Top Tech Jobs & Startup Jobs in Boston, MA

Lead engineering projects and developers building cloud-based, AI-powered risk management solutions. Design distributed microservices and full-stack systems, establish architecture and coding standards, mentor engineers, improve performance, reduce technical debt, and guide Agile teams. The role uses multiple programming languages, databases, AWS and other cloud services, Docker, Kubernetes, APIs, CI/CD, infrastructure as code, automated testing, and observability while influencing long-term technology strategy.

Lead technical vision and architecture for complex software systems, ensuring scalable, performant, and operable solutions. Modernize monoliths into microservices and event-driven platforms, define API and platform standards, lead cross-divisional initiatives, and contribute hands-on to software engineering. Mentor engineers, promote engineering excellence, communicate technical knowledge, and advise leaders on long-term technology strategy.

Lead the architecture and development of enterprise AI platforms, including foundation model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize AI systems for cost, latency, throughput, scalability, safety, and transparency. Set long-term technical strategy, drive organization-wide standards, lead platform initiatives, partner cross-functionally, and mentor senior engineering and research leaders.

Build and deploy scalable AI systems, including foundation model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize model performance, GPU/TPU utilization, latency, throughput, and cost. Own complex AI architecture, define reliability objectives, lead technical reviews, ensure security and compliance, contribute to foundational AI roadmaps, and mentor engineers on scalable design and research-to-production practices.

Leads technology projects and software engineers building AI-powered risk management solutions. Develops distributed microservices and full-stack systems using cloud platforms, databases, containers, APIs, and modern programming languages. Provides technical leadership across Agile teams, establishes engineering standards, partners with architects and product managers, mentors engineers, improves system performance, reduces technical debt, and contributes to long-term technology strategy.

Leads enterprise data science initiatives for agentic AI products, including AI/ML model development, experimentation, telemetry analysis, and strategic recommendations for senior leadership. Partners with data scientists, engineers, and product managers while translating complex statistical insights into business outcomes. Requires extensive experience in quantitative analytics, large-scale data analysis, production AI/ML deployment, A/B testing, and team leadership.

Leads full-stack software engineering projects and developer teams building cloud-based, distributed microservices and regulatory solutions. Responsibilities include designing service boundaries, developing APIs and reusable frameworks, improving system performance, reducing technical debt, establishing engineering standards, mentoring engineers, and influencing technology strategy. The role uses modern programming languages, databases, AWS and other cloud platforms, containers, CI/CD, infrastructure as code, automated testing, observability, and AI-assisted development tools.

Leads full-stack and DevOps engineering efforts across distributed microservices, cloud-based systems, APIs, databases, and containerized platforms. Provides technical direction, mentors engineers, establishes development standards, partners with architects and product managers, improves system performance, reduces technical debt, and influences technology strategy. The role requires expertise in cloud platforms, CI/CD, infrastructure as code, automated testing, observability, and modern programming languages.

Designs, develops, deploys, and supports large-scale AI systems, including foundation models, LLM inference, agentic workflows, similarity search, guardrails, and model evaluation. Defines enterprise AI architecture, optimizes model performance, cost, latency, and throughput, establishes AI safety and governance standards, leads multi-year platform initiatives, and mentors senior technical leaders across engineering and research.

Leads data engineering architecture and modeling initiatives, designing scalable pipelines, cloud data platforms, and reusable data solutions. Collaborates with engineering, product, analytics, and data science teams while mentoring developers and establishing common design patterns. Responsibilities include distributed data processing, relational and NoSQL systems, data security, observability, streaming pipelines, and operational excellence across platforms such as Databricks and Snowflake.