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Onsite AI Engineer - Construction Industry Focus

New Haven, CT - Onsite 5 days per week

• Initial Assignment: Fully onsite 5 days per week at a construction site in Ft. Myers (FL) or New Haven (CT) for 1 year
• Post-Assignment: Relocation to one of the corporate offices for hybrid employment: Boston, MA (preferred), New York City (NY), New Haven (CT), Herndon (VA), West Palm Beach (FL), or Estero (FL)

Role Summary

As the on-site catalyst who turns AI ideas into working reality. Partnering with each project’s AI Champion (Project Manager or Superintendent), you’ll uncover pain points, redesign workflows, and deploy AI agents that cut down reporting, accelerate RFIs, simplify lookahead planning, progress updates, materials tracking, and more. When needed, you will develop user stories and coordinate development with the central AI Studio. You’ll help advance the vision of the “Construction Site of the Future,” showing how agentic AI will transform project operations.

Responsibilities

• Workflow discovery and redesign: Lead Lean/Six Sigma workshops; map value streams; log high-impact AI agent opportunities that improve field efficiency.
• AI agent development: Build and deploy multiple production-ready AI agents using Copilot Studio, Power Apps/Automate, ChatGPT Enterprise, or code-first frameworks. Integrate agents into Teams/SharePoint on the front end and Databricks Lakehouse or other enterprise data sources on the back end.
• RAG pipelines and LLMOps: Design and operate retrieval-augmented generation (RAG) pipelines with Databricks Delta Tables, Unity Catalog, and Vector Search (or Spark/Hadoop equivalents). Monitor cost, latency, adoption, and model drift.
• Cross-cloud orchestration: Blend OpenAI, Azure OpenAI, and AWS Bedrock services through secure custom connectors to maximize flexibility and adoption.
• Data integration: Partner with Data Engineering to deliver ETL/ELT pipelines, API integrations, and event-driven connectors that feed RAG pipelines and AI agents.
• Change management and adoption: Train field teams, gather feedback, iterate quickly, and embed agents into SOPs. Track usage and ROI with adoption metrics and behavior-change KPIs.
• Stakeholder communication: Translate technical results into business value for leadership and clients. Contribute use cases and playbooks for the “Construction Site of the Future.”
• Compliance and hand-offs: Ensure all AI solutions meet the company’s data governance and security standards. Draft clear user stories and specs for escalation to central AI/Data Engineering teams when necessary.

Qualifications

• 4+ years in AI engineering, data science, or ML-focused software engineering.
• Proven experience building multiple AI agents in production environments.
• 2+ years of hands-on experience with LLMs, RAG pipelines, and LLMOps practices.
• Must have strong traditional software engineering background in Python

Bonus Points

• Experience in construction, manufacturing, or other process-heavy industries.
• Advanced degree in a technical field.

• Design and implement automated workflows and AI agents for supply chain tasks.
• Conduct iterative testing and user acceptance testing with supply chain teams.
• Configure workflow logic, decision trees, automation sequences, and integration points for AI functionality.
• Develop hybrid solutions integrating analytics dashboards with AI workflows for process automation.
• Document workflow configurations, prompt patterns, and decisions in detail for non-technical user maintenance.

• Expertise in prompt engineering and AI platform management
• Proficiency in no-code/low-code workflow automation tools
• Deep understanding of AI agent training, context windows, model limitations, and hallucination mitigation.
• Basic technical understanding (APIs, data structures, integrations)

LHH is seeking a Senior Databricks AI/ML Engineer to join our client's team in a fully remote role based in Seattle, WA. Candidates must live in one of the following states, and be prepared to pass a background check/identity verification process: WA, OR, ID, OH, SC, NC, TX, or FL

LHH has a dynamic and challenging opportunity for a Senior Databricks AI/ML Engineer to join our client's engineering team. This role focuses on building and deploying scalable AI/ML solutions across key areas of the insurance functions, including underwriting, claims, pricing, customer engagement, and fraud detection, with a strong emphasis on Databricks architecture and ecosystem integration. The engineer will collaborate closely with data scientists, actuaries, product owners, and engineers to operationalize models, transforming them into robust, production-grade systems seamlessly integrated into business workflows and enterprise platforms.

Salary & Benefits:

• $150k to $185k annually (depending on location & experience)
• Medical, dental, and vision insurance
• 401(k) plan with employer match
• Vacation time accrues at a rate of 10 days annually, with increases based on a tenure schedule, up to a maximum of 25 days per year.
• PTO included Four (4) personal days are granted immediately upon hire.
• Paid holidays are provided for the eight (8) holidays observed in this role throughout the calendar year.
• Up to ten (10) days of sick leave are granted immediately upon hire (pro-rated based on hire date and full-time/part-time status).
• Additional paid time off is available for bereavement, jury duty, and employee volunteer activities in the community.
• Life and disability insurance

Minimum Qualifications:

• Bachelor's degree in Computer Science, AI/ML, Data Science/Engineering, or related field (or equivalent experience).
• 6+ years experience in ETL pipelines, SQL Server, and production data workflows.
• 3+ years enterprise experience with Azure & Databricks AI/ML, including data analysis and visual analytics.
• 3+ years applying ML algorithms and transforming data science prototypes into production.
• 5+ years experience with CI/CD workflows for ML models and related code.
• Strong SQL, real-time and batch data pipeline development, and unsupervised learning techniques.
• Familiarity with agile methodologies (e.g., Scrum).

Responsibilities:

• Conduct customer workshops to gather requirements and design analytics architectures using Azure and Databricks AI/ML.
• Serve as Databricks Architect, managing workspace design, deployment, and governance across environments.
• Define and implement Databricks Lakehouse architecture and governance best practices.
• Integrate Databricks with Azure services and lead implementation of Databricks SQL, Delta Live Tables, and MLflow.
• Develop and maintain automated MLOps workflows for model deployment, monitoring, and lifecycle management.
• Set up and configure Azure and Databricks infrastructure for AI/ML workloads.
• Review ML model code and analytics scripts for quality and performance.
• Design and build data pipelines and cloud services for monitoring, analysis, and reporting.
• Develop robust ETL workflows using Databricks, Spark, and SQL Server for structured and unstructured data.
• Provide production support and performance tuning for data engineering workflows.
• Optimize complex SQL queries and stored procedures for data processing and business logic.
• Collaborate with cross-functional teams to ensure data quality and support business decision-making.
• Scale and deploy machine learning models to handle large-scale data.
• Feed raw data into models and build deployment pipelines for new models.
• Implement logging, observability, and performance monitoring for AI/ML systems.
• Conduct architecture reviews and performance testing.
• Perform other duties as assigned.

Preferred Qualifications:

• Master's degree in a related field.
• Experience in the insurance industry (Auto, Home, Umbrella) and related AI/ML applications.
• Proficiency with tools/platforms: Azure ML, Databricks, Microsoft Fabric, Synapse, Power BI, Snowflake, and APIs like Azure OpenAI and Cognitive Services.
• Knowledge of streaming frameworks: Apache Kafka, Azure Event Hubs, Delta Live Tables.
• Strong math, problem-solving, and rapid learning skills.
• Excellent communication, organization, and independent work capabilities.
• Service-oriented mindset with ability to handle ambiguity and build strong relationships.

Equal Opportunity Employer/Veterans/Disabled

To read our Candidate Privacy Information Statement, which explains how we will use your information, please navigate to Company will consider qualified applicants with arrest and conviction records in accordance with federal, state, and local laws and/or security clearance requirements, including, as applicable:

• The California Fair Chance Act

• Los Angeles City Fair Chance Ordinance

• Los Angeles County Fair Chance Ordinance for Employers

• San Francisco Fair Chance Ordinance

Key Responsibilities:

• Design and deploy observability frameworks leveraging tools such as Grafana, Dynatrace, Prometheus, ELK, Splunk, etc. Define best practices for monitoring, alerting, and visualization across hybrid and multi-cloud environments.
• Develop strategies for monitoring KPIs tied to business outcomes (e.g., sales performance, supply chain efficiency, customer experience).
• Collaborate with business and IT teams to identify key metrics and integrate them into dashboards and alerting systems.
• Implement AIOps solutions using industry-leading platforms like OpenAI, AWS Bedrock, Google Gemini, Anthropic, and similar technologies.
• Develop predictive analytics and anomaly detection models to proactively identify and resolve operational issues.
• Integrate observability tools with ITSM platforms and automation workflows. Enable automated root cause analysis and remediation using AI/ML models.
• Provide observability strategies for infrastructure (servers, storage, cloud), applications (microservices, APIs), and networks (LAN/WAN, SD-WAN). Collaborate with DevOps, SRE, and IT operations teams to ensure end-to-end visibility and reliability.
• Establish observability standards, KPIs, and SLAs for performance and availability. Ensure compliance with security and regulatory requirements in monitoring solutions.
• Develop scalable architecture using LLMs, agentic frameworks, and multi-modal AI technologies.
• Build AI-powered analytics platforms for IT operations analysis, anomaly detection, and predictive insights.
• Architect and deploy intelligent chatbots for IT support and self-service capabilities.
• Integrate AI solutions with existing IT operations tools and workflows.
• Implement automated remediation and root cause analysis using AI/ML models.

Qualifications:

• 10-13 years of relevant experience
• Hands-on experience with Grafana, Dynatrace, and other monitoring platforms.
• Practical experience implementing AI-based solutions for anomaly detection, predictive maintenance, and automated remediation. Familiarity with OpenAI, Bedrock, Gemini, Anthropic, or similar AI platforms.
• Strong understanding of infrastructure, application architectures, and networking. Experience with cloud platforms (AWS, Azure, GCP) and container orchestration (Kubernetes).
• Proficiency in Python, Bash, or similar scripting languages for automation and integration.
• Strong experience with LLMs (OpenAI, Anthropic, Gemini, Bedrock) and agentic AI solutions.
• Hands-on experience in designing AI architectures for enterprise IT environments.
• Proficiency in Python or similar languages for AI model integration and automation.

Looking for a 10+ years of experience in full stack software development, including front-end, back-end, and database technologies in Bothell, WA and its an onsite role.

• Bachelor’s degree in computer science, software engineering, or a related field preferred
• Proficiency in modern programming languages and frameworks such as Python, JavaScript, Java, Next JS, Node.js, React js
• Strong working experience with GenAI, LLM Models, MCP, Vector DB, RAG, Vertex AI, Agentic AI frameworks like NGA, ADK or LangChain/LangGraph, creating AI agents.
• Strong experience with Cloud platforms like GCP, Azure or AWS and cloud technologies like OpenStack, Terraform, Ansible or Chef
• Experience working with LLM observability, analytics, evaluations, testing and annotation using tools like LangSmith, LangFuse, Streamlit, Arize or similar tools.
• Strong experience working with AI/ML development
• Strong experience working with Databases like Cassandra, MongoDB or similar.
• Strong understanding and working experience of microservices architecture, RESTful APIs, Caching and related technologies
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes
• Proficiency in version control systems like Git, and experience with CI/CD tools such as Jenkins, GitHub, Maven, Nexus, JFrog or Sonar
• Strong experience in Unit and Function testing using Junit, Mockito/JMock, Selenium, Robot, Cucumber, SoapUI or Postman
• Strong problem-solving, analytical, and debugging skills.
• Excellent written and verbal communication skills, with the ability to effectively communicate complex technical concepts to both technical and non-technical audiences.
• Demonstrated experience in mentoring and providing technical leadership to other engineers.

• Nice to have skills:
• Google CCAI platform (DialogFlow), Vertex AI, Graph QL, BigQuery, Conversation Graph, LLM as Judge

Position: Principal AI Engineer

Location: San Francisco CA Hybrid

Contract

Job Summary:

• We are seeking a senior level AI/ML engineering contractor to temporarily step into a technical leadership and team lead role supporting personalization models and the company’s AI platform.
• The ideal candidate can balance technical expertise, strategic decision making, and day to day team guidance to ensure continuity during the leave period.

Required Skills & Experience:

• Senior level 12 years of experience building and operating machine learning systems in production.
• Strong understanding of ranking models, recommendation systems, model evaluation, and experiment design.
• Hands on expertise with modern AI/ML engineering tools (e.g., Python, Spark or similar, cloud-based ML pipelines, cloud model serving frameworks, and API design).
• Ability to lead engineering discussions, guide team members, and provide clear direction.
• Strong organizational skills: able to manage complex projects and maintain structure during a temporary leadership period.
• Excellent communication skills, with the ability to translate technical details into clear action for partners and stakeholders.

Note: Interview will be In person

Role and Overview of the role:

This is Senior QA engineer role with eight to ten years experience who also has some experience in leading so that it will be helpful for them to coach candidate, lead, take him to the next level. The position requires candidate to have Java as a mandatory requirement. Karate DSL is not a must but it is good to have if they have knowledge of it. API testing is a must. Looking for somebody who has AWS experience who has keenly worked with these AWS services to know how to test backend. They should have some lead experience so that they have worked on creating test plans, test criterias, test strategies. So they can work independently. Candidates work with the team, deliver the projects. Apart from that, this is going to be a hybrid role.

Top Skills:

l Java - Java Coding

l API Testing

l AWS

l 1 to 2 years of lead experience

l Karate is a plus not a mandatory

Education and Experience

l Years of experience: 10+ yrs experience

l Degree requirement: Bachelor's degree

Typical task breakdown:

Develop test automation code for Continuous Integration (CI), Continuous Delivery (CD), of systems, infrastructure, and test framework.

• Plan, design, develop, and maintain API test automation framework that facilitates automation scripting, execution, and analysis of results

• Provide technical leadership and mentoring for test engineers on multiple applications/projects onshore and offshore; train and mentor project team members to create, execute, analyze, and maintain automated regression suites

• Coordinate with product owner to resolve open issues/enhancements/upgrades and understand the use of a specific functionality as needed

• Develop automated functional scripts using tools such as Java, Karate, JMeter.

• Perform exploratory and manual testing of the product suite as appropriate

• Provide expertise in testing methodologies, best practices, and standards

Technical Skills:

(Required)

- Strong design and development skills in two or more of the following technologies and tools: Java, Cucumber, JBehave or other BDD testing frameworks

• At least 8 years of test automation framework design

• Strong experience in testing Webservices (REST APIs)

• Proven experience developing test scripts, test cases, and test data

• The ability to write queries in SQL or other relational databases

• 3+ years of experience in developing scenario based performance testing using JMeter

• Experience testing full stack and integration testing with 3rd parties

• End-to-end system integration testing experience for software platforms

(Desired)

• Hands on experience with Python

• Development experience in AWS Cloud technology

• Experience in TDD, continuous integration, code review practice is strongly desired

• Experience with Apigee or other API gateways is a plus

• Experience with DevOps concepts and tools (e.g., CI/CD, Jenkins, Git)

• At least 2 years working on an Agile team with a solid understanding of Agile/Lean practices

• Understanding of a micro service Architecture

• Experience load and performance testing

• Strong documentation skills

Soft Skills:

(Required)

• Ability to adapt quickly to a complex environment

• Pro-active, flexible and creative

• Very strong communication skills and the ability to collaborate with developers and business users.

Title: Lead Software Engineer - AI Application Platform

Mode of interview 1 round in person

Location: Must be in Charlotte, NC to work Hybrid Model

Main Skill set: Python, AI and Angular

Description:

Lead Software Engineer - AI Application Platform

The Opportunity

We are seeking a Lead Software Engineer to guide the architectural development and execution of the client, a sophisticated AI-powered application generation platform. This role suits a proven technical leader with deep, hands-on expertise across the full software stack who finds enabling a team to build better software deeply satisfying.

You will shape critical systems, mentor senior and junior developers through complex technical decisions, conduct rigorous code reviews across multiple technology domains, and directly influence the platform's trajectory through strategic engineering leadership.

This is for someone who:

• Engages thoughtfully when a junior developer asks targeted architectural questions—because you see an opportunity to shape how someone thinks about systems
• Takes time to explain subtle type-safety issues in code review, understanding that feedback is a teaching moment
• Can present architecture clearly to executives and confidently explain both what we're building and why it matters
• Finds more energy in the code your team ships than in the code you write individually
• Has proven depth across the full stack and a track record of developing engineers into stronger contributors

This is not a single-language codebase. The role requires the ability to make informed decisions on TypeScript design patterns, Python FastAPI architecture, AWS security posture, and Terraform state management in context with one another.

The Platform Challenge

The client is fundamentally a Platform-as-a-Service (PaaS) for dynamic application generation. This differs from building a traditional SaaS product. Rather than building one application, you're building infrastructure that enables users to build their own applications.

What this means architecturally:

• Dynamic Content Generation at Scale: Unlike traditional development where code is fixed, AppGen generates JSON form schemas, validation rules, and UI layouts on demand. The FormBuilder component doesn't know what fields will exist until runtime. The layout engine renders user-designed screens from configuration, not hardcoded templates.
• Multi-Tenant Isolation & Data Segregation: Each user gets their own generated app, potentially deployed to their own AWS environment. The architecture must account for data isolation, namespace management, and cross-tenant security considerations.
• User-Defined Data Structures: Traditional applications are built with predetermined database schemas. AppGen works differently—form structures, field types, and validation rules emerge from user conversations with Claude. This brings engineering challenges: How do you safely execute validation logic that users define? When users modify existing forms that have thousands of submissions, how do you maintain backward compatibility? How do you version schemas?
• Content Rendering, Not Code Generation: Unlike traditional no-code platforms where users drag-and-drop to build, AppGen uses AI instead. Users chat with Claude, Claude generates a form schema, and your platform renders that schema reliably across diverse field types, validation patterns, and workflows. The system renders configurations for immediate use, rather than generating code for later deployment.

Experience that directly transfers:

• You've contributed to or led development of low-code/no-code platforms (visual builders, workflow engines, configuration-driven systems)
• You've worked on SaaS platforms with multi-tenant architecture and understand isolation strategies, rate limiting, and per-customer customization
• You've built dynamic rendering systems that handle unknown/arbitrary schemas at runtime
• You've addressed the unique challenges of treating data configurations as user-created content (form builders, report designers, automation workflows)
• You understand the difference between platform infrastructure and applications built on that infrastructure—and the architectural implications of each

Core Responsibilities

1. Technical Architecture & Systems Thinking (40%)

• Shape architectural decisions across the full stack: How should the component layer handle dynamically generated forms? What's the right approach to validate complex cross-field dependencies in the FormBuilder? What separation of concerns makes sense between the Generator Lambda and the Parent Backend?
• Guide architecture discussions: Help senior developers think through design trade-offs. Should we use NgRx or Angular signals for this feature? When does a new Lambda function become worthwhile given cold-start costs?
• Identify and address system-wide bottlenecks: Work across layers to improve performance. Explore Lambda cold-start optimization, RDS query efficiency, and DynamoDB access patterns.
• Establish patterns and guide consistency: Define coding conventions that work across Python, TypeScript, and Terraform. Help new team members understand the reasoning behind architectural choices.
• What this looks like in practice: You're able to justify architectural decisions with technical reasoning. When someone questions an approach, you can explain the trade-offs you considered. You can write code in multiple languages to validate an approach if needed.

2. Code Review & Technical Guidance (30%)

• Full-stack PR reviews: Review Python FastAPI endpoints and Angular components with equal depth, understanding how they interact.
• Deep technical review: Catch issues thoughtful code review can surface:
• RxJS Observable lifecycle and potential memory patterns in Angular
• Query efficiency and data loading patterns in SQLAlchemy
• Terraform module organization and state management implications
• Type safety and TypeScript coverage gaps
• AWS security and IAM configurations
• Educational feedback: Your code reviews help the team learn. When you identify an issue, reviewees understand not just what changed, but how to think about similar problems in the future.
• Define quality expectations: Work with the team to establish what \"production-ready\" means for this platform and support consistent application of those standards.
• What this requires: Experience reviewing code across teams and multiple languages. You know how to write feedback that resonates—clear, constructive, and focused on helping people improve.

3. Mentorship & Team Development (20%)

• Expand specialist capabilities: Help backend specialists learn to contribute to the forms-engine. Support frontend experts in understanding FastAPI patterns.
• Accelerate junior developers: Pair on complex problems. Explain the reasoning behind patterns like DataState. Connect architectural choices to implementation details and performance implications.
• Identify and address gaps: Recognize when someone is struggling with a technology and provide targeted support—training, pair programming, or guidance through architectural decisions.
• Create growth opportunities: Stretch the team into new areas. A backend engineer working on their first Terraform contribution. A frontend specialist implementing an AWS Lambda authorizer.
• What this requires: Genuine investment in people's growth. You've walked developers through major transitions (generalist to specialist, specialist to full-stack, or into new technology areas). You understand that team strength grows when individuals expand their capabilities.

4. Stakeholder Communication & Technical Leadership (10%)

• Explain to diverse audiences: Translate architectural choices and trade-offs for product managers, executives, and business stakeholders. Connect \"optimizing DynamoDB queries\" to \"improving form submission latency by 30%.\"
• Shape technical direction: Contribute the engineering perspective on feasibility, risk, and what unlocks future capabilities.
• Support release confidence: You understand the code changes, comprehend the risks, and know what to monitor. You can stand behind releases.

Required Qualifications

Technical Skills

Frontend (Production Experience)

• 5+ years of Angular (including handling version migrations, optimizing change detection, and guiding teams through reactive patterns)
• Strong TypeScript skills with generics, discriminated unions, and strict mode
• RxJS depth: You understand hot vs. cold observables, unsubscription patterns, and can identify potential memory issues in reviews
• NgRx state management: You've designed stores at scale, optimized selectors, and evaluated architectural implications
• CSS Grid & Responsive Design: You can assess component hierarchy and layout decisions
• Material Design: You've worked within it and know when and how to extend it

Backend (Production Experience)

• 5+ years of Python (async/await, type hints, data modeling)
• FastAPI production experience: session management, dependency injection, middleware
• SQL and ORMs (SQLAlchemy): You write efficient queries and review them critically
• AWS services: Understanding of Lambda behavior, IAM least-privilege patterns, VPC networking
• REST API design: Versioning, error handling, idempotency
• Testing frameworks: pytest, testing st

If interested in position, please fill out this form: description

Join the Future of Healthcare at MedWatchers

MedWatchers is a technology-forward leader delivering integrated care solutions that improve lives across Medicare, Medicaid, and Commercial markets. With a growing portfolio of 30+ clinical service lines and a flexible delivery model—ranging from full SaaS, hybrid solutions, to fully delegated services—we help payers close gaps, enhance outcomes, exceed quality benchmarks and demonstrate clear return on investment (ROI) through data-backed interventions.

Our comprehensive suite includes:

• CMAPP, our cloud-based care management platform
• Advanced analytics and risk-based targeting to derive ROI
• Omnichannel member and provider engagement
• Clinical services delivered by a team of 180+ licensed pharmacists, fluent in 30+ languages and dialects

We’re trusted by over 60 national and regional health plans—including the six largest payers in the U.S.

As we scale, we’re expanding our San Diego-based Technology Team across multiple positions. We’re hiring engineers and scientists to build impactful products and develop the next generation of intelligent healthcare technology in San Diego.

Software Engineer (various levels)

Roles: Software Engineer, Product Technologist, Full Stack Developer (Title and level will be commensurate with your education and experience)

Location: Onsite – San Diego, CA (No remote)

Salary Range: $160,000– $200,000 (based on experience and skills) + Annual Bonus

PHD required in Computer Science, Data Science, Engineering, or a related field

Overview

Join our San Diego-based engineering team to design and build robust, scalable technology platforms that support clinical workflows, member engagement, and real-time healthcare analytics. You’ll work across the stack, collaborating with product, data, and clinical teams to deliver impactful features in a fast-moving, mission-driven environment.

Key Responsibilities

• Develop and maintain full-stack web applications with clean, testable code
• Design and implement RESTful APIs and backend services
• Build responsive, component-based user interfaces using modern JavaScript frameworks
• Work with cloud-native tools and infrastructure for scalable deployment
• Participate in code reviews, technical design discussions, and agile ceremonies
• Collaborate cross-functionally with product managers, clinicians, and data teams
• Ensure performance, reliability, and security of deployed applications
• Contribute to platform architecture decisions as the product scales

Representative Technologies (familiarity with similar tools is welcome)

• Frontend: JavaScript (React, Angular, Vue)
• Backend: Node.js, Express, Python (Flask, FastAPI), Go, Rust
• Databases: PostgreSQL, MongoDB, Redis
• Cloud Platforms: AWS, Azure, GCP
• DevOps & Tooling: Git, CI/CD pipelines, Docker, Kubernetes

Ideal Experience

• Strong programming fundamentals and debugging skills
• Proven experience in full-stack application development
• Familiarity with modern deployment workflows and cloud services
• Agile team collaboration and iterative product delivery
• Bonus: Exposure to healthcare data, APIs, or workflows

We offer a comprehensive benefits package, including:

• 401(k) with company matching
• Health, dental, and vision insurance
• Paid time off (PTO)
• Tuition reimbursement
• Employee discounts