Top AI Specialist Jobs in Boston, MA

Drive go-to-market strategy and adoption for Kensho AI products by bridging technical AI capabilities and commercial teams. Lead customer demos, technical deep-dives, co-development partnerships, market analysis, and sales enablement while feeding product and strategy teams with market insights to expand revenue and partnerships.

Design, build, test, deploy, monitor, and maintain production LLM-based agentic solutions for Commercial Customer Success. Integrate agents with CRMs and Samsara systems, define evaluation frameworks and success metrics, implement automated tests and monitoring, iterate on models and prompts, and demonstrate impact on customer outcomes and retention.

The AI Enablement Specialist will drive AI adoption, provide support and training to users, identify efficiency opportunities, and partner with leadership to implement high-impact AI solutions.

Lead Volition's internal AI strategy: design, build, deploy, and maintain production AI tools and infrastructure across deal sourcing, portfolio monitoring, research, and operations while ensuring compliance, data governance, and stakeholder enablement.

Entry-level AI engineer supporting design, development, testing, and deployment of LLM-based and agent-driven solutions. Work includes data prep, API integrations, prompt development, observability, and collaborating with cloud, data, and security teams while learning platform standards and responsible AI practices.

As an AI Product Specialist at Kensho, you will drive market expansion, manage customer engagement, and leverage AI product strategies while collaborating across teams to ensure effective go-to-market execution for AI solutions.

Design, build, and operate a secure, scalable enterprise Generative AI platform on AWS (including AWS Bedrock). Own platform lifecycle: architecture, deployment, operations, monitoring, incident management, reliability, and governance. Implement LLM inference, RAG, Agents, guardrails, observability, security controls, access management, compliance, and cost optimization. Support production-grade GenAI applications in regulated/financial environments.

The role involves designing and delivering AI training programs, creating learning materials, and facilitating workshops to enhance user understanding of AI tools within enterprises.

Lead sales and deployment of custom AI/ML solutions, driving pipeline and revenue for allocated accounts. Collaborate with Field Sales, Product, Sales Engineering and AI teams to discover requirements, architect agentic AI solutions, write SOWs, negotiate commercial terms, and manage complex sales cycles to ensure customer adoption and measurable business outcomes.

Design, develop, and deploy Agentforce AI agents and custom actions on the Salesforce platform. Build Apex classes, LWCs, flows, and API integrations with Data Cloud and legacy federal systems. Enforce AI safety, federal security/compliance, support testing/UAT, and enable secure DevSecOps/CI/CD deployments in cleared environments.

Design, develop, and deploy Agentforce AI agents and custom actions on Salesforce. Build Apex, LWCs, flows, and secure API integrations with legacy federal systems and Data Cloud. Ensure AI safety, compliance, testing, and support CI/CD/DevSecOps practices in cleared federal environments.

Optimize and compress large language and vision models for on-device inference. Build distillation and hardware-specific compilation pipelines, benchmark performance across NPU/GPU architectures, and deploy models to edge environments.

Develop intent-recognition models from gaze, gesture, and voice data; implement socially aware navigation algorithms respecting personal space; and design visual and auditory feedback for robot user interfaces. Conduct user studies and rapid prototype AI-driven voice and visual interaction systems to test and refine HRI paradigms.

Design and run adversarial tests on language and multimodal models, build guardrails and real-time filters for autonomous tools, and develop constitutional AI principles and RLHF alignment pipelines to ensure safe AI deployment.

Design and implement high-fidelity spatial mapping and real-time object recognition pipelines. Integrate vision systems with robotic manipulation and navigation, and train and fine-tune Vision-Language-Action models to improve robotic automation.

Designs, builds, tests, and deploys AI-enabled automations and copilots for GTM and RevOps. Creates reusable agent templates, prompt libraries, and orchestration patterns; implements end-to-end API integrations; monitors performance; documents and hands off production solutions; and trains/coaches business teams on safe, responsible AI usage and prompting best practices.

Build and deploy AI-powered automations across sales, marketing, operations, and finance. Map processes, identify bottlenecks, design end-to-end solutions, integrate systems (CRMs, data platforms, cloud tools) via APIs and automation/no-code platforms, and own production reliability and business impact. Serve as internal expert on AI models and tooling while collaborating cross-functionally and driving measurable ROI.

The role involves cultivating technical relationships with Accenture, supporting solution development, customer deal support, and representing Databricks at events.

Lead design and implementation of AI and data governance frameworks, privacy guardrails, metadata standards, and compliance with GDPR/HIPAA/CCPA/NIST AI RMF. Monitor and audit models for bias, explainability, and transparency; partner with engineers, stewards, and leaders to embed ethical decision-making, set KPIs, run audits, and produce dashboards and reports to drive governance adoption.

Review machine-translated content into Finnish by comparing source and translation, making pass/fail quality judgments on accuracy, grammar, and naturalness. Follow guidelines and provide consistent assessments during a one-year, 1–5 hour/week freelance engagement.

Compare source texts with Hebrew machine translations to judge accuracy, grammar, and naturalness. Make simple pass/fail quality assessments following provided guidelines. Weekly commitment 1–5 hours for a year; no rewriting required.

Create, optimize, schedule, and publish blog and social content about AI applications. Test headlines, landing pages, and ads; review analytics, predict opens/clicks/conversions, write performance reports, and personalize curated content.

Design and maintain a skill and concept graph, build ML models to infer learner skills, and develop recommendation systems and LLM-driven features. Ship production-ready LLM systems, define explainability standards, partner with frontend and product teams, and monitor model performance and evaluation frameworks.

Serve as the primary clinical expert supporting Data Science and Development: validate and monitor AI models, define client requirements, drive product enhancements, and translate clinical feedback into business requirements and user stories.

The AI Adoption Specialist guides organizations in integrating AI technologies, developing strategies, conducting pilots, and overseeing deployment while monitoring performance.