Top Senior Level Jobs in Boston, MA

Leads cross-functional security programs connecting security risk engineering with Product, Engineering, and SRE teams. Manages Security by Design, Secure-SDLC, vulnerability remediation, compliance audits, security roadmaps, governance, and AI-enabled process automation. The role requires financial services and payments expertise, cloud architecture knowledge, and proficiency with PCI-DSS, SOX, SOC 1, and SOC 2. It also provides coaching and drives secure technical enablement across globally distributed teams.

Manage the full sales cycle for education-sector clients, from prospecting and pipeline generation through closing. Build relationships with colleges and universities, present Flywire’s value proposition, achieve revenue quotas, and develop new accounts across the Americas. Partner with product, technical, operations, and marketing teams to support solution delivery and implementation. Conduct market research, participate in lead-generation campaigns, and manage multiple projects while traveling up to 35%.

Leads cybersecurity threat intelligence and vulnerability management initiatives, analyzing threats, deploying intrusion detection and network security platforms, and developing proactive defenses. Manages client projects, including planning, budgeting, execution, and delivery, while mentoring teams and resolving stakeholder issues. Partners with leadership to maintain quality and timelines, conducts security research, and promotes innovation across cybersecurity practices.

Uses advanced analytics, business intelligence, and data science to deliver strategic insights and solutions for AML and sanctions clients in banking and capital markets. Responsibilities include analyzing complex datasets, developing data pipelines and architecture, creating scalable visualization solutions, collaborating with teams, managing stakeholders, building client relationships, and solving complex problems. The role also involves mentoring and managing others while maintaining professional and technical standards.

Develop and execute Google alliance marketing and channel strategies to drive revenue, improve customer experience, and increase brand visibility. Manage external channel partnerships, optimize distribution, conduct market research, and identify new business opportunities. Lead teams through complex situations, communicate impactful messages, coach employees, validate outcomes with stakeholders, and improve marketing processes while upholding professional standards.

Designs and implements security for embedded consumer electronics products, including ARM TrustZone applets, cryptographic device identity, secure boot, firmware protection, key management, and trust chains. Defines security requirements, performs assessments and testing, supports compliance audits, mitigates vulnerabilities, and advises engineering teams through architecture and code reviews. Collaborates with firmware, DevOps, cloud, manufacturing, and program management teams to strengthen product security and incident response.

As a Software Engineer III, you will design, build, and enhance high-complexity components, mentor team members, and collaborate on projects, ensuring high-quality code and customer-centric solutions.

Design, build, deploy, scale, and maintain production machine learning systems and models. Lead technical design, model and application development, data pipeline construction, cloud architecture, testing, CI/CD, monitoring, governance, and responsible AI practices. Collaborate with Product, Data Science, and Agile engineering teams while leading teams developing enterprise AI coding tools.

Leads the design, development, deployment, and maintenance of machine learning systems at scale. Responsibilities include building ML models and data pipelines, writing production code, optimizing cloud architectures, automating testing and deployment, monitoring and retraining models, and ensuring performance, governance, security, responsible AI, and explainability. The role collaborates with Product and Data Science teams in an Agile environment focused on enterprise AI coding tools.

Build and support production AI platform components including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, experimentation, and observability. Optimize large-scale AI systems for scalability, latency, throughput, cost, and hardware utilization. Partner with engineering, research, product, and program teams; contribute to technical vision and roadmap; and lead or mentor engineering teams.

Design, develop, optimize, and test real-time acoustic signal-processing algorithms for distributed undersea systems. Implement embedded software across low-SWAP, ARM, DSP, and server-class hardware while meeting stringent performance requirements. Collaborate on hardware integration and validation using C/C++, Python, MATLAB, Linux, Git, containers, and Jira. The role requires embedded systems, signal processing, hardware-interface, optimization, and debugging expertise, plus an active security clearance and eligibility for special access programs.

Designs, develops, integrates, tests, and demonstrates autonomy algorithms and software for unmanned platforms and mission systems. Provides technical leadership and mentoring across the software lifecycle, develops backend-focused algorithmic applications, supports system and system-of-systems architecture, and collaborates with research scientists to transition mathematical concepts into production software. Work includes mission planning, automated control, DevSecOps, CI/CD, code quality, Agile execution, and team leadership.

Leads Data Fulfillment operations for Life Sciences real-world data products, overseeing preparation, packaging, validation coordination, certification support, client delivery, escalations, team performance, and operational controls. Partners cross-functionally to modernize workflows, improve reliability and scalability, resolve client questions, and implement automation and AI-enabled efficiencies. Builds an accountable, collaborative team culture while supporting revenue-critical delivery and client satisfaction.

Leads Liberty Mutual’s global Finance Technology strategy, transformation portfolio, and organization of approximately 220 employees and 300 contractors. Oversees modernization across accounting, treasury, tax, reinsurance, risk, actuarial, data, architecture, security, and enterprise platforms. Partners with CFO leadership, manages approximately $200 million in annual technology investment, drives measurable delivery outcomes, develops enterprise data and AI capabilities, governs vendors, and builds a high-performing technology organization through sustained transformation.

Leads engineering teams supporting Liberty Mutual’s Guidewire ClaimCenter application and database platforms. Responsibilities include people leadership, delivery accountability, technical guidance, platform migration to Guidewire SaaS, SRE practices, technical debt reduction, risk management, Agile/SAFe planning, hiring, vendor coordination, performance management, and financial planning. The role partners with architects, product owners, technology teams, and business stakeholders to maintain stable, scalable platforms supporting claims transformation initiatives.

Lead identification, definition, and incubation of strategic innovation opportunities for Global Risk Solutions. Design experiments, build prototypes, coordinate technical delivery, partner with stakeholders to de-risk initiatives, and transition validated products/services back to the core business.

Own the strategy and roadmap for WHOOP’s foundational sensing algorithms. Lead cross-functional work across product, sensor intelligence, machine learning, hardware, embedded systems, and science to improve measurement accuracy, reliability, robustness, and performance. Use field data, validation, member feedback, and benchmarking to identify opportunities, define success criteria, make technical tradeoffs, and translate sensing advances into improved health and performance experiences.

Build and scale production-quality AI/ML systems for scientific and clinical workflows. Responsibilities include developing generative AI, agentic, predictive, foundation model, RAG, and fine-tuned systems; engineering data and ETL platforms; deploying cloud infrastructure and CI/CD; creating evaluation harnesses; debugging prototypes; assessing build-versus-buy options; establishing safeguards and SOPs; and collaborating with biologists, immunologists, computational scientists, and clinicians.