Artificial Intelligence Jobs in Cambridge, MA

Supports firm-wide adoption and effectiveness of AI tools by configuring secure data integrations, MCP connections, agentic workflows, and custom agents in Microsoft Foundry. Troubleshoots APIs and AI connectivity, coordinates vendor onboarding, develops documentation and training, tracks adoption and ROI, and supports AI governance, privacy, and security compliance. The role requires technical integration experience, scripting or development skills, strong communication, and the ability to enable AI solutions across business workflows.

Design, build, and optimize software applications and systems; implement software architecture and design patterns; improve performance, scalability, and reliability; collaborate with cross-functional teams; conduct code reviews and ensure adherence to best practices.

Own the product roadmap for AI workload and agent runtime orchestration across Kubernetes clusters and heterogeneous accelerators. Responsibilities include deployment APIs, workload placement, capacity, autoscaling, isolation, networking, governance, metering, reliability, and auditability. The role spans two engineering pods and requires deep expertise in Kubernetes, GPUs, distributed systems, multi-tenancy, platform APIs, and technical prototyping, with influence across matrixed teams and no direct reports.

Build production-grade AI features and LLM pipelines (RAG, prompt engineering, context management) for financial-data workflows. Implement agentic workflows with Agno, optimize for accuracy/latency/cost, evaluate output quality, and integrate AI capabilities with backend APIs while maintaining code quality, observability, and testability.

Develop and maintain human-centered AI software across the SDLC. Collaborate with PIs and cross-functional teams, track requirements in GitLab, produce API/docs, and implement deployable solutions using Python, databases, containerization, and cloud technologies in an Agile environment.

Apply advanced AI/ML and generative foundation models to multi-modal preclinical, clinical, and real-world datasets to identify drug targets and biomarkers. Develop, validate, and deploy ML solutions, collaborate cross-functionally to ensure ML-ready data, and contribute to scientific publications and presentations.

As AI Research Scientist I, you will propose AI solutions, apply ML models in drug design, publish papers, and collaborate in a fast-paced environment.

The Technical Program Manager will lead AI data generation projects, ensuring consistent quality and efficient execution while communicating across teams.

Lead development of external AI platforms for biological design. Define benchmarks, build AI-driven workflows that integrate models, data, and experimental feedback, translate scientific questions into production APIs and user tools, collaborate with wet lab teams to validate outputs, and move prototypes to reliable production systems while shaping product direction.

The AI Solutions Architect specializes in pre-sales technical solutions for AI platforms, collaborating on architectural designs, conducting customer engagements, and ensuring seamless transitions to delivery teams.

The AI Services Consultant develops and positions AI consulting services, collaborates across teams, and manages client engagements to unlock AI potential and drive value through structured proposals and delivery.

The AI Services Consultant scopes and positions AI consulting engagements, collaborates with sales and delivery teams, and develops service proposals to drive AI initiatives and infrastructure investments.

The AI Solutions Executive drives AI sales by generating opportunity pipelines, implementing effective sales strategies, and collaborating with field teams to close various AI solutions.

The AI Solutions Executive generates and closes AI pipeline, collaborates with field sales, builds customer relationships, and delivers tailored presentations and proposals.

Lead end-to-end architecture for a major Generative AI platform: define reference architectures, integration contracts, NFRs, and reusable patterns (RAG, model serving, prompt/agent workflows). Partner with product, engineering, data science, cloud, security, and DevSecOps to ensure secure, scalable, compliant, and production-ready AI solutions. Conduct design reviews, proofs-of-concept, and drive platform governance and operational readiness.

Lead and manage global AI-readiness and AI security programs: scope and run multi-workstream initiatives, drive governance for enterprise AI systems, partner with cross-functional teams, manage vendors, measure and mitigate risks, and enable secure, compliant rollouts (including GxP alignment) with observability, training pilots, and developer enablement.

Lead cloud and AI security strategy, governance, and operations. Oversee CSPM/CWPP/CNAPP, SIEM/SOAR integrations, identity and data protection, IaC and DevSecOps practices, compliance, incident response, and mentor a team while partnering with engineering and stakeholders.

Design, build, deploy, and monitor production-grade AI and ML solutions (including GenAI/LLM applications) for Long-Term Care. Collaborate with cross-functional teams to operationalize models, implement MLOps/LLMOps pipelines, ensure governance/compliance, and improve observability, scalability, and cost efficiency. Mentor junior staff.

Lead assessment and secure adoption of AI/ML and GenAI systems for clients. Design security patterns and controls, perform assessments and pen tests, prototype AI-enabled security capabilities, ensure compliance (PII, privacy, regulatory), document protocols, and collaborate with cross-functional teams to productionize scalable AI-security solutions.

Lead discovery and design of end-to-end enterprise AI/ML architectures, define MLOps/LLMOps and data lifecycles, integrate solutions with enterprise systems and security, produce reference patterns and runbooks, mentor teams, and scale repeatable delivery through accelerators while partnering with clients and risk/security stakeholders.

Lead the development of AI applications and data products to enhance Immunology R&D. Manage a technical team and collaborate across departments.

Partner with attorneys to design, build, deploy, and maintain AI-enabled legal workflows (prompting, RAG, templates, evaluations). Provide training, change management, governance-aligned guardrails, monitor adoption and performance, and iterate on workflows with cross-functional teams.

Lead Kymera's enterprise AI strategy and roadmap; prototype, build, and deploy AI/LLM solutions; select and govern AI platforms; establish AI governance with InfoSec; manage vendors and external engagements; drive adoption through training; and advise functional leaders to operationalize AI across research, development, regulatory, and G&A.

The Principal Robotics Application Engineer will lead technical strategies and influence customer solutions in robotics, working across teams to match customer needs with ADI's technology offerings.

Serve as the primary finance business partner for AI/ML and Infrastructure teams, building driver-based models, rolling forecasts, KPI dashboards, and cost models for compute, GPU, LLM API, data storage, and pipelines. Support planning, fundraising diligence, cash runway scenarios, headcount and capacity planning, and FP&A tooling integrations while partnering with Accounting, IT, and Procurement to improve cost allocation and reporting.