AI Engineer

• AI Implementation - Design, build, and maintain all of our AI systems across the company. Everything from internal marketing, sales, finance, and operations systems to local AI systems in our engineering workflows, and the Chamber itself.
• AI Adoption - Educate, Train, Support, and Uplift everyone in the company with their AI adoption. Running office hours, making tutorials, providing resources, sourcing solutions, and more.
• AI Infrastructure - Architect and operate a scalable set of infrastructure that allows non-technical, and technical teams to use AI in a secure and productive manner.
• AI Systems & Agents - In conjunction with departments, design, build and maintain all AI systems and agents. This includes administering and managing our off the shelf AI systems like Claude, Viktor, Cursor, etc. It also includes our custom built Agents, Skills, Plugins, Tools, and more.
• AI Security - You are responsible for creating, maintaining, and enforcing all data, privacy, and security policies across our AI systems and Agents. Organization, Department, and Role based permissions and settings across all our products.
• Other Projects - As this is a technical role, you will also be asked to help build other internal systems like automations, micro apps, and more.

AI Solutions Lead

• Define product vision and prioritize initiatives across multiple applications
• Oversee requirements for gathering, feature design, and release planning
• Guide product owners and analysts to align deliverables with business outcomes
• Engage with stakeholders at all levels to champion product usability and value
• Coordinate with QA and development managers to ensure on-time delivery

Lead AI Engineer – Capital Project Delivery

• Define and evolve the standards, architecture patterns, and tooling choices that govern how engineers use AI across the codebase — including where to invest in codebase readiness (instrumentation, specification, evaluation) versus targeted rewrites.
• Own execution of the multi-milestone plan (readiness → validated → governed) applied to corgi and secondary repos, in partnership with squad leads — without being their manager.
• Decide what AI tooling, agent infrastructure, and evaluation pipelines the org needs, and build or oversee the build of the ones that don't exist yet.
• Set the policy and technical controls for where human-in-the-loop review is required versus where autonomous agent action (PR review, deployment) is safe — resolving the tension between adoption speed and security/quality risk.
• Write the guidance engineers actually use — AGENTS.md/CLAUDE.md conventions, review norms for AI-generated code, eval standards — and make sure it's adopted, not just published.

AI Architect

• Design, build, test, and deploy AI legal workflows and skills across firm-approved AI tools, supporting use cases such as contract review, due diligence, drafting, research, and summarization
• Partner directly with attorneys and knowledge management professionals to identify high-value use cases, map workflows, and translate practice needs into structured AI solutions
• Develop and maintain retrieval pipelines, document templates, and reusable workflow components with clear, attorney-ready documentation
• Build and execute evaluation frameworks to measure workflow quality, accuracy, and reliability; monitor performance and iterate based on feedback and outcomes
• Serve as a go-to resource for enablement and change management for developed workflows, partnering with the AI Adoption team to drive usage, deliver training sessions and workshops, 1:1 coaching, and develop practical playbooks and materials that support sustained adoption
• Develop and scale best-practice standards, use-case libraries, and playbooks that empower attorneys to responsibly and independently leverage AI tools while maintaining quality and risk controls
• Embed human-review checkpoints and audit mechanisms aligned with Firm governance, confidentiality, and professional responsibility requirements
• Collaborate closely with cross-functional stakeholders including the AI Product team, AI Adoption team, Knowledge & Innovation team, IT, Innovation Practice Group, and Professional Development to ensure aligned delivery and support
• Track adoption, usage, and impact metrics for deployed workflows and recommend refinements or expansion opportunities
• Manage ongoing maintenance of production workflows, including updates to prompts, retrieval sources, and guardrails in response to model and platform changes, user feedback, or evolving practice needs
• Represent the AI Products & Adoption team in internal meetings, committees, and practice group sessions

AI Legal Engineer

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
• Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
• Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.
• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

Senior Lead AI Engineer – SDKs, Gen AI Evaluation, MCP

• Collaborate with domain experts to understand business needs and translate them into clear and effective LLM prompts.
• Develop, test, and refine prompts for a variety of use cases, ensuring high accuracy and relevance in generated outputs.
• Work closely with software developers to integrate LLM solutions into existing or new applications.
• Contribute to the development of a scalable framework for prompt engineering, promoting reuse and knowledge sharing across different business units.
• Assist in gathering and analyzing user feedback to continually improve prompt effectiveness.
• Stay up-to-date with advancements in LLM technology and contribute to strategic decisions on tool and platform selection.
• Document prompt engineering processes, best practices, and use case outcomes to build a comprehensive knowledge base.

Senior Staff GenAI Engineer

• Ship and debug code on a live, real-time voice pipeline where latency and correctness are user-facing
• Design control systems around LLMs: guardrails, budgets, watchdogs, safe fallbacks
• Build and operate LLM evaluation and batch-analysis pipelines
• Own traditional ML workflows from data to scheduled production inference
• Trace production issues from a metric anomaly to root cause, including building the evidence when the cause is a vendor

Senior Software Engineer – Applied AI

• As a Senior AI Engineer on the AI Venture Studio team, you will be a hands-on senior individual contributor who leans into artificial intelligence (AI) to design and build impactful solutions to transform patients’ lives.
• This role is accountable for the AI-first engineering of cloud-native applications, agentic AI products, and the knowledge and context infrastructure that powers them.
• You will have access to the latest AI-centric tools and technologies to support activities such as the design of APIs and MCPs, cloud services orchestration, agent runtime deployment, workflow pipeline implementation, and reusable platform pattern development that enables AI Accelerator projects to move fast without giving up reliability, observability, security, or enterprise architectural alignment.
• This role lives inside the AI Accelerator delivery model: six fully agile two-week sprints across a twelve-week cycle to build, test, validate, and prepare minimum viable products (MVPs) for broader organizational adoption and scaling.
• AI Accelerator projects focus on the most challenging and highest-upside pharma-specific problems across R&D, Commercialization, Manufacturing, and Enabling Functions where critical context is buried in unstructured knowledge files, multimodal documents and reports, operational records, and scientific evidence packages.
• Ship in cycles by demonstrating engineering progress and lessons learned every two weeks.
• Focus on AI-first solutioning that prioritizes BMS technology investments (AWS, Claude, LangSmith, etc.) with the best chance of meeting use case and project success metrics.
• Collaborate effectively with other engineers (AI, data, UI/UX, machine learning) and broader agile AI accelerator product teams.
• Demonstrate a curious and inquisitive mindset with broad technical adaptability while staying hands-on with frontier AI technologies, AI coding agents, and the latest agentic engineering capabilities.

Senior AI Engineer

• Own stakeholder relationships across Medbridge’s executive team, working with them to find the problems and AI enabled solutions that can expedite, or remove, the current blockers in the business.
• Design, build, and ship AI-powered features across our internal teams, from the user interface to the backend services and AI workflows behind it.
• Build full-stack applications using AI-native engineering workflows and tools such as Claude, Cursor, Codex, and OpenAI and Anthropic APIs.
• Develop APIs, backend services, and automation pipelines that support intelligent product capabilities and production-ready deployments.
• Apply software engineering, DevOps, and MLOps best practices to the testing, deployment, monitoring, evaluation, and optimization of AI solutions.
• Partner closely with our Product and Engineering teams to turn ambiguous goals into scalable internal products.
• Use AI tooling throughout your workflow (coding, code review, testing, and planning) and help push the team’s adoption forward.
• Research emerging AI technologies, LLM implementation patterns, and modern product engineering frameworks, and bring what works back to the team.
• Instrument what you ship and use usage data and evidence to decide what to build, fix, or kill next.

Product Engineer – AI

• Collaborate with domain experts to understand business needs and translate them into clear and effective LLM prompts
• Develop, test, and refine prompts for a variety of use cases, ensuring high accuracy and relevance in generated outputs
• Work closely with software developers to integrate LLM solutions into existing or new applications
• Contribute to the development of a scalable framework for prompt engineering, promoting reuse and knowledge sharing across different business units
• Assist in gathering and analyzing user feedback to continually improve prompt effectiveness
• Stay up-to-date with advancements in LLM technology and contribute to strategic decisions on tool and platform selection
• Document prompt engineering processes, best practices, and use case outcomes to build a comprehensive knowledge base

Senior Principal AI Engineer

• Collaborate with domain experts to understand business needs and translate them into clear and effective LLM prompts
• Develop, test, and refine prompts for a variety of use cases, ensuring high accuracy and relevance in generated outputs
• Work closely with software developers to integrate LLM solutions into existing or new applications
• Contribute to the development of a scalable framework for prompt engineering, promoting reuse and knowledge sharing across different business units
• Assist in gathering and analyzing user feedback to continually improve prompt effectiveness
• Stay up-to-date with advancements in LLM technology and contribute to strategic decisions on tool and platform selection
• Document prompt engineering processes, best practices, and use case outcomes to build a comprehensive knowledge base.

• Designing and implementing seamless integration solutions and robust platform architectures to optimize technology infrastructure
• Analyzing business requirements and developing technical designs to enable successful delivery of innovative technology solutions
• Leading strategic technology planning and promoting technological advances to create environments where people and technology thrive together
• Overseeing multiple projects and maintaining executive-level client relations to drive business growth and shape client engagements
• Mentoring the next generation of leaders and cultivating potential within teams to uphold PwC's reputation for quality and integrity
• Conducting research and feasibility studies to identify gaps in the market and convert opportunities into success for the firm
• Developing new ideas, solutions, and structures to drive thought leadership and enhance business performance
• Collaborating across the PwC Network to leverage collective strength and maximize client satisfaction

AI Architect Director

• Design, develop, and deploy machine learning models and AI-powered applications
• Collaborate with cross-functional teams to identify and implement AI/ML solutions for client needs
• Build and maintain data pipelines, model training workflows, and inference systems
• Evaluate and integrate large language models (LLMs), generative AI tools, and emerging AI frameworks
• Monitor model performance, conduct testing, and iterate on improvements
• Document technical architectures, methodologies, and best practices
• Stay current with AI/ML research and translate advancements into practical applications

• Architect and build AI agentic systems from the ground up that reshape how commerce operates
• Own end to end full stack development from front to back, infrastructure to interface, with AI first thinking throughout
• Design and build intuitive, AI native user experiences, not just backend logic
• Prototype quickly and iterate in direct collaboration with co-founders and early customers
• Partner with forward leaning industry leaders who are moving fast and expect the same
• Help define the technical foundation, stack decisions, and engineering culture for a scaling team
• Operate daily in the trenches with leadership, with high visibility, high ownership, and high impact

Agentic AI Engineer

• Define and evolve enterprise AI architecture, standards, reference models and implementation guidelines to support consistent solution delivery across business functions
• Align AI initiatives to enterprise strategies, roadmaps, and business priorities
• Identify and prioritize AI opportunities that drive student success and operational efficiency
• Design scalable AI platforms and solutions across data, application, and technology domains
• Provide guidance on how AI, ML, and automation will improve current and future-state architectures
• Lead design and implementation of AI-powered solutions (e.g., LLMs, agents, automation, and analytics)
• Integrate AI capabilities with enterprise applications and data platforms
• Guide evaluation and selection of AI/ML models, frameworks, and vendors
• Establish reusable patterns, APIs, and integration approaches
• Establish governance practices covering model oversight, responsible AI usage, security controls, compliance expectations, and lifecycle management
• Establish AI governance, including responsible AI, security, privacy, and compliance (FERPA, HIPAA, GDPR)
• Establish lifecycle management practices (MLOps/LLMOps, model monitoring, drift detection, retraining)
• Implement performance, bias, and risk monitoring frameworks
• Ensure secure AI architecture (e.g., data protection, isolation, adversarial defense)
• Partner with business, product, data, and engineering teams to provide AI solutions
• Provide architectural guidance to architects and delivery teams
• Facilitate workshops, POCs, demos and AI adoption projects identifying viable opportunities where AI can be a positive differentiator
• Mentor teams on AI best practices, patterns, and frameworks

Enterprise AI Architect

Staff Engineer – AI Engineering

• Developing innovative software solutions to drive digital transformation and enhance business performance
• Designing, coding, and testing applications to deliver exceptional user experiences
• Utilizing Acceptance Test Driven Development (ATDD) and Continuous Integration/Continuous Delivery (CI/CD) methodologies to improve software quality
• Managing application lifecycle and software project planning to meet client needs
• Implementing API management and microservices for seamless enterprise application integration
• Conducting code reviews and debugging to maintain coding standards and software reliability
• Collaborating with clients to analyze business requirements and deliver tailored solutions
• Applying analytical thinking and problem-solving skills to address complex software engineering challenges
• Leveraging programming languages such as Kotlin, Rust, and SwiftUI for application development
• Engaging in business process improvement and requirements management to optimize software solutions

Senior AIT AI Developer

• Designing and implementing seamless integration solutions and robust platform architectures to optimize technology infrastructure
• Analyzing client requirements and developing technical designs to deliver innovative technology solutions
• Leading teams in the successful planning, budgeting, execution, and completion of projects
• Coaching and mentoring team members to leverage their unique strengths and manage performance
• Addressing conflicts and engaging in difficult conversations with clients and stakeholders

AI Architect Manager

• Actively works with product and engineering to design and build breakthrough AI-powered and agentic capabilities for our clients using LLMs, agentic workflows, and modern DL/ML techniques
• Design, prototype, develop, and test LLM-powered applications, agentic workflows, and predictive models using Python and modern AI frameworks to power critical product capabilities
• Work with both structured and unstructured clinical trial data, including patient reports, trial documentation, and free text notes
• Ideate, design, prototype, and develop solutions such as multi-agent workflows, RAG-based applications, document intelligence and summarization pipelines, and intelligent process automation
• Design, prototype, and develop solutions using modern AI frameworks and libraries such as LangChain, LangGraph, LlamaIndex, PyTorch, Hugging Face Transformers, and scikit-learn
• Champion AI-driven development practices across the team — using AI coding assistants and agentic dev tools to accelerate prototyping, code generation, testing, and review
• Build and maintain LLM, agentic, and ML pipelines, including prompt engineering, orchestration logic, and evaluation harnesses
• Apply relevant evaluation frameworks, guardrails, and statistical measures for performance, quality, and error analysis of AI systems
• Drive the entire workflow of multiple AI engineering projects
• Enhance the experience and efficiency of our elluminate software platform users
• Work with our Engineering team to integrate AI capabilities into our elluminate software platform
• Work with the MLOps/AIOps team to deploy LLM, agentic, and ML systems in production and to track performance, cost, and quality
• Consult with and assist our software development and biometrics teams to consume the results of these AI systems
• Ensure data quality throughout all stages of acquisition and processing
• Serve as Subject Matter Expert in Generative AI, agentic systems, and applied Machine Learning
• Keep up to date with the latest research and tooling in LLMs, agentic AI, and ML
• Educate other team members in modern AI techniques and best practices
• Publish and present work and contribute to company’s intellectual property

• Build AI-powered workflows, automations, prompts, templates, and tools that reduce manual work and improve CS execution
• Prototype and scale workflows such as automated EBR/QBR decks, renewal briefs, customer summaries, risk narratives, meeting prep, and next-best-action recommendations
• Help operationalize the CS operating model, including lifecycle stages, health and risk models, renewal readiness, executive engagement, customer prioritization, and value tracking
• Partner with CS, RevOps, Data, Support, Product, and other teams to connect the right data into the right workflows
• Work across systems such as Salesforce, Gainsight, Clari, Gong, Zendesk, Snowflake, Slack, Zoom, Google Workspace, Claude, ChatGPT, and other AI/automation tools
• Establish prompt structures, QA checks, feedback loops, and documentation to ensure AI outputs are useful, accurate, and scalable
• Gather feedback from CSMs and leaders, iterate quickly, and continuously improve workflows based on real team usage
• Help CSMs spend less time on manual reporting, prep, and coordination, and more time on high-value customer engagement

AI Engineer jobs in Massachusetts

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AI Solutions Lead

Lead AI Engineer – Capital Project Delivery

AI Architect

AI Legal Engineer

Senior Lead AI Engineer – SDKs, Gen AI Evaluation, MCP

Senior Staff GenAI Engineer

Senior Software Engineer – Applied AI

Senior AI Engineer

Product Engineer – AI

Senior Principal AI Engineer

Senior Principal AI Engineer

AI Architect Director

AI Engineer

Agentic AI Engineer

Enterprise AI Architect

Staff Engineer – AI Engineering

Senior AIT AI Developer

AI Architect Manager

AI Engineer

Customer Success Lead – AI Operations