About Sovrn

Every interesting company solves important problems for other people.  Sovrn is a Software and Data business that helps Open Web businesses be and remain independent.  We help them understand their business better, operate more efficiently, and make & keep more money.

• We believe in the freedom and free-flow of information.
• We believe the Open Web is the largest source of this information.
• We believe in helping Open Web businesses be and remain Independent.

Through Software products and Data solutions we help our customers:

• Understand their business better, so they can make better decisions
• Operate their business more efficiently, so they can invest in what matters most
• Make (and Keep) more money, so they control their own destiny

About the Role

We're looking for a Principal Software Engineer with deep roots in adtech infrastructure and a genuine conviction about what AI-native engineering looks like in practice. This role is backend-focused at its core — you'll work on the systems that power our exchange, from bid request processing and traffic shaping to data pipelines and auction logic. But we're also at an inflection point in how we build software, and we want this person to help lead us through it.

From a generative/agentic AI capabilities standpoint, we already use LLMs and agentic tooling across our data stack and, we’re looking for is someone who can help us take that from general adoption to intentional practice — who has strong opinions about where AI creates real leverage in a high-throughput adtech environment, and who can bring the rest of the engineering organization along with them.

Languages/components/tools in our stack: Java, Kafka (Redpanda), AWS, Databricks, Datadog, ONYX.

What you'll be doing:

• Own the design and evolution of backend systems that operate at exchange scale — high throughput, low latency, always on
• Lead architectural decisions across auction infrastructure, bid processing, traffic shaping, and supply-side integrations
• Establish and champion AI engineering practices across the team — from prompt engineering and RAG patterns to agentic workflow design and LLM evaluation
• Identify high-leverage opportunities to apply AI in our adtech stack: traffic scoring and filtering, bid shading, yield optimization, anomaly detection, and automated decisioning
• Set standards for how we evaluate, trust, and operate AI-powered systems in production — including observability, fallback behavior, and model governance
• Drive technical standards, design reviews, and engineering best practices across a senior team
• Partner with product, data science, and platform teams to ship end-to-end
• Help the broader engineering team build fluency and confidence with AI tooling, not just tolerance of it
• Mentor and level up engineers through code review, design collaboration, and hands-on guidance

A successful candidate will have:

• 10+ years of software engineering experience, with a strong backend track record
• 5+ years working specifically in adtech infrastructure — SSP, DSP, exchange, or ad server environments
• Deep fluency in the programmatic ecosystem: OpenRTB, bid request/response flows, auction mechanics, supply path optimization, or similar
• Experience building and operating systems at exchange scale — high QPS, strict latency budgets, fault tolerance
• Demonstrated experience leading AI or agentic engineering efforts in production environments — not just experimentation, but shipped, operated, and iterated on
• Hands-on experience with LLM integration patterns: RAG, tool use, multi-step agentic workflows, prompt engineering, and evaluation frameworks
• Strong distributed systems fundamentals: messaging, caching, service architecture, observability
• Comfort driving technical decisions in ambiguous, fast-moving environments
• A point of view on where AI is and isn't the right tool — and the credibility to make that case

Location: This position is based in our Boulder Colorado or New York City office. Applicants need to be able to commute/travel to our Boulder or New York City location. For exceptional candidates we would consider remote locations in these states: AZ, CA, CO, GA, MD, MA, MI, MO, NJ, NY, NC, OK, TX, UT, WA. #LI-Hybrid #LI-Remote

We understand that no candidate is perfectly qualified for any job. Experience comes in different forms; many skills are transferable; and passion goes a long way. Even more important than your resume is a clear demonstration of accountability and the ability to thrive in a fluid and collaborative environment. We expect you to learn new things in this role and encourage you to apply if your experience is close to what we’re looking for.

Sovrn Core Values: Candid, Customer Empathy, Learning, Scrappy, Second Order Thinking

Compensation and Benefits

The base pay range for this position is $200,000 to $240,000 annually. In addition to the base salary, the total compensation package includes bonus, equity, and benefits. Actual earnings may vary depending on the candidate’s direct experience, skills, industry knowledge, and location.

Sovrn offers a full slate of benefits from competitive salaries, stock options, medical, dental, and vision coverage, short and long-term disability, life insurance, 11 paid holidays, flexible vacation, commuter benefits, a 401(k) plan and match, and a paid parental leave program.

Job Posting

Applications will be accepted until July 1, 2026.

Equal Opportunity Employer

Sovrn is proud to be an Equal Opportunity Employer and provides equal employment opportunities to all employees and applicants regardless of race, color, religion, gender, gender identity, age, national origin, disability, parental or pregnancy status, marriage and civil partnership, sexual orientation, veteran status, or any other characteristic protected by law.

Recruitment Agencies

Sovrn does not accept agency resumes. Please do not forward resumes to our jobs alias or Sovrn employees. Sovrn is not responsible for any fees related to unsolicited resumes.

About Sovrn

Every interesting company solves important problems for other people.  Sovrn is a Software and Data business that helps Open Web businesses be and remain independent.  We help them understand their business better, operate more efficiently, and make & keep more money.

• We believe in the freedom and free-flow of information.
• We believe the Open Web is the largest source of this information.
• We believe in helping Open Web businesses be and remain Independent.

Through Software products and Data solutions we help our customers:

• Understand their business better, so they can make better decisions
• Operate their business more efficiently, so they can invest in what matters most
• Make (and Keep) more money, so they control their own destiny

About the Role

We’re looking for a Principal Software Engineer (Data) with deep roots in adtech data infrastructure and a genuine conviction about what AI-native data engineering looks like in practice. This is a specialized principal-level engineering role — one that carries all the architectural ownership and technical leadership expectations of a Principal Software Engineer, focused on Sovrn’s Data Collective.

From a generative/agentic AI capabilities standpoint, we already use LLMs and agentic tooling across our data stack and, we’re looking for is someone who can help us take that from general adoption to intentional practice — who has strong opinions about where AI creates real leverage in a high-throughput adtech environment, and who can bring the rest of the engineering organization along with them.

Languages/components/tools in our stack: Python, Pyspark, Kafka, Databricks, AWS

What you'll be doing:

Data Platform & Architecture

• Own the design and evolution of data platform systems that operate at exchange scale; high throughput, real-time streaming, and always-on batch pipelines
• Lead architectural decisions across data infrastructure: pipeline design, data modeling, lakehouse architecture, and data services layers
• Specify data platform components and configurations required for pipeline implementation; define pipeline observability to understand and improve performance at massive scale
• Research, implement, and evolve methods to process and democratize data across the organization
• Drive technical standards, design reviews, and engineering best practices across a senior team
• Partner with product, data science, and platform teams to ship end-to-end

AI & Agentic Engineering Leadership

• Establish and champion AI engineering practices across the team, from prompt engineering and RAG patterns to agentic workflow design, LLM evaluation, and progressive implementation of agentic design patterns
• Identify high-leverage opportunities to apply AI in our data stack: intelligent pipeline optimization, anomaly detection, automated data quality, forecasting, and LLM-powered data services
• Lead the evolution of our existing LLM and agentic tooling from passive use to intentional, well-architected integration within our data platform
• Set standards for how we evaluate, trust, and operate AI-powered systems in production, including observability, fallback behavior, and model governance
• Help the broader engineering team build fluency and confidence with AI tooling, not just tolerance of it

Collaboration & Mentorship

• Provide domain expertise across the organization to enable business growth through data services and data models
• Provide counsel to all consumers and stakeholders of data to enable efficient and impactful use of our data assets
• Mentor and level up engineers through code review, design collaboration, and hands-on guidance; foster a culture of innovation and continuous learning
• Operate with high autonomy across ambiguous, high-impact problems

A successful candidate will have:

• 10+ years of software engineering experience, with a strong data engineering and backend track record
• 5+ years working specifically in adtech data infrastructure, SSP, DSP, exchange, or ad server environments
• Deep fluency in the programmatic ecosystem: OpenRTB, bid request/response flows, auction mechanics, supply path optimization, or similar
• Excellent understanding of real-time streaming and batch pipelines, big data, and data lakes; hands-on experience in distributed data processing in the AWS ecosystem
• Strong understanding of second-layer big data platforms such as Snowflake and Databricks, applicable use cases, best practices, implementation, and support considerations
• Strong experience in structured, unstructured, and semi-structured data techniques; metadata management, data lineage, and data governance
• Experience with data security and compliance (PII, CCPA, GDPR, etc.)
• Demonstrated experience leading AI or agentic engineering efforts in production environments; not just experimentation, but shipped, operated, and iterated on
• Hands-on experience with LLM integration patterns: RAG, vector DBs, tool use, multi-step agentic workflows, prompt engineering, and evaluation frameworks
• Ability to clearly document and communicate architectural concepts at multiple levels; ability to lead problem definition, solution designs, and implementation work plans
• Understanding of DevOps and SRE practices
• Comfort driving technical decisions in ambiguous, fast-moving environments
• A point of view on where AI is and isn’t the right too, and the credibility to make that case

Location: This position is based in our Boulder Colorado or New York City office. Applicants need to be able to commute/travel to our Boulder or New York City location. For exceptional candidates we would consider remote locations in these states: AZ, CA, CO, GA, MD, MA, MI, MO, NJ, NY, NC, OK, TX, UT, WA. #LI-Remote, #LI-Hybrid

We understand that no candidate is perfectly qualified for any job. Experience comes in different forms; many skills are transferable; and passion goes a long way. Even more important than your resume is a clear demonstration of accountability and the ability to thrive in a fluid and collaborative environment. We expect you to learn new things in this role and encourage you to apply if your experience is close to what we’re looking for.

Sovrn Core Values: Candid, Customer Empathy, Learning, Scrappy, Second Order Thinking

Compensation and Benefits

The base pay range for this position is $200,000 to $240,000 annually. In addition to the base salary, the total compensation package includes bonus, equity, and benefits. Actual earnings may vary depending on the candidate’s direct experience, skills, industry knowledge, and location.

Sovrn offers a full slate of benefits from competitive salaries, stock options, medical, dental, and vision coverage, short and long-term disability, life insurance, 11 paid holidays, flexible vacation, commuter benefits, a 401(k) plan and match, and a paid parental leave program.

Job Posting

Applications will be accepted until July 1, 2026.

Equal Opportunity Employer

Sovrn is proud to be an Equal Opportunity Employer and provides equal employment opportunities to all employees and applicants regardless of race, color, religion, gender, gender identity, age, national origin, disability, parental or pregnancy status, marriage and civil partnership, sexual orientation, veteran status, or any other characteristic protected by law.

Recruitment Agencies

Sovrn does not accept agency resumes. Please do not forward resumes to our jobs alias or Sovrn employees. Sovrn is not responsible for any fees related to unsolicited resumes.

Position Summary: 

Join our mission to infuse cutting-edge AI/ML/GenAI into pharmacy benefits as a Machine Learning Engineer.  We are looking for a software engineer with machine learning expertise to join us in expanding our AI capabilities, enabling increased productivity and magical experiences in our products and services. 

In this role you will be expected to design and implement complex AI systems that leverage ML models for NLP, NLG, multimodal data analysis, chatbots, and RAG-based QnA. The ideal candidate should be passionate about applying AI/ML concepts to difficult problems and develop scalable solutions. We want people who like working in a collaborative team environment and enjoy creating practical, efficient, and high-performance software that leverages Large Language Models (LLM), Multimodal Language Models(MLM), and other ML models and techniques to build amazing capabilities for our customers, partners, and employees. Most importantly, we are a mission-oriented, high-growth startup and we are looking for folks that are excited to be part of our journey to make lasting impact towards transforming healthcare. 

Responsibilities: 

• Develop and productionize machine learning (ML) solutions in the fields of Document understanding, Search and QnA, GenAI, Virtual Agents, etc. 

• Develop and maintain backend services using Python, focusing on AI-driven applications. 

• Design and implement APIs for seamless integration with AI models and services. 

• Develop tools for large-scale data processing and ETL and contribute to extracting insights from data to help guide ML systems development 

• Participate in code reviews, testing, and quality assurance processes. 

• Troubleshoot and resolve technical issues related to AI model, integration, deployment and backend services. 

• Develop algorithms to ensure the integrity and robustness of ML solutions by developing automated testing and validation processes. 

• Document and communicate development processes and implementation details with peers and supervisors 

• Ensure the security and compliance of healthcare data, adhering to HIPAA regulations. 

Required Qualifications: 

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related quantitative field. 

• 2+ years experience in the industry with a strong focus on ML solutions development and production deployment is a plus. 

• Good understanding of Machine Learning fundamentals such as Deep Neural Networks, Transformer-based LLM and MLMs, Boosted or standard decision trees, RAG, etc.  

• Strong grasp of OOP, Design Patterns, efficient algorithms, and quality software development. 

• Proficiency in Python and familiarity with ML libraries such as PyTorch. 

• Familiarity with GenAI services such as OpenAI GPT, Anthropic Claude, Google Gemma etc. Some experience in developing and fine-tuning prompts on any of the GenAI services is a plus. 

• Excellent problem-solving skills, attention to detail, and a strong capacity for logical thinking. 

• The ability to work collaboratively across multiple disciplines in an extremely fast-paced, startup environment. 

• Good written communication skills that enable collaboration in a remote environment. 

About the Opportunity

The Customer Insights & Adoption (CIA) team is hiring a Senior Product Architect, Internal Tools (f/m/d) to design and build internal products that help Contentful teams work smarter. This role serves internal product development, turning ambiguous workflow problems into useful systems that improve how Customer Experience, Sales, and Partner-facing teams operate every day.

This is a hands-on role with approximately 60% implementation and 40% architecture and planning. You will actively contribute production code while owning technical design and direction for a focused set of internal tools that support pipeline, retention, and customer experience outcomes. You’ll prototype, iterate, and operationalize internal systems that are lightweight where they should be, durable where they need to be, and designed for clear long-term ownership.

If you are excited by the idea of shipping high-leverage internal tools, bringing order to messy workflows, and translating promising prototypes into systems people actually rely on, this role offers the chance to have visible impact across the business.

Why this role matters

CIA’s internal tools work is part of how we turn customer, field, and partner insights into operational advantage. The right tools help our teams move faster, reduce manual work, improve data quality, and create a more consistent way of supporting customers and partners. This role exists to make those improvements real — not as one-off experiments, but as well-scoped internal products and patterns that deliver demonstrable value for our internal teams.

• Join a high-impact team building internal products that improve customer experience, strengthen field effectiveness, and help Contentful scale more effectively
• Shape how CIA approaches internal product development, R&D, and technical architecture — with meaningful room to influence both the systems we build and the way we build them
• Work on a wide range of interesting problems, from internal apps and integrations to structured data workflows, experimentation, and AI-assisted tooling
• Partner with deeply cross-functional stakeholders across CX, Sales, Partnerships, Product, IT, and Platform teams, with visible impact on how Contentful operates internally

What to expect? 

This is a hands-on role with approximately 60% implementation and 40% architecture and planning

• Own and evolve a focused set of internal tools, utilities, and integrations that support the Customer Experience organization (CSMs, Support, Professional Services, Learning Services) and cross-functional internal users such as Sales, Partnerships, and Pricing & Packaging
• Lead R&D and rapid prototyping efforts to identify high-leverage solutions, then determine which ideas should remain lightweight, which should be operationalized, and which should be designed for clean handoff to other teams
• Build production-quality front-end and back-end code, including API design, data flows, resilience, observability, and robust internal user experiences that align with our design system and engineering standards
• Apply component-based and front-end best practices to ensure internal tools are consistent, scalable, and maintainable
• Leverage Contentful and other internal platforms where appropriate to create reusable patterns and scalable internal solutions rather than reinventing common capabilities from scratch
• Explore and implement web crawler and scraper approaches, structured extraction workflows, and other internal data-ingestion patterns
• Explore and implement AI-assisted workflows where relevant to improve internal tools, accelerate development, and support pragmatic experimentation without compromising quality or maintainability
• Collaborate with IT, InfoSec, Platform, Legal, and Privacy partners on responsible data handling, hosting, identity, compliance, and operational readiness
• Define success metrics, instrument telemetry, report impact, and document architecture & playbooks so that stakeholders understand where they unlock value for Sales, CSMs, Professional Services, and adjacent teams, and how other teams can support or extend the systems over time

What success looks like

• Customer Experience, Sales, and partner-facing internal teams rely on a focused set of internal tools that are easy to use, well adopted, and meaningfully improve how work gets done across the business
• Internal tools built by this role are consistent, scalable, and reliable, reflecting strong front-end patterns, sound API and data-flow design, and user experiences that align with Contentful’s design system and internal platform standards
• Stakeholders have clear visibility into the impact of CIA-built systems through trusted success metrics such as adoption, time saved, data quality, and reliability, and use those signals to prioritize future investments
• Cross-functional partners experience CIA as a pragmatic, high-leverage internal product and architecture function that can take ambiguous problems, define the right solution, and deliver useful systems that support pipeline, retention, and customer experience outcomes
• Reusable patterns, technical documentation, and operating playbooks make it easier for adjacent teams to build on this work, support it over time, and extend internal tooling without accumulating unnecessary complexity or one-off solutions

What you need to be successful

• Demonstrated ability to balance system design with hands-on implementation, including recent experience contributing to production codebases
• 7–10 years building and operating production web applications
• Hands-on expertise with modern TypeScript, React and Next.js (or equivalent), state management, testing, performance, and accessibility best practices
• Back-end experience with Node.js and TypeScript, API design, eventing or queues, and serverless or containerized services, along with sound observability practices across logs, metrics, and traces
• Experience with Contentful or similar API-first CMS and composable content platforms
• Ability to translate ambiguous requirements into clear technical designs and scalable implementations, engineered for maintainability and ownership transfer
• Experience designing web application architectures, data flows, and integration points across multiple systems, with judgment about when to build a full product, when to automate, and when to keep a solution intentionally small
• Experience establishing lightweight engineering practices for a small team, including clear documentation, code review norms, testing approaches, release discipline, and operational readiness
• Mentorship and technical leadership that raises the bar on code quality, design rigor, and documentation while helping peers make better architectural decisions
• Clear written and verbal communication with technical and non-technical stakeholders, along with a bias for action and evidence-based decision making

Nice to Have

• Practical experience with AI and LLM-based workflows, particularly spec-based development, evaluation, and test or guardrail processes
• Experience working with component-based front-end architectures and design systems, including design tokens, component libraries, CSS architecture, accessibility, and Figma design and development experience
• Familiarity with web crawling and scraping approaches, including structured content extraction, normalization, and change detection
• Experience building internal tools, dashboards, or workflow systems for customer-facing, revenue, or operations teams

What’s in it for you?

• Join an ambitious tech company reshaping the way people build digital experiences
• Full-time employees receive equity awards for the opportunity to share in the success of our company
• Comprehensive healthcare package covering 100% of monthly health premiums for employees and 85% of costs for your dependents. 
• Fertility and family building benefits, including a lifetime reimbursable wallet to support your growing family.
• We value Work-Life balance and You Time! A generous amount of paid time off, including vacation days, sick days, compassion days for loss,  education days, and volunteer days
• Company paid parental leave to care for and focus on your growing family 
• Use your personal annual education budget to improve your skills and grow in your career
• Enjoy a full range of virtual and in-person events, including workshops, guest speakers, and fun team activities, supporting learning and networking exchange beyond the usual work duties 
• An annual wellbeing stipend to care for your physical, financial, or emotional health
• A monthly communication stipend and phone hardware upgrade reimbursement.
• New hire office equipment stipend for hybrid or distributed employees. Get the gear you need to work at your best.

Position Overview:

As the Director of Monetization Strategy, you will be the primary architect of Iterable’s economic engine. You aren't just managing a price list; you are defining how we capture value in a rapidly evolving MarTech ecosystem. You will sit at the intersection of Product, Sales, Finance, and Marketing to design and execute pricing and packaging strategies that drive sustainable growth, expand Net Revenue Retention (NRR), and align our success with our customers' success.

Responsibilities:

• • Strategic Vision: Lead the long-term monetization roadmap. You’ll evolve our current models from usage-based pricing toward value-based frameworks that reflect the power of our AI-driven orchestration.
  • Cross-Functional Leadership: Act as the "connective tissue" between Product (to price new features, and ensure our roadmap is optimized for capturing value), Marketing (to position value), and Sales (to ensure deal velocity).
  • Market Intelligence: Conduct deep-dive competitive analysis and buyer research to identify gaps in our current monetization strategy and capitalize on emerging market trends.
  • Packaging & Tiering: Design and optimize product bundles and editions that simplify the buying process for mid-market and enterprise customers alike.
  • Operational Excellence: Partner with RevOps to implement pricing changes within our systems (CPQ, billing) and develop the discounting frameworks and "guardrails" for the field.
  • Change Management: Lead the internal enablement for global sales teams, ensuring they can confidently articulate the "why" behind our pricing.

Qualifications:

• You have 10+ years of experience in SaaS monetization, management consulting, or strategic finance. You think in systems and understand the downstream impacts of a single pricing lever.
• You have direct experience in SaaS monetization, with a particular focus on monetizing AI
• You are comfortable navigating complex datasets to find the "signal" in the noise. You use data to prove your hypotheses about price elasticity and expansion paths.
• You can distill complex economic theories into simple, persuasive narratives for the Executive Leadership Team (ELT).
• You don't just want a seat at the table; you want to build the table. You enjoy creating processes where none existed.

Bonus Points

• Experience building and productionizing LLM based, agentic or autonomous systems that handle complex orchestration and evaluation.
• Experience establishing shared AI platforms or internal developer enablement capabilities
• Familiarity with analytics systems, experimentation workflows, or decisioning frameworks

Perks & Benefits:

• Paid parental leave
• Competitive salaries, meaningful equity, & 401(k) plan
• Medical, dental, vision, & life insurance
• Balance Days (additional paid holidays)
• Fertility & Adoption Assistance
• Paid Sabbatical
• Flexible PTO
• Monthly Employee Wellness allowance 
• Monthly Professional Development allowance 
• Pre-tax commuter benefits
• Complete laptop workstation

The US base salary range for this position at the start of employment is $172,000 - $260,000. Within this range, individual pay is determined by specific US work location, as well as additional factors, including job-related skills, experience, relevant education or training, and internal equity considerations.

Please note that the range listed above reflects only base salary. The total compensation package includes variable pay (where applicable), equity, plus a range of benefits, including medical, dental, vision, and financial. In addition, we offer perks such as generous stipends for health & fitness and learning & development, among others.

The Product Solutions Architecture (PSA) team acts as a technical multiplier across Datadog. PSAs are domain experts who partner with Field teams on complex customer use cases across pre- and post-sales engagements and scale their impact by producing reusable collateral, including reference architectures, technical guides, and enablement assets. By feeding real-world customer insights back to Datadog Product teams, PSAs help influence product roadmaps while accelerating adoption, usage, and long-term customer success.

Datadog’s LLM Observability product enables organizations to monitor, troubleshoot, and optimize large-scale LLM-powered applications with confidence, while meeting requirements around data privacy, compliance, and cost management. As a Product Solutions Architect, you will partner closely with Datadog customers and the LLM Observability product team to design architectures, implement best practices, and drive adoption of LLM observability across customer environments.

At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.

What You’ll Do:

• Serve as the in-house subject matter expert for Datadog’s LLM Observability product
• Partner with Field teams to provide hands-on technical and architectural guidance to enterprise customers adopting LLM Observability
• Create high-impact technical collateral, including reference architectures, technical guides, cookbooks, and documentation to enable Field teams and the broader customer community
• Build proofs of concept and small-scale deployments to validate solutions and reproduce real-world customer environments
• Act as a trusted advisor to Product Management by delivering actionable feedback informed by real-world field experience

Who You Are: 

• You bring a strong software engineering foundation, with hands-on experience building and operating LLM-powered applications in production environments, and are comfortable diving deep into codebases to understand architectural decisions, tradeoffs, and implementation details
• You are familiar with distributed systems and core observability concepts, such as tracing, metrics, and logging, and can translate those patterns into the emerging LLM observability domain, including LLM spans, evaluations, and prompt templates
• You have experience with languages such as Python and/or JavaScript/TypeScript
• You are comfortable operating in rapidly evolving, ambiguous technical domains
• You build deep context across teams and translate it into reusable, scalable solutions
• You take ownership from problem definition through implementation and measurable outcomes
• You are highly detail-oriented, particularly when working on architectures and customer-facing technical assets
• You bring strong listening and consultative skills and are experienced supporting customers in high-pressure, complex situations
• Able to sit up to 4 hours, traveling to and from client sites 
• Able to travel via auto, train, or air up to 40% of the time 

Bonus Points:

• Successful track record with 5+ years experience working as an Architect or Consultant 
• Experience using Datadog and/or other observability tools in an SRE or DevOps capacity
• Experience with LLM application evaluation and testing frameworks

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.

Benefits and Growth: 

• Best-in-breed onboarding
• Generous global benefits
• Intra-departmental mentor and buddy program for in-house networking
• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Continuous professional development, product training, and career pathing
• An inclusive company culture, able to join our Community Guilds and Inclusion Talks

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

Shopmonkey's vision is to help every shop thrive by equipping them with the tools they need to run and grow their business. Our cloud based all-in-one shop management software takes owners and technicians from quote to cashing out a satisfied customer. Our software has a modern and intuitive UI and our backend is powered by the latest technologies so our clients can focus on the things they do best. As a Senior ML Engineer at Shopmonkey, you will be a part of a globally distributed engineering team working closely with your product and design counterparts. You will have the chance to work on the frontier of ML modeling, data pipelines, MLOps, and agentic AI systems to meet real-world auto shop needs. Shopmonkey has the structured data, workflows, and operational maturity to deliver ML powered systems that are not only intelligent but trusted and useful. You’ll move fast to bring ML systems from discovery all the way through production, helping to shape the future of the automotive care experience. For any Bay area based candidates, this would be hybrid with 2-3 days/week office at our Morgan Hill, CA office for collaboration. 

What you will do:

• Design, build, and ship production-ready ML models across a range of problem spaces: regression, classification, clustering, ranking, and recommendation systems.
• Conduct end-to-end development of ML systems: data gathering, experimentation, feature engineering, model training, evaluation, deployment, and monitoring.
• Define and track model performance metrics, run A/B tests, and iterate based on real-world feedback.
• Help design and implement shared feature stores so that reusable features can serve multiple models consistently in both batch and real-time contexts.
• Work within a modern MLOps environment to ensure scalable and reliable deployment of models.
• Contribute to training infrastructure, model versioning, and CI/CD pipelines for ML workflows.
• Work closely with data scientists and data engineers to develop data driven solutions that are high impact for businesses.
• Translate complex ML workflows into digestible updates for cross-functional stakeholders.
• Contribute to backlog velocity by owning appropriate tickets and delivering high-impact work in a collaborative, fast-paced environment.
• Implement NLP and LLM-powered components for sentiment analysis, real-time conversation evaluation, and behavior optimization.
• Contribute to analytics and predictive features such as no-show prediction and sentiment dashboards.
• Help build and ship AI agents that help automate key auto-shop business processes.

We are looking for people who have:

• Minimum of 5+ years of industry experience in applied machine learning; advanced degrees (Master’s or PhD) may offset years of experience.
• Proven experience shipping models into production (not just proof-of-concepts or notebooks).
• Proficiency in Python; experience with ML frameworks like PyTorch or Tensorflow.
• Strong foundations in classical ML/DL. Including some of the following: regression, classification, clustering, ranking, feature engineering, model evaluation, and experimentation.
• Bachelor’s degree in a STEM field, or equivalent practical experience.
• Strong collaboration and communication skills—comfortable working with PMs, designers, engineers and other cross functional team members.

Nice to have:

Candidates should have some experience in one or more of the following areas.

• Understanding of MLOps principles: model versioning, orchestration, evaluation, monitoring, model serving, and CI/CD for ML. 
• Understanding of MLOps, and experience with modern tooling like MLFlow, DVC, Airflow, etc.
• Experience with LLMs and NLP frameworks (e.g., TensorFlow, Hugging Face, LangChain).
• Experience with/interest in LLM workflows and agentic workflows
• Cloud infrastructure experience, (e.g. GCP, AWS).
• Familiarity with vector databases (e.g. Pinecone, pgvector) and embedding-based retrieval or similarity search.
• Strong SQL skills for working with large-scale data.
• Experience designing or contributing to feature stores (e.g. Feast, VertexAI Feature Store, Tecton) for shared, reusable feature pipelines.

Bonus Points:

• Prior experience working at a high growth startup.
• Experience building consumer-facing agents in vertical SaaS, in the automotive industry (business or consumers).
• Background in data processing or real-time analytics.
• Experience with Snowflake or other large-scale data warehouse solutions.

In the United States, the range is typically a salary of $165,000 to $200,000 + bonus + equity + benefits. The range provided is Shopmonkey’s reasonable estimate of the base compensation for this role. The actual amount will be based on job-related and non-discriminatory factors such as location, experience, training, skills, and abilities. Consult with your Recruiter during the initial call to determine a more targeted range based on these job-related factors. In addition to this base compensation company stock options and benefits as outlined below are included.

The application window will be open until at least April 24, 2026 . This opportunity will remain online based on business needs which may be before or after the specified date.

This role is not eligible for immigration sponsorship.

This role is part of the Growth department on the Digital team. You'll collaborate with ad operations and growth specialists to deliver web, app, and media analytics to key stakeholders. The Growth team works across departments—including sales, marketing, brand, and product—to identify new opportunities and test strategies to drive revenue and improve the customer experience with GFiber’s products.

Role Description

As the Marketing Web Developer you will be the technical lead responsible for managing GFiber’s websites and integration points, supporting digital marketing and sales efforts. You’ll lead, organize, and manage program activities that drive business outcomes while developing systems to proactively identify improvements and drive future optimizations including change management and performance metrics. You'll oversee content management systems, A/B testing tools, and tracking implementations, ensuring smooth operations and optimal performance. Collaboration with cross-functional teams will be key in driving our analytics, marketing, and growth initiatives.

In this role, you'll:

• Engineer and maintain the GFiber web architecture, writing clean, scalable code to integrate marketing technology stacks and third-party services. 
• Implement and manage tools for content management, knowledge management, A/B testing, tracking, and services integration.
• Create technical design documents for new website features and integrations.
• Manage user access, roles, and responsibilities for web tools like Contentful, Optimizely, and KMS Lighthouse.
• Support change requests, issue management, and day-to-day updates related to website content and services, and also align with stakeholders on decisions and changing circumstances.

At a minimum we'd like you to have:

• Bachelor's degree in Digital Marketing, Computer Science, or related fields—or equivalent practical experience.
• 4 years' experience building high-traffic marketing websites and scalable web systems using React, Typescript and JavaScript.
• Experience with A/B testing tools (e.g. Optimizely, Optimize, Test and Target) and experiment configuration.
• Experience implementing and leveraging analytics, tracking and data warehouse platforms (e.g., Google Analytics 4, Google Tag Manager, BigQuery).

It's preferred if you have:

• Experience with headless Content Management Systems (e.g. Contentful, Sanity).
• Experience with ad-tech integrations and custom tracking pipelines for Google Ads and Campaign Manager, ensuring accurate reporting and data attribution for high-traffic marketing sites via API. 
• Experience with AI tools coding tools and LLM technologiesExperience using written and verbal communication to convey technical requirements to both technical and non-technical stakeholders.
• Experience with Python and back-end integrations to support large-scale consumer traffic.

The US base salary range for this full-time position is between $132,800 - $175,100 + bonus + cash award + benefits. As pay varies by location, your recruiter will share more about the specific salary range for your targeted location during the hiring process.

#LI-DNI

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.

About the role:

Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.

Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.

In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.

What you’ll do:

• Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
• Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
• Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
• Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
• Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
• Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
• Improve observability, reliability, security, and maintainability across ML infrastructure and services
• Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
• Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
• Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
• Get hands-on with customers at the most forward-leaning places in the Department of War

What we are looking for:

• 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
• 5+ years of experience with Docker and Kubernetes in production environments
• 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
• Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
• Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
• Practical experience deploying machine learning workloads on Kubernetes
• Experience managing clusters or workloads that use GPUs
• Strong understanding of Helm and Kubernetes deployment patterns
• Strong scripting or programming skills, preferably in Python
• Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
• Strong troubleshooting, systems thinking, and communication skills
• Ability to work independently and collaboratively in a fast-moving environment
• Ability to obtain and maintain a Top Secret clearance
• Ability to obtain Security+ certification within the first 90 days of employment

Highly preferred:

• Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
• Experience with secure and compliant deployment practices in regulated or government environments
• Experience with Kubernetes-based ML platforms such as Kubeflow
• Familiarity with service mesh technologies such as Istio
• Experience provisioning and debugging complex CI/CD systems
• Experience with infrastructure as code tools such as Terraform
• Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
• Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
• Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
• Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system

What success looks like:

• You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
• ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
• Model deployments become more secure, observable, and supportable across real-world mission environments
• The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership

Clearance Requirements:

• Ability to obtain and maintain a Top Secret clearance 

Work Type: 

• Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
• May require up to 40% travel
  

Salary Range: $150,000.00 - $200,000.00

What we will offer you:

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) and company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Annual budget for your tech/gadgets needs
• Monthly box of yummy snacks to eat while doing meaningful work
• Remote, hybrid, and flexible work options
• Team off-site in fun places!
• Generous Referral Bonuses
• And More!

Our Vision Statement: 

We bridge the gap between humans and data through radical transparency and our obsession with the mission. 

Our Customer Obsession: 

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there? 

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm. 

Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration. 

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.

About the role:

Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.

Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.

In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.

What you’ll do:

• Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
• Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
• Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
• Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
• Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
• Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
• Improve observability, reliability, security, and maintainability across ML infrastructure and services
• Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
• Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
• Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
• Get hands-on with customers at the most forward-leaning places in the Department of War

What we are looking for:

• 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
• 5+ years of experience with Docker and Kubernetes in production environments
• 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
• Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
• Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
• Practical experience deploying machine learning workloads on Kubernetes
• Experience managing clusters or workloads that use GPUs
• Strong understanding of Helm and Kubernetes deployment patterns
• Strong scripting or programming skills, preferably in Python
• Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
• Strong troubleshooting, systems thinking, and communication skills
• Ability to work independently and collaboratively in a fast-moving environment
• Ability to obtain and maintain a Top Secret clearance
• Ability to obtain Security+ certification within the first 90 days of employment

Highly preferred:

• Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
• Experience with secure and compliant deployment practices in regulated or government environments
• Experience with Kubernetes-based ML platforms such as Kubeflow
• Familiarity with service mesh technologies such as Istio
• Experience provisioning and debugging complex CI/CD systems
• Experience with infrastructure as code tools such as Terraform
• Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
• Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
• Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
• Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system

What success looks like:

• You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
• ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
• Model deployments become more secure, observable, and supportable across real-world mission environments
• The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership

Clearance Requirements:

• Ability to obtain and maintain a Top Secret clearance 

Work Type: 

• Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
• May require up to 40% travel
  

Salary Range: $150,000.00 - $200,000.00

What we will offer you:

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) and company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Annual budget for your tech/gadgets needs
• Monthly box of yummy snacks to eat while doing meaningful work
• Remote, hybrid, and flexible work options
• Team off-site in fun places!
• Generous Referral Bonuses
• And More!

Our Vision Statement: 

We bridge the gap between humans and data through radical transparency and our obsession with the mission. 

Our Customer Obsession: 

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there? 

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm. 

Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration. 

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.

About the role:

Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.

Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.

In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.

What you’ll do:

• Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
• Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
• Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
• Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
• Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
• Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
• Improve observability, reliability, security, and maintainability across ML infrastructure and services
• Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
• Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
• Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
• Get hands-on with customers at the most forward-leaning places in the Department of War

What we are looking for:

• 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
• 5+ years of experience with Docker and Kubernetes in production environments
• 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
• Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
• Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
• Practical experience deploying machine learning workloads on Kubernetes
• Experience managing clusters or workloads that use GPUs
• Strong understanding of Helm and Kubernetes deployment patterns
• Strong scripting or programming skills, preferably in Python
• Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
• Strong troubleshooting, systems thinking, and communication skills
• Ability to work independently and collaboratively in a fast-moving environment
• Ability to obtain and maintain a Top Secret clearance
• Ability to obtain Security+ certification within the first 90 days of employment

Highly preferred:

• Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
• Experience with secure and compliant deployment practices in regulated or government environments
• Experience with Kubernetes-based ML platforms such as Kubeflow
• Familiarity with service mesh technologies such as Istio
• Experience provisioning and debugging complex CI/CD systems
• Experience with infrastructure as code tools such as Terraform
• Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
• Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
• Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
• Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system

What success looks like:

• You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
• ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
• Model deployments become more secure, observable, and supportable across real-world mission environments
• The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership

Clearance Requirements:

• Ability to obtain and maintain a Top Secret clearance 

Work Type: 

• Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
• May require up to 40% travel
  

Salary Range: $150,000.00 - $200,000.00

What we will offer you:

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) and company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Annual budget for your tech/gadgets needs
• Monthly box of yummy snacks to eat while doing meaningful work
• Remote, hybrid, and flexible work options
• Team off-site in fun places!
• Generous Referral Bonuses
• And More!

Our Vision Statement: 

We bridge the gap between humans and data through radical transparency and our obsession with the mission. 

Our Customer Obsession: 

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there? 

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm. 

Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration. 

Who we are:

At Focused, we move quickly to deliver quality software that achieves client outcomes and meets their customer’s needs. We strategically partner with our clients to leverage our expertise in design and software, while our clients bring their own domain expertise. We work with a variety of clients from different industries, collaborating as we get new products to market, modernizing legacy systems, or helping teams learn the skills they need to be successful.   

Our values:

• Listen first • We are experts in product practices but life long learners in the domain of our customers. We research, collaborate, and understand. 
• Learn why • We ask questions and talk to users to understand problem spaces, objectives, and goals, which allows us to deeply invest and drive towards the outcomes of our clients. 
• Love your craft • We love diving into a variety of domains and solving problems.  We take pride in delivering value, in communicating progress, and guiding our clients to success.

At Focused, our Engineers are both practitioners and experts in their craft. This role would play a crucial role in shaping and implementing engineering best practices and ensuring the successful delivery of complex software projects. With clients, we develop trust and influence - we are unintimidated and unintimidating. With colleagues, we set the standard for how we deliver success for clients.

What would you be doing?

• Build AI-enabled applications leveraging LangChain and LLMs to deliver meaningful, production-ready outcomes for clients.
• Deep expertise in LangChain, LangGraph and LangSmith.
• Lead teams through end-to-end delivery across the stack, from backend services to modern web UIs.
• Pair program daily with teammates and clients to share knowledge, improve code quality, and grow together.
• Practice TDD and continuous refactoring to ensure code is reliable, maintainable, and understandable.
• Guide architecture decisions to support scalability, observability, and performance.
• Collaborate closely with designers, product managers, and stakeholders to continuously deliver valuable software.
• Coach developers on the team through pairing, mentoring, and modeling healthy engineering culture.
• Influence technical direction beyond the team, working across client orgs and Focused’s internal practices to share lessons, shape approaches, and raise the collective bar.
• Stay curious through experimenting with new patterns in the GenAI space, share what works (and what doesn’t), and help evolve how we build AI-powered software.

We are excited about you, because you:

• You’re a hands-on, full stack engineer with a strong track record of delivering software in collaborative, agile environments.
• You’ve worked with LangChain (or similar agentic frameworks), and understand how to architect AI-native systems responsibly and effectively.
• You believe that code quality matters, and that TDD and pairing help build better systems and stronger teams.
• You’ve worked across multiple languages or frameworks (e.g., Python, Node, Java, React, Next.js) and are pragmatic about tool selection.
• You’re excited about what’s happening in the AI space but stay focused on delivering value.
• You have experience navigating complex organizations, building bridges across functions, and helping teams adopt modern development practices.
• You’re as comfortable in the code as you are in a client meeting and can translate technical risks and wins into language anyone can understand.
• You love to share what you’re learning and make the team around you better.

If you had worked at Focused over the last 3 months you may have:

• Paired with a teammate to build a document Q&A system using LangChain and OpenAI APIs
• Helped design an architecture that integrates LLM agents into a legacy enterprise workflow
• Refactored a flaky test suite to support continuous delivery with confidence
• Built and deployed a full stack GenAI MVP with a React frontend and FastAPI backend
• Facilitated an architecture spike to evaluate vector database options for semantic search
• Contributed a new section to our internal AI playbook
• Helped write this job req

What to know before you apply: 

• This role will require being in the Denver office three days per week and up to 20% travel within the United States.
• Focused is unable to sponsor or take over sponsorship of the employment Visa process at this time.
• The Denver base salary range for this role is $120,000 - $175,000.

About Pushpay

Pushpay exists to serve the Church. We build software that helps faith communities manage generosity, connect members, and focus on what matters most: ministry. As we deepen our commitment to Catholic parishes and dioceses, we are looking for a Senior Product Manager who brings both world-class product craft and an authentic understanding of Catholic parish life - someone who sees this work as more than a job.

About the Role

As Senior Product Manager for the Catholic Market, you will be Pushpay’s dedicated product voice for how Catholic parishes and dioceses actually operate. You will not own a standalone Catholic product - Pushpay’s portfolio serves both Catholic and Protestant communities through shared infrastructure. What you will own is the Catholic lens: identifying, prioritizing, and championing the features and workflows that make the portfolio meaningfully better for Catholic users.

This role lives at the intersection of deep domain knowledge and cross-functional influence. Success here is not about controlling the roadmap - it’s about building the credibility, relationships, and clarity of argument needed to ensure Catholic needs are consistently represented in portfolio decisions made by teams with broader mandates.

Named as one of BuiltIn ‘Best Places to Work’ in Seattle, Denver and Dallas for 2025; ranked number 10 by Seattle Business Magazine in the ‘Washington’s 100 Best Companies to Work For’ list in the large companies category for 2024; named as a 2025 'Best Places to Work for Women' by Best Companies Group.

Benefits and Compensation

We have a passion for making all employees feel supported. In addition to having a genuine interest in helping you do your best work and drive your career, we offer:

• 100% employer-paid premiums for Medical HDHP Plan, Dental, and Vision for employee
• 70% employer-paid premiums for Medical PPO Plan for employees, and Medical, Dental, and Vision for dependents
• 401K match
• Hybrid work model - 3 days in the office / 2 days remote each week: COS, CO & Allen, TX area
• Remote: All other approved locations
• 12 paid Company Holidays
• 2 paid Volunteer Time Off days
• 20 days PTO to start, increases with tenure and seniority.
• Paid parental and adoption leave
• Compensation Range:
  • $106,729 - $123,332, depending on location.
  • $112,500 - $130,000, COS, CO & Allen, TX:

Compensation ranges are determined by role and location. The range displayed on each job posting reflects the pay range for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

The following states are approved as remote work locations for this position: AR, AZ, CA, CO, FL, GA, IA, IL, IN, MD, MI, MN, MO, NC, OH, OK, PA, SC, TN, TX, VA, WA - All other states are not in consideration for this role at this time.

What You'll Do

• Be the Catholic Expert: Apply deep Catholic operational knowledge to product decisions from day one. Use targeted discovery with parish and diocese stakeholders to validate direction and surface nuance across Catholic traditions, liturgical timing, and stewardship models, then translate that back into the portfolio with speed and clarity.
• Own the Catholic Product Narrative: Build and maintain a clear, credible product story for Catholic diocese leaders and board-level stakeholders, one that connects Pushpay’s portfolio investments directly to Catholic outcomes and priorities.
• Navigate and Influence the Portfolio: Work across product domains, Engineering, and UX to ensure Catholic-specific needs are understood, prioritized, and delivered, including where AI capabilities can reduce friction or surface insights for Catholic users. Your effectiveness depends on building trust, making a clear business case, and knowing when to escalate.
• Responsible AI: Champion a "Human-in-the-Loop" approach to AI, surfacing insights and reducing administrative burden without replacing pastoral judgment or the personal relationships central to parish life. Ensure all AI features align with data privacy standards and Catholic social teaching.
• Catholic Market Advocacy: Help Sales, Customer Success, and Product Marketing explain the value of Pushpay’s product to Catholic stakeholders, translating the what and why into language that resonates with parish and diocese leaders. Show up externally at key Catholic events and diocese conversations as a credible product voice for the Catholic market.
• Measure What Matters: Define and track adoption, NPS, and retention signals within the Catholic segment. Use data to build the internal case for prioritization, know when a delivered feature is actually working, and iterate based on real feedback from parishes and dioceses.

How We'll Measure Success

In your first 12 months:

• Time Savings: Quantified improvement in time-on-task for parish administrators using delivered features.
• Catholic Segment NPS: Measurable improvement in NPS scores within Catholic accounts, with qualitative signal via CSat that Catholic parishes are satisfied with how the software actually works.
• Adoption & Retention: Growth in the percentage of Catholic accounts actively engaging with delivered features, with an eye on churn as a lagging indicator of whether the product is delivering real value over time.
• Portfolio Influence: Evidence that Catholic-specific requirements are being incorporated across product domains, measured by feature delivery and stakeholder feedback.
• Roadmap Clarity: A Catholic product narrative that diocese leaders and board-level stakeholders find credible, useful, and consistently reflective of where Pushpay is headed.

What You'll Bring

• Catholic Domain Fluency (Required): Parish and diocese life from the inside. Liturgical calendar, stewardship models, sacramental workflows. A personal connection to or deep respect for the Catholic faith is essential.
• 5+ Years in B2B SaaS Product Management: End-to-end ownership from discovery through adoption. Complex workflows or financial data preferred. Faith-based context a plus.
• Influence Without Authority: You drive outcomes across teams you don’t control, through expertise and trust, not org chart position.
• AI Product Fluency: You know what AI can and cannot do in a ministry context, can define requirements for LLM-based features, and recognize when a human touch matters more than automation.
• Operational & Technical Fluency: Comfortable with APIs and integrations. You understand why being the source of truth for parish data matters.
• Communication That Moves People: Clear point of view. Adapts on evidence. Doesn’t hedge.

Pushpay is committed to equal opportunity. We value and embrace diversity and inclusion of all Team Members. Pushpay uses E-Verify to confirm employment eligibility. Head to our career page to learn more.

If you have a disability under the Americans with Disabilities Act or similar law, or you require religious accommodation, and you wish to discuss potential accommodations related to applying for employment at Pushpay, please contact peopleteam@pushpay.com.

About Pushpay

Pushpay helps organizations and communities come to gather & stay connected, strengthening community, connection, and belonging through our suite of mobile apps, management software, and giving technology. Our 550 Pushpay teammates support 10,000+ customers as they drive social good, and we’re honored to have processed over $15 billion in charitable giving. We’re growing fast, including some exciting acquisitions in recent years, and we need driven talent. Join Pushpay and grow with us!

**Applications will be taken on an ongoing basis.

#LI-TS1 #LI-Remote #LI-Hybrid

Position Overview:

We are looking for a Senior Machine Learning Engineer to build the core Machine Learning foundations that power Nova’s agentic experiences. This role focuses on applied Machine Learning in production environments: retrieval systems, evaluation frameworks, and model integration layers that make AI features reliable, scalable, and repeatable. You will design and implement the underlying components that support rich, intelligent interactions in the Iterable platform.

You will work closely with backend, frontend, and product teams to shape how Machine Learning is introduced and maintained across the company. The work blends hands-on engineering with system design, and is ideal for someone who can drive complex efforts independently, make practical architectural decisions, and collaborate in a fast-moving, cross-functional product environment.

Responsibilities:

• Design and build Machine Learning platform components that support agentic systems, including retrieval pipelines, indexing strategies, and model integration layers.
• Introduce and operationalize RAG use cases, from data sourcing and embedding generation to runtime retrieval patterns.
• Develop generalized evaluation frameworks for LLM- and agent-based features, including offline metrics, golden datasets, and continuous monitoring.
• Implement abstractions, tooling, and reusable patterns that enable other teams to build ML- and LLM-powered experiences efficiently.
• Partner with backend engineers to productionize ML features with strong reliability, observability, and performance characteristics.
• Prototype applied ML solutions to validate feasibility before investing in full builds.
• Ensure secure, robust handling of data used in ML workflows and retrieval operations.
• Collaborate with product, design, and engineering to align ML system design with user experience and product goals.
• Contribute to iterative improvements of the Nova agent framework, including workflows built with Mastra and TypeScript.

Qualifications:

• 5+ years experience as a Machine Learning Engineer or similar role focused on production systems.
• Strong engineering skills with Python or TypeScript, including experience building ML workflows in frameworks like Mastra or comparable agent/LLM toolkits.
• Experience with retrieval systems, vector databases, search technologies, or RAG architectures.
• Prior work integrating ML or LLM-powered features into production applications.
• Understanding of ML evaluation techniques, experimentation design, and failure analysis.
• Ability to lead complex projects, make practical trade-offs, and work independently in areas of ambiguity.
• Strong communication and collaboration skills in a distributed environment.

Bonus Points

• Experience building ML or LLM platforms, tooling, or developer-facing frameworks.
• Prior work with embeddings, search–ranking systems, or advanced RAG architectures.
• Familiarity with event-driven systems or streaming architectures.
• Experience with model observability, performance monitoring, or proactive regression detection.
• Background in personalization, recommendations, or applied NLP.
• Experience working in remote-first engineering teams.

Perks & Benefits:

• Competitive salaries, meaningful equity, & 401(k) plan
• Medical, dental, vision, & life insurance
• Balance Days (additional paid holidays)
• Fertility & Adoption Assistance
• Paid Sabbatical
• Flexible PTO
• Monthly Employee Wellness allowance 
• Monthly Professional Development allowance 
• Pre-tax commuter benefits
• Complete laptop workstation

The US base salary range for this position at the start of employment is $133,500 - $212,000. Within this range, individual pay is determined by specific US work location, as well as additional factors, including job-related skills, experience, relevant education or training, and internal equity considerations.

Please note that the range listed above reflects only base salary. The total compensation package includes variable pay (where applicable), equity, plus a range of benefits, including medical, dental, vision, and financial. In addition, we offer perks such as generous stipends for health & fitness and learning & development, among others.

Position Overview:

We are looking for a Senior Full-Stack Engineer to join the team building Nova’s agentic experiences within the Iterable platform. This team is responsible for the full end-to-end development of conversational and agent-driven workflows, including the interaction surfaces, orchestration layers, and core platform integrations that make these experiences seamless and intuitive for users.

In this role, you will work across the stack to build both frontend and backend components that bring agentic capabilities to life. You will collaborate closely with design, product, and engineering partners to deliver high-quality, user-centered features. This position is well-suited for someone who enjoys solving complex product and technical problems, can navigate ambiguity, and brings a strong sense of ownership to their work.

Responsibilities:

• Build and iterate on the frontend and backend components that power agentic user experiences.
• Collaborate with design and product teams to create intuitive, conversational interaction patterns.
• Work across the stack to integrate frontend workflows with backend services, platform APIs, and internal tooling.
• Contribute to the evolution of underlying frameworks, including agent workflows and supporting infrastructure.
• Participate in architectural and design discussions to ensure solutions are scalable, maintainable, and aligned with product goals.
• Write high-quality, well-tested code and help refine engineering standards and best practices.
• Debug production issues, improve observability, and contribute to system reliability.
• Partner with other engineers to deliver features from concept to production, including technical design, implementation, testing, and rollout.

Qualifications:

• 5+ years of experience building full-stack applications in production environments.
• Strong proficiency with TypeScript and experience working across both frontend and backend systems.
• Experience with modern frontend frameworks (React preferred) and backend application development.
• Ability to design clean, maintainable APIs and internal interfaces.
• Strong collaboration skills and comfort working closely with product and design.
• Ability to operate independently, manage ambiguity, and drive work to completion.
• Interest in building intelligent, agent-driven experiences, even without prior LLM experience.

Bonus Points

• Experience contributing to or building internal frameworks or developer tooling.
• Familiarity with agent frameworks, agentic patterns, or LLM tool-calling workflows.
• Strong intuition for UI/UX quality in interactive interfaces.
• Experience with observability, performance tuning, or production debugging at scale.
• Experience with event-driven or distributed systems.
• Prior experience working in remote-first engineering environments.

Perks & Benefits:

• Competitive salaries, meaningful equity, & 401(k) plan
• Medical, dental, vision, & life insurance
• Balance Days (additional paid holidays)
• Fertility & Adoption Assistance
• Paid Sabbatical
• Flexible PTO
• Monthly Employee Wellness allowance 
• Monthly Professional Development allowance 
• Pre-tax commuter benefits
• Complete laptop workstation

The US base salary range for this position at the start of employment is $133,500 - $212,000. Within this range, individual pay is determined by specific US work location, as well as additional factors, including job-related skills, experience, relevant education or training, and internal equity considerations.

Please note that the range listed above reflects only base salary. The total compensation package includes variable pay (where applicable), equity, plus a range of benefits, including medical, dental, vision, and financial. In addition, we offer perks such as generous stipends for health & fitness and learning & development, among others.

How you will make an impact:

We are looking for an Engineering Manager to lead the team responsible for building agentic experiences and integrating AI-powered capabilities into the core Iterable application. This team owns the application-facing development that turns emerging AI capabilities into reliable, usable product features.

In this role, you will guide a group of frontend, backend, and applied engineers working on conversational workflows, orchestration layers, and AI-enabled product surfaces. You will balance people leadership with strong technical judgment, helping the team deliver high-quality features while navigating ambiguity and evolving requirements in a fast-moving product area. This role sits within the broader Nova initiative and plays a key part in shaping how intelligent experiences appear across the Iterable platform.

One of our core values is a growth mindset and Iterable is a company where everyone can grow. If this is a role that excites you, please do apply as we value applicants for the skills they bring beyond a job description.

How You Will Make a Difference:

• Lead and support a team of engineers building agentic and AI-enabled product experiences.
• Partner closely with Product, Design, and Data Science leadership to translate AI capabilities into scalable, user-facing experiences.
• Guide the design and implementation of agent workflows, orchestration logic, and application integrations.
• Ensure AI-powered features are reliable, observable, secure, and ready for production use.
• Drive execution across multiple initiatives, balancing short-term delivery with sustainable technical direction.
• Foster strong engineering practices around code quality, testing, documentation, and iterative delivery.
• Coach and mentor engineers, supporting career growth and healthy team dynamics.
• Collaborate with other engineering and data teams to align on interfaces, dependencies, and shared goals.
• Contribute to hiring and onboarding as the team grows.

We Are Looking for People Who:

• Have at least 5 years of hands-on software development experience.
• Have at least 3 years of experience managing and growing software engineering teams.
• Strong background in application or platform engineering, ideally in a SaaS environment.
• Experience leading teams that integrate AI or ML-powered capabilities into production systems.
• Comfort operating at the intersection of product, platform, and data science teams.
• Strong technical judgment across system design, APIs, distributed systems, and developer workflows.
• Experience working with modern backend and frontend stacks.
• Ability to navigate ambiguity, make pragmatic trade-offs, and drive execution across multiple initiatives.
• Excellent communication skills and ability to align technical work with business and product goals.

Bonus Points:

• Experience leading teams building agentic or LLM-powered product experiences.
• Familiarity with agent frameworks such as Mastra or similar orchestration tools.
• Prior work on decisioning engines, rules engines, or real-time personalization systems.
• Experience collaborating closely with Data Science and ML teams on production integrations.
• Background in marketing technology or customer engagement platforms.
• Experience scaling teams and systems in a remote-first environment.

Perks & Benefits:

• Competitive salaries, meaningful equity, & 401(k) plan
• Medical, dental, vision, & life insurance
• Balance Days (additional paid holidays)
• Fertility & Adoption Assistance
• Paid Sabbatical
• Flexible PTO
• Monthly Employee Wellness allowance 
• Monthly Professional Development allowance 
• Pre-tax commuter benefits
• Complete laptop workstation

The US base salary range for this position at the start of employment is $156,000 - $242,000. Within this range, individual pay is determined by specific US work location, as well as additional factors, including job-related skills, experience, relevant education or training, and internal equity considerations.

Please note that the range listed above reflects only base salary. The total compensation package includes variable pay (where applicable), equity, plus a range of benefits, including medical, dental, vision, and financial. In addition, we offer perks such as generous stipends for health & fitness and learning & development, among others.

Who we are:

At Focused, we move quickly to deliver quality software that achieves client outcomes and meets their customer’s needs. We strategically partner with our clients to leverage our expertise in design and software, while our clients bring their own domain expertise. We work with a variety of clients from different industries, collaborating as we get new products to market, modernizing legacy systems, or helping teams learn the skills they need to be successful.   

Our values:

• Listen first • We are experts in product practices but life long learners in the domain of our customers. We research, collaborate, and understand. 
• Learn why • We ask questions and talk to users to understand problem spaces, objectives, and goals, which allows us to deeply invest and drive towards the outcomes of our clients. 
• Love your craft • We love diving into a variety of domains and solving problems.  We take pride in delivering value, in communicating progress, and guiding our clients to success.

At Focused, our Engineers are both practitioners and experts in their craft. This role would play a crucial role in shaping and implementing engineering best practices and ensuring the successful delivery of complex software projects. With clients, we develop trust and influence - we are unintimidated and unintimidating. With colleagues, we set the standard for how we deliver success for clients.

What would you be doing?

• Build AI-enabled applications leveraging LangChain and LLMs to deliver meaningful, production-ready outcomes for clients.
• Deep expertise in LangChain, LangGraph and LangSmith
• Lead teams through end-to-end delivery across the stack, from backend services to modern web UIs.
• Pair program daily with teammates and clients to share knowledge, improve code quality, and grow together.
• Practice TDD and continuous refactoring to ensure code is reliable, maintainable, and understandable.
• Guide architecture decisions to support scalability, observability, and performance.
• Collaborate closely with designers, product managers, and stakeholders to continuously deliver valuable software.
• Coach developers on the team through pairing, mentoring, and modeling healthy engineering culture.
• Influence technical direction beyond the team, working across client orgs and Focused’s internal practices to share lessons, shape approaches, and raise the collective bar.
• Stay curious through experimenting with new patterns in the GenAI space, share what works (and what doesn’t), and help evolve how we build AI-powered software.

We are excited about you, because you:

• You’re a hands-on, full stack engineer with a strong track record of delivering software in collaborative, agile environments.
• You’ve worked with LangChain (or similar agentic frameworks), and understand how to architect AI-native systems responsibly and effectively.
• You have experience leading engineering teams and feel confident mentoring and supporting other developers.
• You believe that code quality matters, and that TDD and pairing help build better systems and stronger teams.
• You’ve worked across multiple languages or frameworks (e.g., Python, Node, Java, React, Next.js) and are pragmatic about tool selection.
• You’re excited about what’s happening in the AI space but stay focused on delivering value.
• You have experience navigating complex organizations, building bridges across functions, and helping teams adopt modern development practices.
• You’re as comfortable in the code as you are in a client meeting and can translate technical risks and wins into language anyone can understand.
• You love to share what you’re learning and make the team around you better.

If you had worked at Focused over the last 3 months you may have:

• Paired with a teammate to build a document Q&A system using LangChain and OpenAI APIs
• Helped design an architecture that integrates LLM agents into a legacy enterprise workflow
• Refactored a flaky test suite to support continuous delivery with confidence
• Mentored a junior dev through their first pairing and TDD session
• Built and deployed a full stack GenAI MVP with a React frontend and FastAPI backend
• Facilitated an architecture spike to evaluate vector database options for semantic search
• Contributed a new section to our internal AI playbook
• Helped write this job req

What to know before you apply: 

• This role will require being in the Denver office three days per week and up to 20% travel within the United States.
• Focused is unable to sponsor or take over sponsorship of the employment Visa process at this time.
• The Denver base salary range for this role is $175,000 - $250,000.