Top Tech Jobs & Startup Jobs in Boston, MA

Leads program scheduling for aerospace and defense projects, integrating cross-functional plans and schedules. Owns project schedules, analyzes critical paths, reconciles cost and schedule performance, monitors earned value and variances, and supports integrated master plans and schedules. Works with program, finance, engineering, manufacturing, and cost teams to ensure contractual schedule objectives are met and resolve planning conflicts.

Leads finance for CUAS international and strategy portfolios, overseeing program controls, earned value management, forecasts, EACs, operating plans, proposals, investments, overhead, and risk management. Partners with senior leadership, presents financial insights, supports strategic decisions, and manages finance professionals. The role requires strong FP&A, P&L, program control, forecasting, communication, and supervisory experience.

Supports engineering and program leaders with earned value management, cost and schedule analysis, forecasts, quarterly EACs, monthly LREs, budget change requests, variance reporting, and risk and opportunity assessments. Uses SAP, APEX, IMS, and PMX tools to monitor actual costs, analyze labor and financial performance, and communicate results that support predictable program outcomes.

Supports global trade compliance for international aerospace and defense programs. Prepares export authorizations, interprets ITAR and EAR regulations, determines export authorities and exemptions, facilitates hardware exports, tracks authorization status, supports audits and investigations, delivers employee training, and advises stakeholders on U.S. and non-U.S. export/import requirements. Requires active Secret clearance, U.S. citizenship, relevant trade compliance experience, and minimal quarterly domestic travel.

Leads FP&A budgeting support for Legal and Compliance, including annual operating plans, forecasts, variance reporting, expenditure analysis, financial controls, and compliance. Partners with stakeholders across Raytheon cost accounting segments, prepares pricing and cost submissions, performs ad hoc analysis, maintains historical records, and supports purchase orders and invoice processing. Communicates findings to management and non-finance stakeholders while ensuring accurate financial planning and reporting.

Supports engineering and program leads with earned value management, financial analysis, forecasts, and cost and schedule control. Prepares quarterly EACs, monthly LREs, budget change requests, variance reports, and risk and opportunity assessments. Monitors actual costs, analyzes budget and schedule performance, and partners with control account managers using SAP, APEX, IMS, and PMX tools.

Lead cost control and financial execution for the MRAD NASAMS program: implement and maintain EVMS, develop forecasts (EAC/LRE), manage program logs, provide financial guidance, support FP&A, and review financial reports and proposals.

Serves as the primary finance partner to Hardware Engineering leadership, leading cost forecasts, annual operating plans, utilization and overhead outlooks, variance analysis, financial modeling, monthly reviews, and quarterly EAC reporting. Maintains reporting tools and cost models, ensures compliance with internal controls and government accounting standards, identifies financial risks and opportunities, and mentors junior analysts.

Defines enterprise AI and machine learning architectures spanning Generative AI, agentic AI, data, applications, cloud, infrastructure, and enterprise systems. Translates business requirements into architecture blueprints, technical strategies, and implementation roadmaps; develops reusable standards and design patterns; evaluates technology alternatives; and leads technical reviews. The role also establishes patterns for MLOps, model serving, monitoring, governance, security, and deployment across cloud, hybrid, on-premises, and restricted environments while mentoring engineering teams.

Design, build, evaluate, and deploy production AI and ML solutions, including generative AI, large language models, retrieval-augmented generation, and agentic workflows. Develop reliable software, APIs, integrations, evaluations, and observability capabilities while partnering with architecture, platform, data, cybersecurity, and business teams. Apply AI engineering practices across enterprise, cloud, hybrid, and regulated environments.