Top Tech Jobs & Startup Jobs in Boston, MA

Lead AI Engineer responsible for developing AI-powered products, optimizing large language model inference, and collaborating across teams to enhance customer interactions and business value.

Lead AI Engineer responsible for designing and developing AI-powered products, utilizing ML algorithms, and optimizing large-scale AI systems. Collaborate with cross-functional teams to enhance customer experience and drive AI initiatives at Capital One.

The Applied Researcher I will work in AI Foundations to develop multi-agent systems, harness machine learning for customer experiences, and engage in applied research using modern AI techniques.

As a Lead Data Engineer, you will collaborate with Agile teams, develop technical solutions, and enhance cloud-based data warehousing to empower financial services for customers.

Lead Workday functional engineer responsible for designing, configuring, and supporting Workday HCM modules (HCM, Recruiting, Compensation, Payroll, Benefits). Partner with product owners, provide production support, automate processes, maintain documentation, and drive process improvements and Workday upgrades.

Lead medium-to-large cross-functional finance product projects end-to-end: establish structure, manage timelines/budgets, maintain governance and documentation, run OKR reporting, support org communications, build an AI-powered learning/onboarding strategy, and partner with stakeholders to streamline processes and mitigate risk.

Build, deploy, and maintain production ML and AI systems (including LLMs, RAG, similarity search, guardrails, observability). Partner with cross-functional teams to design data pipelines, fine-tune models, monitor performance, and apply Responsible/Explainable AI best practices while contributing technical vision and roadmap for risk-focused AI products.

Lead enterprise-scale Generative AI programs from research to production, focusing on multi-agent conversational systems, agentic architectures, pretraining/finetuning, and inference optimization. Drive cross-functional delivery, manage technical risk, establish evaluation and deployment frameworks, partner with risk/compliance, and ensure scalable, secure adoption of AI solutions.

Lead design, development, deployment, and support of production-scale AI systems (foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, observability). Drive LLM optimizations, technical vision, and cross-functional delivery of responsible AI products.

Lead design and delivery of an agentic AI platform: define architecture, standardize agentic workflows, build GenAI SDK/CLI, harden guardrails and observability, optimize orchestration and costs, own Helm/K8s operators for autoscaling, incubate RFCs and proofs of concept, and mentor engineering leaders while evangelizing platform practices internally and externally.