakeholder reporting, budgeting, and cross-site program coordination.
How can I get hired as a engineering senior manager in Massachusetts with little or no experience?
The most realistic entry path is through a lead engineer or principal engineer role at a Massachusetts employer, where you take on direct ownership of a small team or a defined work package before pursuing a formal management title. Large Massachusetts employers such as Raytheon Technologies, Boston Scientific, and MathWorks run rotational engineering leadership development programs and new-grad associate programs that build the technical depth and cross-functional exposure hiring managers look for. Earning a Professional Engineer license through the Massachusetts Board of Registration of Professional Engineers and Land Surveyors, or completing a part-time MBA at a Massachusetts university, signals readiness for management responsibility to employers who promote from within.
Where can I find and apply to engineering senior manager jobs in Massachusetts?
You can find and apply to engineering senior manager jobs in Massachusetts on Migrate Mate, which lists current Massachusetts openings updated regularly. Find the roles that fit your background and apply directly to the ones that match.
See All 123+ Engineering Senior Manager Jobs in Massachusetts
Find roles in Massachusetts that match your experience and apply in just a few clicks.
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