Top Tech Jobs & Startup Jobs in Boston, MA

Leads Unanet’s internal data strategy and architecture for enterprise AI. Defines the shared data foundation, target architecture, governance standards, roadmap, and reusable approaches for AI assistants, agents, and workflows. Evaluates platforms and integration options, validates technical solutions, and coordinates IT, Security, Legal, Engineering, business owners, and system specialists. Advises senior leaders, establishes data quality and stewardship requirements, and helps determine when data is ready to support scalable AI initiatives.

Manage a portfolio of mid-market B2B SaaS customers, driving adoption, retention, renewals, expansion, and measurable business outcomes. Build executive relationships, create strategic account success plans, monitor customer health, lead executive business reviews, identify risks and growth opportunities, and collaborate cross-functionally with Sales, Product, Support, Professional Services, Finance, and Marketing. Serve as the customer advocate and trusted strategic advisor.

Build and maintain Customer Success and Implementation playbooks, SOPs, training programs, knowledge bases, presentation materials, and scalable workflows. Partner cross-functionally to communicate process and product changes, improve automation and efficiency, identify customer risks, and measure enablement effectiveness. Support implementation, launch readiness, customer health, escalations, business reviews, renewals, and expansion.

Lead end-to-end LLM inference performance across serving systems, models, GPU hardware, and workloads. Define rigorous benchmarks, diagnose bottlenecks from scheduling through kernels and interconnects, optimize single- and multi-node deployments, and deliver production-ready runtimes and configurations. Collaborate with product and infrastructure teams, evaluate inference technologies, and implement runtime fixes. The role requires strong Python engineering, production experience with serving engines such as vLLM or SGLang, GPU profiling, and knowledge of modern inference optimization techniques.

Owns end-to-end accounts payable operations, including invoice processing, payments, accruals, prepaids, reconciliations, and month-end/year-end close. Supports audits, maintains audit-ready documentation, strengthens internal controls, and partners with Accounting and FP&A on accruals, cash forecasting, and vendor issues. The role also drives AP automation, standardizes procedures, optimizes NetSuite and Ramp workflows, and may mentor or manage additional resources as the function grows.

Designs, implements, and manages AWS infrastructure and Infrastructure as Code automation. Partners with application engineering, quality, security, and compliance teams to deliver reliable platform solutions. Owns platform stability, observability, incident response, security best practices, and zero-downtime deployments. Participates in on-call rotations, uses metrics for decision-making, and supports application architecture decisions while continuously improving DevOps processes and automation.

Leads product initiatives from concept through launch and lifecycle management. Responsibilities include market and customer research, requirements development, roadmap planning, feature prioritization, business case and pricing development, pilot programs, product demonstrations, and cross-functional collaboration with engineering, sales, marketing, support, and internal stakeholders. The role also identifies partnership opportunities, defines success metrics, and delivers products within scope, timeline, and budget.

Lead CTV media buying and programmatic strategy across Ashley’s furniture and mattress brands. Optimize campaigns, budgets, CPMs, audience targeting, and frequency to drive online conversions and in-store sales. Manage publisher, streaming platform, ad exchange, and DSP relationships; negotiate Deal IDs and PMP agreements; oversee attribution, incrementality testing, clean-room analysis, impression deduplication, and offline conversion measurement. Partner with data science and creative teams to improve performance, unify fragmented vendor data, and achieve ROAS targets.

Build and deploy production machine learning systems that optimize Samsara’s global hardware supply chain. Responsibilities include demand, inventory, lead-time, spend, and supplier-risk forecasting; anomaly detection; feature engineering and ETL; real-time inference; MLOps; data infrastructure improvements; governance; and model monitoring. The role defines the AI transformation roadmap, partners with executive and cross-functional stakeholders, mentors scientists, and drives adoption of AI-enabled operational workflows.

Lead enterprise go-to-market execution and sales for Samsara’s Tracking Label product across strategic US accounts. Architect pilots and global shipment-network rollouts, build ROI and loss-prevention business cases, engage C-suite stakeholders, navigate complex procurement and security processes, and close large multi-year contracts. Partner with account executives, product, and GTM leadership while developing sales playbooks and enabling broader specialist teams.

Coordinates field, event, and partner marketing programs, including trade shows, conferences, webinars, regional events, sponsorships, and co-marketing campaigns. Manages stakeholders, vendors, venues, budgets, logistics, communications, and on-site execution. Supports marketing reporting and metrics covering registrations, attendance, campaigns, and events while collaborating with sales, finance, legal, and external partners.

Architect and build a high-performance trading platform for active traders. Develop responsive web interfaces integrating real-time market data, low-latency execution workflows, and advanced trading tools. Collaborate with cross-functional engineering teams on large-scale initiatives, emphasizing scalability, performance, API quality, maintainability, developer experience, and end-user usability.

Own the reliability and quality of an AI copilot for a trading platform. Build evaluation frameworks, benchmarks, quality gates, monitoring, incident response, and model improvement workflows. Partner with engineering and product to create safe, auditable tool interactions and improve assistant behavior. Develop domain expertise in trading, risk, margin, execution, and portfolio reasoning while operating across model, backend, and frontend systems.