Inovalon is a leading cloud-based healthcare technology company that leverages data analytics and AI to drive meaningful improvements across the healthcare ecosystem. The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which serves as Inovalon’s central AI and machine learning hub. This team partners with Provider, Payer, and Pharmacy business units to identify, build, and deploy AI solutions that improve clinical and operational outcomes at scale. 

In this role, you will contribute to both classical machine learning and generative AI applications, including LLM-based and agentic solutions. You will work across the full model development lifecycle on a modern, cloud-native AWS stack, collaborating closely with AI Product Managers and a distributed team of senior engineers across the U.S. and India. 

Key Responsibilities

• Design, train, and deploy machine learning models spanning classical ML (classification, regression, clustering, time-series) and generative AI use cases including LLM-based and agentic applications. 
• Build and maintain cloud-native solutions on AWS using containerized architectures (Docker, Kubernetes) to support scalable model serving and data pipelines. 
• Own and contribute to the full Model Development Lifecycle (MDLC), including dataset versioning, model versioning, model registry management, and model evaluation frameworks. 
• Develop and integrate Python-based ML components that work seamlessly with existing product platforms across multiple business units. 
• Collaborate with AI Product Managers across the Insights BU and partner business units (Provider, Payer, Pharmacy) to translate business needs into AI solutions. 
• Apply neural networks and deep learning techniques using PyTorch for appropriate use cases alongside scikit-learn-based classical approaches. 
• Write robust, production-ready code following engineering best practices; participate in code and design reviews. 
• Leverage AI coding tools (such as Claude Code or equivalent) as part of your daily development workflow to improve velocity and code quality. 
• Mentor junior engineers and contribute to team knowledge-sharing around ML best practices, tooling, and architecture decisions. 
• Support integration of frontend components into ML-powered features where applicable. 
• Contribute to retrospectives and team process improvements; actively participate in sprint planning and end-of-iteration demos. 
• Adhere to all HIPAA, data governance, confidentiality, and regulatory requirements in all aspects of work. 
• Maintain compliance with Inovalon’s policies, procedures, and mission statement, fulfilling responsibilities that support operational and financial success. 

Qualifications

Required 

• Minimum 5 years of software development experience with a strong foundation in machine learning fundamentals and model training. 
• Expert-level Python proficiency; Python is the team’s primary language and is the highest-priority technical requirement. 
• Hands-on experience building and deploying classical ML models in production using scikit-learn. 
• Demonstrated experience with generative AI, LLMs, or agentic application development. 
• Proficiency with PyTorch and neural network architectures. 
• Practical knowledge of the Model Development Lifecycle (MDLC): dataset versioning, model versioning, model registry, and model evaluation. 
• AWS cloud experience, including deploying and managing cloud-native workloads. 
• Containerization experience with Docker and/or Kubernetes. 
• Strong problem-solving ability; demonstrated capacity to work independently and take ownership of complex technical challenges. 
• Daily usage of AI-assisted coding tools (e.g., Claude Code, GitHub Copilot, or similar) as part of standard development workflow. 

Preferred 

• Experience with database technologies (SQL or NoSQL); familiarity with data pipeline tooling. 
• Frontend development skills to support full-stack ML feature work. 
• Healthcare domain experience or exposure to HIPAA-regulated environments. 

Education 

• Bachelor’s degree in Computer Science, Data Science, Software Engineering, or a related technical field required. 
• Master’s degree or PhD in Computer Science, Machine Learning, or equivalent practical experience preferred. 

Physical Demands and Work Environment 

• Sedentary work (i.e., sitting for long periods of time). 
• Exerting up to 10 pounds of force occasionally and/or a negligible amount of force. 
• Subject to inside environmental conditions. 
• Travel for this position will include less than 10% locally, usually for training purposes. 

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

Role Overview

Zeta Global is seeking a Lead Software Engineer to build and scale healthcare-focused applications and data systems that power audience intelligence, activation, measurement, and reporting across both HCP and DTC workflows.

This is a hands-on technical leadership role operating at the intersection of distributed systems, data engineering, and healthcare domain constraints. You will design and deliver systems that integrate identity, audience data, and campaign performance while meeting strict requirements for privacy, compliance, and reliability.

The ideal candidate brings strong system design depth, experience building data-intensive platforms, and the ability to lead through architecture and execution in regulated environments.

What You’ll Build

• Full-stack applications supporting HCP and patient (DTC) audience discovery, segmentation, and activation
  • Scalable data pipelines for ingestion, normalization, and enrichment of healthcare datasets
  • Identity resolution and data linkage services across fragmented data sources
  • Reporting, attribution, and measurement systems connecting campaigns to outcomes
  • APIs and services enabling downstream activation, analytics, and partner integrations

Key Responsibilities

• Lead architecture and hands-on development of distributed systems supporting healthcare data workflows
  • Design and implement scalable data pipelines (batch and streaming) for large-scale datasets
  • Build and maintain APIs and services with strong SLAs, observability, and fault tolerance
  • Implement identity resolution logic including matching, deduplication, and graph-based linkage
  • Ensure high data quality through validation, reconciliation, and monitoring frameworks
  • Design systems with strong security controls, including encryption, access control, and auditability
  • Apply privacy-by-design principles across all systems handling PHI/PII
  • Partner with Product and Data teams to translate healthcare requirements into scalable architectures
  • Drive engineering best practices across testing, CI/CD, code quality, and operational excellence
  • Mentor engineers and act as a technical leader across the team

Engineering Expectations

• Strong experience designing distributed systems (microservices, event-driven architectures)
  • Deep understanding of data modeling, storage systems (OLTP, OLAP), and data processing frameworks
  • Experience with streaming and batch processing (e.g., Kafka, Spark, Flink, or similar)
  • Proficiency in backend development (Python, Java, or Ruby) and API design (REST/gRPC)
  • Experience building modern front-end applications (React or similar)
  • Strong experience with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code
  • Familiarity with containerization and orchestration (Docker, Kubernetes)
  • Experience implementing observability (logging, metrics, tracing) and reliability patterns
  • Strong understanding of performance optimization and scalability tradeoffs

Healthcare & Domain Expectations

• Experience working with HCP data (provider identity, targeting, segmentation)
  • Experience with patient / DTC data workflows and privacy-aware systems
  • Understanding of healthcare data ecosystems (claims, provider, or audience datasets)
  • Familiarity with identity graphs and data onboarding patterns
  • Experience building reporting or attribution systems tied to business outcomes
  • Strong grasp of HIPAA, PHI/PII, and regulated data handling requirements

Qualifications

• 8–10 years of software engineering experience with increasing technical ownership
  • Proven track record of building and scaling data-intensive or distributed systems
  • Experience working in regulated environments (healthcare strongly preferred)
  • Strong system design and architecture skills
  • Ability to lead technically while remaining hands-on in implementation
  • Strong collaboration skills across engineering, product, and data teams

Preferred

• Experience with healthcare data providers or identity ecosystems
  • Background in AdTech, MarTech, or audience/data platforms
  • Experience with privacy-enhancing technologies (tokenization, clean rooms)
  • Exposure to ML/AI-driven data products or analytics systems

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $200,000 - $215,000, depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

#LI-TS1

We’re seeking a Staff DevOps Engineer to join our Cloud Platform Team — the engineer who sets the technical direction for how Built’s infrastructure is designed, operated, and evolved. This is the most senior individual contributor role on the platform team, and it goes well beyond day-to-day operations. You’ll architect the systems that every engineering team at Built depends on, define the standards that others work within, and drive the platform roadmap with full autonomy. By raising the reliability and velocity of our infrastructure, you directly enable Built’s mission of radically disrupting construction finance.

Our Guiding Principles

• Be Bold. We pursue the biggest problems in our industry, challenge assumptions others take for granted, and take calculated risks to get there. We don’t hide behind consensus or committees. Playing it safe is just failing slowly.
• Help Customers Win. We learn our customers’ businesses deeply — how they think, how they deploy capital, what keeps them up at night. We treat their capital like our own. We ship leverage, not features. And we measure ourselves by customer results, not our intentions.
• Move with Urgency & Purpose. We bias toward delivery over perfection, remove friction from our own paths, and communicate in real time. Momentum compounds — and we build it every day.
• Own the Outcome. We own outcomes, not just tasks. We hold a high Say:Do ratio and take responsibility from idea through impact. When something breaks, we fix it — we don’t wait to be asked.
• Never Satisfied. We raise the bar continuously. We stay curious, hold exacting standards, debate hard, and hold our opinions loosely when the evidence shifts. Excellence is a habit, not an event.

What You’ll Do

• Architect and own Built’s core cloud infrastructure on AWS — defining the patterns, standards, and systems that all engineering teams build on, from EKS/ECS cluster design to VPC topology to IAM governance.
• Lead platform modernization — driving the migration and simplification of our software delivery lifecycle, rationalizing tooling, and building the infrastructure foundation for Built’s AI-related product initiatives.
• Own SLOs and SLIs for the platform — define them, instrument them in your observability stack, and lead the team in meeting reliability targets consistently across all environments.
• Define DevOps engineering standards across the team — IaC patterns, CI/CD architecture, container orchestration standards, and observability frameworks.
• Drive the platform roadmap in partnership with engineering leadership — balancing foundational investment with immediate delivery needs and communicating trade-offs clearly to technical and non-technical stakeholders.
• Lead incident response and postmortems — serve as the technical escalation point for complex infrastructure failures, drive systemic improvements, and reduce incident volume over time.
• Evaluate and adopt new technologies across the platform stack — making sound build-versus-buy decisions with a clear view of long-term trade-offs and ROI.
• Mentor a team of 5 platform engineers through design reviews, pairing, architecture guidance, and knowledge-sharing sessions across the broader engineering organization.
• Partner with Information Security to lead vulnerability assessment and security architecture — ensuring compliance, proactive risk management, and adherence to regulatory requirements.

Skills & Experience

Must-Have

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 8+ years of hands-on experience in DevOps, platform engineering, or cloud infrastructure in a production environment.
• Expert-level AWS knowledge — deep fluency with EKS, ECS, EC2, RDS, S3, IAM, VPC, and cost management tooling.
• Deep Kubernetes expertise — cluster architecture, networking, RBAC, autoscaling, and debugging production workloads at scale.
• Strong infrastructure-as-code proficiency with Terraform — writing extensible, maintainable modules and enforcing IaC standards across the team.
• Proven experience designing and operating CI/CD pipelines with GitHub Actions, CircleCI, or similar tooling.
• Hands-on observability experience with Datadog, Grafana, or similar platforms — metrics, logs, traces, monitors, SLO tracking, and alerting.
• Familiarity with incident management tooling (Incident.io, PagerDuty, or similar) and a track record of leading postmortems and driving systemic reliability improvements.
• Fluency in at least one scripting or automation language — Python, Go, or Bash.
• Strong communication skills — able to present infrastructure risks and architectural trade-offs to both engineers and non-technical stakeholders.

Nice-to-Have

• Experience with other IaC tools (Pulumi, CloudFormation, CDK) is a plus.
• Experience with service catalog and developer experience tooling (OpsLevel, Backstage, or similar).
• Background in fintech, lending, or regulated industries where uptime, auditability, and data security are critical.
• FinOps experience — cloud cost governance, right-sizing, and spend transparency across engineering teams.
• Contribution to open-source infrastructure projects or published engineering RFCs.

What the First Year Looks Like

Days 1–30: Learn the Landscape

• Ramp up on Built’s AWS infrastructure (EKS, ECS, VPC, IAM), CI/CD pipelines, and observability stack.
• Shadow on-call rotations (roughly one week every six weeks) to understand current incident patterns and pain points firsthand.
• Build relationships with product engineering teams to understand their infrastructure dependencies and friction points.

Days 30–60: Start Shaping the Platform

• Identify the highest-leverage opportunities for platform modernization and SDLC simplification.
• Begin contributing to architecture decisions and TRDs for current initiatives.
• Propose improvements to IaC standards, deployment pipelines, or observability coverage where gaps exist.

Days 60–90: Own and Drive

• Lead a meaningful platform initiative from architecture through delivery — whether modernization, reliability, or developer experience.
• Establish yourself as the technical standard-setter the team turns to for complex infrastructure and AI-related platform questions.
• Contribute to the roadmap planning process with a clear point of view on what the platform needs next.

AI & Technology Expectations

At Built, AI is a first-class part of how we work — not a pilot program. For this role specifically, that means:

• Use AI coding assistants (your choice of platform) as a daily productivity multiplier for IaC authoring, pipeline configuration, and automation scripting.
• Apply AI to platform operations: runbook generation, incident summarization, root cause analysis drafts, and postmortem synthesis.
• Drive and contribute to Built’s broader initiative to automate the software delivery lifecycle — identifying where AI can reduce manual toil across build, test, deploy, and observe workflows.
• Evaluate emerging AI infrastructure tooling and bring well-reasoned recommendations to the team.
• Share effective AI use cases and patterns with the broader engineering organization.

Operational Details

• Team size: You’ll join a team of 5 platform engineers, with this role serving as the senior technical anchor.
• On-call: Rotations run approximately one week every six weeks. We work continuously to reduce incident volume and toil so that on-call is manageable and low-noise.
• Location: Remote (US). Flexible working hours.

Built’s salary range for this position is $175,000-$235,000 USD per year. The pay range is designed to accommodate upward mobility in the role, therefore it encompasses the full span of proficiency levels for this role and we believe that the midpoint of the range is competitive in the market. Salary is just one component of Built's total compensation package for employees. Your total rewards package at Built will include equity, top-notch medical, dental and vision coverage, an unlimited PTO policy, and other benefits.

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn't coming; it's here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

As a Senior Data Engineer at Metropolis, you will play a key role in shaping data products that align with our mission. Your technical expertise and analytical acumen will contribute to designing and building extensive data sets that impact thousands of internal users and millions of members. Join a world-class data engineering team dedicated to advancing your skills and career in data engineering and beyond.

What you'll do

• Collaborate with cross-functional teams to develop end-to-end data pipelines and foundational data sets
• Design and own data architecture for large-scale projects while managing operational trade-offs
• Build and optimize sophisticated data pipelines, models, and visualizations across multiple domains
• Define and manage Service Level Agreements (SLAs) for all owned data sets
• Implement data security models, ensure privacy compliance, and evolve data governance processes
• Solve complex integration challenges using optimal ETL/ELT patterns for structured and unstructured data
• Maintain production processes by optimizing complex code using advanced algorithmic concepts
• Streamline data artifact development by optimizing pipelines, dashboards, and frameworks
• Mentor team members through actionable feedback to foster collective skill growth
• Maintain flexibility with availability during evening hours

What we're looking for

• Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field
• master's degree is preferred
• 5+ years of experience in data engineering, database engineering, business intelligence, data warehousing, and ETL tools, working with large data sets in the cloud
• 5+ years of experience with Python, and experience building scalable Big Data solutions and ETL ecosystems
• Proficiency in SQL, ETL/ELT, and data modeling, with extensive experience in Snowflake and dbt
• Hands-on experience with RDBMS such as MySQL, MS SQL Server (optional), and Postgres
• Familiarity with integration tools like Airflow and Automic, along with a working knowledge of CI/CD pipelines
• Ability to deliver high standards of code quality, system reliability, and performance
• Deep understanding of the modern IaC ecosystem to drive automated infrastructure deployments
• Experience with cloud computing services, preferably AWS, including hands-on experience with services like Glue, Airflow (MWAA), DMS, EKS, and SNS

While not required, these are a plus:

• Experience with Spark and PySpark
• Master's degree in Computer Science, Computer Engineering, or a relevant technical field

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $160,000.00 USD to $220,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-CM1 #LI-Onsite

What You'll Do:

• Participate fully in the Solutions Engineering Academy bootcamp, mastering core product knowledge, sales methodologies, and demonstration techniques.
• Shadow and support the Commercial sales team throughout the sales cycle, including discovery calls and technical discussions, in preparation for a client-facing role.
• Conduct internal practice demonstrations of the Motive product offering, effectively showcasing our core value proposition, specifically the capabilities driven by Artificial Intelligence and Machine Learning.
• Develop expertise in Motive's integrated platform, spanning IoT hardware (in-vehicle devices, sensors), cloud-based data aggregation, and AI/ML features that automate complex operational workflows.
• Learn to successfully match customer pain points and requirements to proposed solutions, articulating clear business benefits and foundational return on investment (ROI).
• Rapidly become a subject matter expert on Motive’s current product offering and future roadmap.
• Collaborate closely with the Product Team to provide feedback from the field and assist with training on new feature releases.
• Act as a technical liaison during the training phase between the sales team and various internal organizations, including Product, Engineering, and Customer Success, ensuring seamless information flow.
• Prepare and deliver technical presentations and mock proposals that clearly articulate the value and functionality of Motive's solutions.

What We're Looking For:

• Bachelor's Degree required
• 0-1 years of professional experience. Internship experience in a pre-sales, technical support, or customer-facing role is a significant plus.
• A strong desire and ability to quickly learn complex SaaS and hardware solutions, paired with a genuine interest in experimenting with and understanding how AI/ML models and IoT devices operate in real-world environments.
• Excellent communication skills, both verbal and written, with the ability to explain complex technical concepts in an understandable way.
• Proven analytical and problem-solving skills, with the ability to understand customer challenges and propose effective technical solutions.
• The ability to quickly connect technical solution features to tangible business outcomes and value.
• A strong desire to learn, grow, and execute in a dynamic and fast-paced environment.
• Interest in the Transportation & Logistics industry is beneficial.

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

The responsibilities of our Platform team include building and maintaining all backend services, including, but not limited to, payments, analytics, subscriptions, new products, text to speech, and external APIs.

This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, is passionate about making product decisions, and has experience building great user experiences that delight users.

We are a flat organization that allows anyone to become a leader by showing excellent technical skills and delivering results consistently and fast. Work ethic, solid communication skills, and obsession with winning are paramount. 

Our interview process involves several technical interviews and we aim to complete them within 1 week. 

What You’ll Do

• Design, develop, and maintain robust APIs including public TTS API, internal APIs like Payment, Subscription, Auth and Consumption Tracking, ensuring they meet business and scalability requirements
• Oversee the full backend API landscape, enhancing and optimizing for performance and maintainability
• Collaborate on B2B solutions, focusing on customization and integration needs for enterprise clients
• Work closely with cross-functional teams to align backend architecture with overall product strategy and user experience

An Ideal Candidate Should Have

• Proven experience in backend development: TS/Node (required)
• Direct experience with GCP and knowledge of AWS, Azure, or other cloud providers
• Efficiency in ideation and implementation, prioritizing tasks based on urgency and impact
• Preferred: Experience with Docker and containerized deployments
• Preferred: Proficiency in deploying high availability applications on Kubernetes

What We Offer

• A dynamic environment where your contributions shape the company and its products
• A team that values innovation, intuition, and drive
• Autonomy, fostering focus and creativity
• The opportunity to have a significant impact in a revolutionary industry
• Competitive compensation, a welcoming atmosphere, and a commitment to an exceptional asynchronous work culture
• The privilege of working on a product that changes lives, particularly for those with learning differences like dyslexia, ADD, and more
• An active role at the intersection of artificial intelligence and audio – a rapidly evolving tech domain

The United States Based Salary range for this role is: 140,000-200,000 USD/Year + Bonus + Stock depending on experience

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

About the team/role

As the Staff Knowledge Base Specialist, you will be a senior contributor to the knowledge systems that enable both Checkr's human and digital workers to resolve issues accurately and efficiently. This is a senior individual contributor role within Shared Services, responsible for leading complex, cross-functional knowledge programs that span department boundaries and directly shape the quality of agent-assisted and AI-driven resolution at scale. You will set strategy, clarify goals, and independently drive programs from initiation to measurable outcomes.

Knowledge at Checkr serves a dual audience: human agents who rely on clear, actionable content to resolve complex cases, and AI agents that retrieve, reason over, and act on that same knowledge base autonomously. This role requires mastery of both dimensions. You will design content that is clear and actionable for human agents while simultaneously being structured for accurate AI retrieval, optimized for fast search, and enriched with metadata that drives correct segmentation and response logic. You will also build, manage, and iterate on AI workforce agents that accelerate knowledge operations, treating them as members of your toolkit the same way you would a contractor or vendor.

Our ideal candidate brings a rare combination of disciplines: the precision of a technical writer, the systems thinking of an information architect, and the LLM fluency of a prompt engineer. You have hands-on experience building knowledge for RAG-based AI systems, a sharp instinct for the content gaps that cause agent escalations and model hallucinations, and the ability to drive alignment across engineering, product, quality, and operations partners. You thrive in ambiguity, mentor peers, and balance department impact with broader company objectives. You are startup-minded: comfortable building from scratch, owning ambiguous problems end to end, and leveraging AI agents as force multipliers to drive outcomes at a scale beyond what manual effort allows.

This role is based in Nashville, TN and requires periodic travel (<25%) to connect with teams across Checkr office locations in San Francisco and Denver.

What you'll do

• Design and drive Checkr's agent-facing knowledge architecture: content structure, chunking strategy, metadata schema, retrieval optimization, and decision logic encoding for both human and AI agent consumption.
• Independently lead complex, cross-functional knowledge programs from initiation to delivery, coordinating with product, engineering, quality, and operations stakeholders to set strategy and achieve program goals within planned timeframes.
• Build, deploy, and manage AI workforce agents that execute knowledge operations tasks, including content audits, metadata enrichment, quality checks, and triage workflows, owning agent performance and iterating on prompts, logic, and guardrails to improve outcomes.
• Define and enforce authoring standards that serve a dual audience: content readable and actionable for frontline BPO agents, and structured for accurate, low-latency AI retrieval.
• Design and manage analytical workflows, including AI assisted triage, to surface knowledge gaps from escalation patterns, quality scores, and conversation failure logs.
• Proactively identify and anticipate risks and gaps in the knowledge ecosystem, including content that misleads agents, creates compliance exposure, or degrades AI performance; propose and execute next steps without waiting to be directed.
• Build and maintain metadata frameworks that ensure knowledge is correctly segmented across agent types, customer tiers, product lines, and support workflows.
• Partner with AI/Product and Engineering teams to surface knowledge-side limitations affecting agent and AI resolution quality, influence prompt design, and advocate for platform enhancements.
• Identify opportunities across agent and AI performance data to drive continuous improvements to content standards, knowledge architecture, and intake processes.
• Serve as a trusted cross-functional partner to Quality, Training, Service Design, and frontline operations teams, translating frontline agent experience needs into knowledge improvements.
• Mentor Knowledge team members on agent-aware and AI-aware authoring practices, providing clear, specific feedback and coaching to build team capability.

What you bring

• 5+ years of experience in knowledge management, information architecture, technical writing, or content operations, with demonstrated progression in scope and complexity.
• 2+ years of hands-on experience building knowledge for AI systems, including chunking strategies, metadata design, retrieval accuracy improvement, and hallucination reduction in a RAG-based environment.
• Experience designing content for a dual audience: human agents who need clear, scannable, actionable content and AI systems that require precision structure for accurate retrieval and reasoning.
• Hands-on experience building and managing AI agents or automated workflows (e.g., prompt chains, decision agents, RPA sequences) to execute operational tasks at scale.
• Proven ability to independently lead complex, cross-functional programs, balancing department priorities with broader company objectives and driving outcomes without direct authority.
• Fluency with leading LLMs (GPT-4, Claude, Gemini) and Gen AI concepts including RAG, agentic AI, chain-of-thought prompting, decision flows, and vector search.
• Strong systems thinking: ability to trace how a knowledge gap, metadata error, or unclear procedure propagates into agent escalations, AI failures, and customer experience degradation.
• Analytical mindset with comfort reading quality scores, latency logs, and accuracy data to diagnose root causes and design targeted solutions.
• Track record of proactively identifying risks, leading retrospectives, and implementing process improvements that prevent recurring issues.
• Demonstrated ability to mentor and coach more junior team members; experience leading external contractors is a plus.
• Exceptional written communication: able to produce clear, actionable content for agent-facing audiences and translate complex AI-system concepts into standards and recommendations for varied stakeholders.
• Preferred: Experience with Zendesk or Salesforce knowledge bases.
• Preferred: Background in support operations or conversation design.
• An A-player mindset with a strong bias for action: you raise the bar, move with urgency, stay resilient through ambiguity, and take ownership to deliver meaningful outcomes

What you'll get

• A fast-paced and collaborative environment
• Learning and development allowance
• Competitive compensation and opportunity for advancement
• 100% medical, dental, and vision coverage
• Up to $25K reimbursement for fertility, adoption, and parental planning services
• Flexible PTO policy
• Monthly wellness stipend

Location: Nashville, TN

Work Environment: Hybrid, periodic travel required   

Target Compensation Range: $130,000 to $170,000

Role Summary: Lead data engineering workstreams and build high-quality data solutions that support client reporting, analytics, and data pipelines.

Who We Are 

At The Gunter Group (TGG), we are a people-first management consulting firm and proud 20-time workplace award winner. We build trusted partnerships with our clients by working alongside their teams. Together, we deliver practical solutions and lasting impact across strategy, execution, people, and technology. We show up ready to roll up our sleeves, solve complex problems, and make a real difference together.

Your Impact at The Gunter Group

As a Senior Consultant – Data Engineer at The Gunter Group, you partner closely with clients and consulting teams to deliver meaningful business results through high-quality data engineering solutions. You take ownership of technical workstreams, help guide delivery, and collaborate with both technical and non-technical stakeholders to turn unstructured challenges into structured, actionable data solutions.

You contribute across a variety of industries and engagement types, applying strong technical judgment and practical problem-solving skills to design, build, and deliver data platforms and pipelines that support client goals.

Lead High-Impact Client Delivery

• Play a key role in client engagement delivery by leading data engineering workstreams and guiding TGG teams to successful project outcomes.
• Flex across delivery environments, working as an individual contributor, part of a consulting team, or as a technical or workstream lead embedded with the client.
• Apply structured methodologies, toolkits, and best practices to execute effectively and deliver high-quality data solutions.
• Embrace unstructured challenges and help turn them into actionable plans and measurable outcomes.

Deliver Data Engineering & Analytics Solutions

• Analyze requirements and design, build, debug, and deploy cloud-based data services and components.
• Build and schedule data pipelines to extract, transform, and store data across SQL databases and cloud platforms including Azure, GCP, AWS, and Snowflake.
• Explore and analyze data using Excel, Power Query, SQL, and Python, developing solutions in Python/Jupyter and presenting insights through data visualizations.
• Develop and maintain design documentation, data models, and interface specifications.
• Write unit tests and work within CI/CD, code quality, and UAT processes.

Collaborate Across Stakeholders and Teams

• Partner with client stakeholders ranging from individual contributors to senior executives to align on goals and deliver outcomes.
• Communicate effectively with IT developers, product owners, and other technical stakeholders.
• Work alongside a collaborative team of TGG consultants committed to delivering outstanding client service.
• Engage with TGG partners, principals, account leaders, managers, and peers who support your success across engagements

What You Bring 

• 6+ years of consulting or related experience with a strong track record of client service and delivering results.
• Proven ability to collaborate with non-technical stakeholders to gather requirements, plan delivery, and communicate results using clear documentation, diagrams, and presentations.
• Experience with data science and machine learning concepts and methods.
• Experience with Python, SQL, and BI/analytics tools (e.g., Power BI, Tableau), and familiarity with modern programming languages and frameworks (Java, C#/.NET, JavaScript). 
• Understanding of programming paradigms, source control, and software lifecycle best practices (e.g., Git). 
• Strong knowledge of data lifecycles, including how data is collected, transformed, stored, and consumed. 
• Experience working in Agile/Scrum environments and translating business needs into effective technology solutions.

Working at The Gunter Group

Salary and Benefits

Supporting the well-being of our team is a priority at TGG. Our benefits package includes competitive health coverage, wellness programs, flexible PTO, professional development and work-from-home stipends, as well as team offsites, social events, and volunteer opportunities.

The total expected compensation range for this role is $130,000 to $170,000, consisting of a base salary and variable billing bonus component. Additional compensation may be earned through contributions to account leadership and business development. We discuss compensation and bonus opportunities openly throughout the hiring process.

Why TGG

The Gunter Group is headquartered in Portland, Oregon, with team members primarily located in our three core geographies: Portland, Nashville, and Denver. Our consultants work across remote, hybrid, and onsite environments depending on client needs, with travel expectations varying by engagement and aligned collaboratively with both clients and team members.

We partner with organizations across industries including retail, apparel, government, education, insurance, and Fortune 100 companies, working alongside client teams to solve complex problems and deliver practical solutions that drive lasting results. Our work is rooted in strong relationships, thoughtful execution, and a shared commitment to doing quality work.

At TGG, we believe people do their best work when they feel respected, supported, and included. We are committed to fostering an engaging, fair, and authentic environment where diverse backgrounds and perspectives are valued. Our culture is guided by non‑negotiable values—including integrity, curiosity, emotional intelligence, collaboration, confidence, and the ability to thrive in ambiguity—and by a high standard of excellence in how we show up for our clients and each other.

The Gunter Group LLC is an equal opportunity employer.

WORKING AT THE MLC

The MLC is committed to excellence, service, transparency, and diversity. Our culture is collaborative, our people are adaptable. On our team, you are respected, valued for your unique strengths and experiences, and empowered to identify and resolve your own challenges.

WHO WE ARE

The Mechanical Licensing Collective (The MLC) is a nonprofit organization designated by the U.S. Copyright Office to administer blanket mechanical licenses for digital music services in the United States. Our mission is to ensure songwriters, composers, and music publishers are accurately compensated for the use of their music.

Operating at the intersection of music, data, and technology, we process billions of usage records, match them to the correct musical works, and distribute royalties with accuracy and transparency. As we continue to grow, we are building scalable data platforms and workflows that power the future of digital music licensing.

THE ROLE

As a SQL Engineer / Data Analyst, you will play a critical role in designing, building, and maintaining scalable data solutions that power usage and royalty processing, reporting, and internal analytics. You’ll work closely with Data Platform, Engineering, Finance, and Member Experience teams to ensure data integrity, accessibility, and performance across systems.

This role is ideal for someone who enjoys working with complex datasets, optimizing queries for performance, and building reliable data pipelines that directly support business-critical operations.

Preference to individuals in Eastern and Central Time Zone to accommodate for UK team member collaboration.

QUALIFICATIONS

Required

· 3+ years of experience writing complex SQL queries in a production environment

· Strong experience with relational databases (e.g., PostgreSQL, Oracle)

· Proven ability to optimize queries and improve database performance

· Experience working with large, complex datasets

· Strong problem-solving skills and attention to detail

· Ability to communicate technical concepts to non-technical stakeholders

Preferred

· Experience with cloud data platforms (AWS Athena, Metabase, or similar)

· Familiarity with ETL/ELT processes and data pipeline concepts

· Experience supporting financial, royalty, or transactional data systems

· Understanding of data modeling concepts (star schema, normalization, etc.)

ESSENTIAL RESPONSIBILITIES

AS A MEMBER OF THE TECH TEAM, YOU WILL:

· Design, develop, and maintain complex SQL queries, stored procedures, and views to support business operations and reporting

· Optimize database performance through query tuning, indexing strategies, and execution plan analysis

· Partner with Data Engineers and Analytics teams to support data pipelines and transformations across platforms (e.g., AWS Athena, Metabase, or similar)

· Support royalty processing workflows by ensuring accuracy, consistency, and timeliness of data outputs

· Collaborate with cross-functional stakeholders (Finance, Rights Management, Member Experience) to translate business requirements into scalable data solutions

· Troubleshoot data discrepancies and implement long-term fixes to improve data quality

· Contribute to data governance, documentation, and best practices across the data ecosystem

· Assist in building and maintaining reporting datasets for internal and external stakeholders

· Data quality and validation frameworks to ensure accuracy