Artificial Intelligence Jobs in Cambridge, MA

Lead design and delivery of an enterprise Agentic AI Platform enabling build/bring-your-own-agents. Architect production-grade services for model integration, orchestration, lifecycle management, observability, evaluation, and performance optimization while partnering with cross-functional teams, enforcing governance and responsible AI, and mentoring engineers to translate experiments into scalable, secure production systems.

Design, build, and maintain secure, scalable integrations between an agentic AI platform and enterprise systems using MCP/A2A, APIs, webhooks, and event-driven patterns. Create reusable connectors and middleware, implement authentication/authorization and secrets management, enable data exchange for structured and unstructured sources, and ensure observability, resiliency, and compliance while partnering across product, security, and platform teams.

Own Halo end-to-end: define roadmap, shape the AI-native consumer experience, coordinate advisor handoffs, and work with engineering and data science to ship multi-agent, compliance-grade AI features. Measure success across a coupled consumer-advisor product, prioritize ruthlessly with limited resources, and embed SEC-compliant traceability into product decisions.

Design, build, and operate AWS-native AI/ML systems: RAG pipelines, fine-tuned LLMs, and microservices. Implement IaC (Terraform), CI/CD, policy guardrails, and production deployments integrating Bedrock/SageMaker, LangChain, and telemetry for secure, scalable enterprise use.

Lead the product strategy for Scribd's internal developer and agentic platforms: unify AI workstreams, own internal app/plugin/agent runtimes, translate functional needs into platform requirements, drive cross-functional adoption and metrics, and run internal rollouts and evaluation to prove impact.

As an AI Engineer, you will develop AI security capabilities, integrate features for vulnerability detection, and maintain APIs for secure interactions while collaborating across teams.

As a Staff Software Engineer in Applied AI, you will architect AI systems for vulnerability detection, collaborate across teams, and improve AI model performance.

As a Senior Software Engineer on the AI Platform team, you will develop AI security features, enhance vulnerability detection, integrate AI patterns, and collaborate across functions to deliver solutions.

As a Senior Software Engineer for Applied AI, you'll develop AI security capabilities, integrate AI models, and improve security workflows within HackerOne's platform while collaborating across teams.

The Principal Software Engineer will lead architectural decisions, mentor engineers, optimize system performance and reliability, and drive technical direction for LangChain's observability and evaluations platform.

As a Machine Learning Engineer, you will optimize backend services, integrate ML models, collaborate with cross-functional teams, and support continuous improvement initiatives.

The Staff Research Scientist will develop AI algorithms, software simulations, and lead hardware prototyping in a collaborative research team setting.

Build and ship full-stack features for a production AI/LLM platform: implement polished React UIs from specs, own database and access-control/security, integrate multi-provider LLMs (RAG, agentic workflows), and formalize QA by extending test suites with integration and end-to-end coverage.

Lead and manage 2-3 AI POD teams as a player-coach to drive pipeline, forecast accuracy, revenue, and margin. Run structured GTM cadence, enforce pipeline/CRM governance, engage in strategic executive customer pursuits, coordinate shared and OEM resources, integrate PODs with regional sales, and hire and develop high-performing AI sales specialists.

Quota-carrying sales role generating, qualifying, and closing AI opportunities across an assigned region. Partner with field teams and AI ecosystem partners to build pipeline, craft executive pitch decks, sell product/infrastructure and consulting services, and maintain CRM, forecasting, and GTM operational discipline.

Drive consulting pre-sales for regional AI PODs by scoping, packaging, and positioning AI services (data readiness, governance, AI Factory, workforce AI, coding assistant pilots). Collaborate with sales, architects, and delivery to develop proposals, ensure clean handoffs, justify infrastructure, design lab/PoC engagements, and build repeatable service frameworks to accelerate customer adoption and downstream consumption.

Technical pre-sales AI architect responsible for designing end-to-end enterprise AI architectures, whiteboarding GPU cluster and MLOps solutions, coordinating ATC proof-of-concepts, aligning with NVIDIA and hyperscaler partners, producing BOMs/sizing/POC plans, and enabling clean handoffs to delivery teams while supporting revenue-generation and co-selling activities.

Sell coding-assistant and AI-native engineering solutions and co-sell NVIDIA-accelerated application services. Engage enterprise development leadership to design pilots, benchmark developer productivity, scope consulting engagements, and translate developer tools into business outcomes while collaborating within regional PODs and with NVIDIA technical teams.

Sell, scope, and package enterprise AI consulting services across workforce AI, AI Foundations, and AI Factory use cases. Develop proposals, run discovery workshops and assessments, justify infrastructure investments, design lab/PoC engagements, and ensure clean handoffs to delivery while collaborating with sales, architecture, and delivery teams to grow services pipeline and consumption.

Quota-carrying sales role generating, qualifying, and closing enterprise AI opportunities across an assigned region. Partner with field teams and AI ecosystem partners, craft executive pitch decks, drive product/infrastructure and consulting services sales, manage CRM and forecasting, and deliver multi-phase AI engagements.

Technical pre-sales AI architect responsible for designing end-to-end AI/ML architectures, leading discovery and POC lab engagements, co-selling with sales and partners, producing reference architectures, BOMs, sizing models, and ensuring clean handoff to delivery teams. Operates in a revenue-generating, customer-facing pre-sales role and collaborates with NVIDIA, hyperscalers, and infrastructure partners.

Evaluate AI outputs, perform audit-based reviews, identify failure modes and trends, apply and refine guidelines, communicate findings, participate in calibrations and stakeholder syncs, and help improve evaluation frameworks for human-in-the-loop AI.

Audit and ensure quality of data labeling outputs, coach and onboard Data Labeling Associates, provide actionable feedback, monitor workflows, identify patterns and edge cases, and help improve guidelines and processes in human-in-the-loop AI workflows.

Audit and review data labeling outputs, provide actionable feedback, train and support labeling teams, monitor workflows, identify recurring issues and edge cases, participate in calibrations and stakeholder syncs, and help improve guidelines and processes in human-in-the-loop AI workflows.

Audit and validate data labeling outputs, provide structured feedback and hands-on training to annotators, monitor workflows and escalate issues, help apply and improve guidelines, and identify patterns in human and model outputs to maintain high-quality AI training data.