What you'll be doing:

Client Partnership & Implementation

• Own and manage an enterprise client portfolio as primary technical advisor
• Deliver seamless implementations from kickoff through go-live, coordinating internal teams and ensuring timely deployment
• Develop deep knowledge of each client's goals and translate them into actionable plans with measurable results
• Engage clients regularly via Zoom, email, phone, and on-site visits to strengthen relationships and ensure alignment

Adoption & Value Realization

• Drive product adoption with measurable improvements in usage metrics and client health scores
• Conduct technical assessments of API implementations and lead quarterly optimization sessions
• Guide clients on product integrations and troubleshooting in collaboration with Implementation Engineer and Support
• Serve as the first technical point of contact for enterprise clients during implementation and post–go-live, owning technical triage and driving resolution with Implementation and Support.
• Educate clients on best practices to maximize value from Symmetry's solutions

Client Health & Retention

• Monitor client health scores, usage metrics, and interaction to identify risks early and implement mitigation plans
• Provide prompt, professional responses to inquiries ensuring fast resolution and strong confidence
• Support renewal readiness and risk mitigation in partnership with Account Manager

Operational Excellence

• Identify process improvements that reduce implementation time and increase team capacity
• Leverage AI tools and automation to streamline reporting, communication, and coordination
• Maintain thorough documentation in CRM and ticketing systems
• Collaborate with Sales, Product, Engineering, and Support to address issues and drive continuous improvement

Experience & Requirements:

Required Background:

• Bachelor's degree or equivalent combination of education and experience
• 5+ years in Client Success, Account Management, or Implementation Management in B2B SaaS
• Proven track record managing enterprise portfolios and guiding retention, adoption, and satisfaction
• Experience project managing complex software implementations from kickoff through go-live
• Technical aptitude to understand API/SDK integrations, conduct assessments, and troubleshoot issues
• Track record leveraging data and metrics to drive client outcomes and operational efficiency
• Experience in payroll, HR tech, or compliance technology strongly preferred

Core Skills & Attributes:

• Proven technical acumen with ability to translate capabilities into business value
• Extraordinary relationship-building skills to advise enterprise stakeholders on technical and business outcomes
• Outstanding communication skills with ability to simplify complex technical concepts
• Proactive, ownership-driven mindset with accountability for results
• Keen analytical and critical thinking with comfort in qualitative and quantitative analysis
• Great organizational and project management skills managing multiple priorities
• Client-first orientation committed to delivering measurable value
• Collaborative team player thriving in cross-functional partnerships
• Demonstrated ability to leverage AI and automation for efficiency
• Continuous learning mindset staying current on product innovations

Technology Experience:

• Comprehension of API/SDK architecture, RESTful APIs, and integration concepts
• Ability to read API documentation and guide clients through technical implementation
• Experience with API testing tools (Postman or similar) for client troubleshooting
• Proficiency with CRM systems (NetSuite, Salesforce, or comparable)
• Experience with customer success platforms (Catalyst, Gainsight, ChurnZero, or similar)
• Working knowledge of project management and ticketing systems (Jira, Asana, Zendesk, or comparable)
• Proficiency with Google Workspace (Slides and Sheets including formulas and data analysis)
• Experience with virtual meeting platforms (Zoom, Microsoft Teams, or similar)
• Experience with generative AI tools (ChatGPT, Gemini, or comparable) and building AI agents
• Project management certification (PMP, CAPM, Google Project Management) is a plus
• API fundamentals certification (Postman Student Expert or equivalent) is a plus

Compensation Details

Our cash compensation amount for this role is targeted at $121,000/yr- $149,000/yr in Scottsdale. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above. 

YOUR MISSION

AI-assisted work is the biggest force multiplier available to a company at True Anomaly's stage. It accelerates how we build, how we deliver, and how we scale. We are investing in AI as a core operating capability, not a side experiment, and this role exists to help make that investment real. 

As a Senior AI Platform Engineer, you will build the infrastructure, tooling, and integrations that put AI directly into the hands and workflows of every team across the company. This is not a research role. It is a building role. You will ship capabilities that engineers, program managers, operators, and business teams use every day to move faster and produce better work. 

The scope is broad by design. You may be standing up on-premises GPU infrastructure one week, building connectors between AI models and internal systems the next, and developing a custom application for a specific business workflow after that. You will contribute to platform-level technical decisions about AI providers, tools, and architectures. You will also help build and deliver AI training and enablement for the company, including office hours, brown bags, and hands-on resources. 

This role reports to the Chief Security Officer and works across every function. You will have meaningful autonomy, direct visibility to executive leadership, and the opportunity to shape how a fast-growing defense technology company operates with AI. 

RESPONSIBILITIES

• Build and maintain AI platform infrastructure: API integrations, model access pipelines, system connectors (MCP, tool use), and on-premises compute environments as needed 
• Develop custom AI-powered applications, workflows, and integrations that connect frontier models to internal systems such as project management, documentation, communications, and operational tools 
• Contribute to technical evaluation and selection of AI providers, tools, and platforms, helping inform build-vs-buy decisions based on capability, compliance requirements, and speed to value 
• Help design and deliver AI training and enablement programs for the company, including hands-on workshops, office hours, documentation, and shared resources that build real fluency across teams 
• Partner with engineering, security, and IT teams to ensure AI deployments meet government security and compliance requirements across data classification levels 
• Stay current with the rapidly evolving AI landscape and surface new models, tools, and capabilities that could accelerate the company 

QUALIFICATIONS

• Software engineering background with experience building and shipping production systems, ideally in Python, TypeScript, or similar languages common in AI/ML tooling 
• Hands-on experience with large language model APIs, including prompt engineering, tool use, retrieval-augmented generation (RAG), or agent frameworks 
• Experience building integrations between software systems using APIs, webhooks, data pipelines, or authentication flows 
• Ability to work across a broad technical surface area, moving between infrastructure, application development, and platform work as priorities require 
• Good communication skills and ability to explain technical AI concepts to non-technical audiences through training, documentation, or direct support 
• Comfortable operating with autonomy in a fast-paced environment where priorities shift and the playbook is being written in real time 
• Ability to maintain or obtain TS//SCI clearance 

PREFERRED SKILLS AND EXPERIENCE

• Experience deploying AI or ML systems in government, defense, or regulated environments with security and compliance constraints 
• Familiarity with government cloud environments (AWS GovCloud, Azure Government) and authorization frameworks (FedRAMP, IL4/IL5) 
• Experience with on-premises GPU infrastructure (NVIDIA, CUDA) for model hosting or fine-tuning 
• Background in developer tooling, platform engineering, or internal tools teams at high-growth technology companies 
• Experience building knowledge retrieval systems, embedding pipelines, or enterprise search infrastructure 
• Currently hold or have previously held a U.S. security clearance at any level 

COMPENSATION

• Base Salary: $170,000-$275,000
• Equity + Benefits including Health, Dental, Vision, HRA/HSA options, PTO and paid holidays, 401K, Parental Leave 

Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, location, and experience. 

ADDITIONAL REQUIREMENTS

• Work Location—while we observe a hybrid work environment, you will need to be onsite as the business needs require. On an average week, you can expect to spend at least 3 days per week in office.
• Work environment—the work environment; temperature, noise level, inside or outside, or other factors that will affect the person's working conditions while performing the job.
• Physical demands—the physical demands of the job, including bending, sitting, lifting and driving.

This position will be open until it is successfully filled. To submit your application, please follow the directions below. #LI-Hybrid

YOUR MISSION

AI-assisted work is the biggest force multiplier available to a company at True Anomaly's stage. It accelerates how we build, how we deliver, and how we scale. We are investing in AI as a core operating capability, not a side experiment, and this role exists to make that investment real. 

As a Staff AI Platform Engineer, you will be one of the first hires to build the infrastructure, tooling, and integrations that put AI directly into the hands and workflows of every team across the company. This is not a research role. It is a building role. You will ship capabilities that engineers, program managers, operators, and business teams use every day to move faster and produce better work. 

The scope is broad by design. You may be standing up on-premises GPU infrastructure one week, building connectors between AI models and internal systems the next, and developing a custom application for a specific business workflow after that. You will make platform-level technical decisions about which AI providers, tools, and architectures to adopt. You will also own AI training and enablement for the company, running office hours, brown bags, and building the resources that help people get real value from these tools. 

This role reports to the Chief Security Officer and works across every function. You will have significant autonomy, direct access to executive leadership, and the opportunity to define how a fast-growing defense technology company operates with AI. 

RESPONSIBILITIES

• Build and maintain AI platform infrastructure: API integrations, model access pipelines, system connectors (MCP, tool use), and on-premises compute environments as needed 
• Develop custom AI-powered applications, workflows, and integrations that connect frontier models to internal systems such as project management, documentation, communications, and operational tools 
• Own technical evaluation and selection of AI providers, tools, and platforms, making build-vs-buy decisions based on capability, compliance requirements, and speed to value 
• Design and deliver AI training and enablement programs for the company, including hands-on workshops, office hours, documentation, and shared resources that help teams build real fluency 
• Partner with engineering, security, and IT teams to ensure AI deployments meet government security and compliance requirements across data classification levels 
• Stay current with the rapidly evolving AI landscape and bring informed recommendations on new models, tools, and capabilities that could accelerate the company 

QUALIFICATIONS

• Strong software engineering background with experience building and shipping production systems, ideally in Python, TypeScript, or similar languages common in AI/ML tooling 
• Hands-on experience with large language model APIs, including prompt engineering, tool use, retrieval-augmented generation (RAG), and agent frameworks 
• Experience building integrations between AI systems and enterprise platforms (APIs, webhooks, data pipelines, authentication flows) 
• Demonstrated ability to work across a broad technical surface area, context-switching between infrastructure, application development, and platform architecture 
• Strong communication skills and ability to translate technical AI concepts for non-technical audiences through training, documentation, and direct support 
• Self-directed and comfortable operating with high autonomy in a fast-paced environment where priorities shift and the playbook is being written in real time 
• Ability to maintain or obtain TS//SCI clearance 

PREFERRED SKILLS AND EXPERIENCE

• Experience deploying AI or ML systems in government, defense, or regulated environments with security and compliance constraints 
• Familiarity with government cloud environments (AWS GovCloud, Azure Government) and authorization frameworks (FedRAMP, IL4/IL5) 
• Experience with on-premises GPU infrastructure (NVIDIA, CUDA) for model hosting or fine-tuning 
• Background in developer tooling, platform engineering, or internal tools teams at high-growth technology companies 
• Experience building knowledge retrieval systems, embedding pipelines, or enterprise search infrastructure 
• Currently hold or have previously held a U.S. security clearance at any level 

COMPENSATION

• Base Salary: $200,000 - $330,000
• Equity + Benefits including Health, Dental, Vision, HRA/HSA options, PTO and paid holidays, 401K, Parental Leave 

Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, location, and experience. 

ADDITIONAL REQUIREMENTS

• Work Location—while we observe a hybrid work environment, you will need to be onsite as the business needs require. On an average week, you can expect to spend at least 3 days per week in office.
• Work environment—the work environment; temperature, noise level, inside or outside, or other factors that will affect the person's working conditions while performing the job.
• Physical demands—the physical demands of the job, including bending, sitting, lifting and driving.

This position will be open until it is successfully filled. To submit your application, please follow the directions below. #LI-Hybrid

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.

Your Mission 

We are seeking a rare combination of disciplines: an experienced Sr. Compliance Engineer with deep AI Subject Matter Expertise (SME) and export compliance background to join our Governance, Risk, and Compliance (GRC) team. This role is responsible for building, implementing, and sustaining the organizational compliance posture across key regulatory and security frameworks — with a primary emphasis on RMF (NIST 800-53 Rev. 5 + Classified Overlays), CMMC Level 3, NIST 800-171 Rev. 3, EAR/ITAR cyber regulations, and — critically - the governance, risk management, and compliance controls surrounding AI/ML systems and large language models (LLMs) deployed across the enterprise. 

As AI becomes embedded in True Anomaly's operations, mission systems, and products, this role serves as the organizational authority on how AI capabilities are adopted, audited, and controlled responsibly. You will architect and operationalize compliance checkpoints and governance gates within LLM pipelines, evaluate AI vendors and platforms (including OpenAI, Anthropic Claude, and others) against classified and unclassified compliance requirements, and ensure AI-driven workflows satisfy both regulatory obligations and internal risk tolerance. 

The ideal candidate brings deep GRC knowledge, hands-on AI/LLM engineering fluency, and the ability to engage credibly with compliance assessors, government partners, and internal AI/ML engineering teams alike. 

Responsibilities 

Compliance Program Execution 

• Lead and support compliance assessment readiness across key organizational frameworks including NIST SP 800-171 Rev. 2 and 3, CMMC Level 3, NIST SP 800-53 Rev. 5, and the NIST Cybersecurity Framework (CSF). 

• Provide direction on cybersecurity readiness to address EAR and ITAR-related controls and requirements. 

• Drive CMMC readiness activities across the organization, including scoping, gap analysis, control implementation validation, evidence collection, and pre-assessment preparation. 

• Review, maintain, and mature System Security Plans (SSPs) to accurately reflect organizational control implementations, system boundaries, and operational practices — including AI/ML system boundaries and data flows. 

• Manage Plans of Actions and Milestones (POA&Ms), tracking open findings to resolution, communicating status to GRC leadership, and coordinating remediation efforts across responsible teams. 

• Conduct internal compliance audits and control effectiveness reviews to ensure ongoing adherence to applicable frameworks and to surface emerging gaps before external assessments. 

• Maintain audit-ready evidence repositories and documentation packages, ensuring traceability between controls, evidence, and framework requirements. 

AI Governance, Risk & Compliance (AI-GRC) 

• Serve as the organizational AI compliance SME — the primary authority on how AI/LLM systems (including OpenAI GPT models, Anthropic Claude, open-source models, and internally developed models) are evaluated, onboarded, and continuously governed within True Anomaly's compliance boundaries. 

• Design, implement, and maintain compliance checkpoints and enforcement gates within LLM pipelines, including:  

• Input/output filtering and content policy enforcement layers 

• Prompt injection detection and mitigation controls 

• Data classification guardrails to prevent CUI, ITAR-controlled, or classified data from flowing into non-authorized AI systems or endpoints 

• Automated audit logging of AI interactions for traceability and incident investigation 

• Model access control and role-based permissions within AI platforms 

• Conduct AI-specific risk assessments, including evaluation of AI vendor data handling practices, model training data provenance, and third-party AI API security postures against NIST AI RMF, NIST SP 800-53 AI overlays, and internal standards. 

• Develop and enforce an AI System Acceptable Use Policy and supporting standards that govern how employees and systems interact with LLMs, including permissible data inputs, output handling, human-in-the-loop requirements, and escalation procedures. 

• Evaluate proposed AI/ML use cases for regulatory risk (EAR/ITAR, CMMC, data privacy) and provide compliance go/no-go determinations with documented rationale. 

• Collaborate with AI/ML engineers and DevSecOps teams to integrate compliance gates into CI/CD pipelines and MLOps workflows, ensuring model changes and prompt changes undergo review before production deployment. 

• Maintain an AI system inventory, tracking all deployed models, APIs, integrations, and associated risk and compliance status. 

• Monitor emerging AI regulatory developments (e.g., EO 14110, NIST AI RMF, DoD AI Ethics Principles, EU AI Act implications for U.S. defense partners) and assess organizational impact. 

Cross-Functional Compliance Enablement 

• Serve as a primary GRC team resource for compliance questions, control guidance, and framework interpretation across engineering, IT, operations, legal, and security teams. 

• Partner with IT and security operations teams to verify that technical controls — including access management, logging, configuration baselines, and incident response procedures — meet CMMC and NIST requirements at an organizational level. 

• Partner with AI/ML engineers, data scientists, and product teams to embed compliance thinking into AI system design, model selection, and deployment architecture. 

• Collaborate with the Enterprise Risk Manager and broader GRC leadership to ensure compliance findings — including AI-specific risks — are reflected in the enterprise risk register and remediation priorities. 

• Support the development of compliance training and awareness materials, including AI-specific training that builds organizational understanding of responsible AI use, LLM risk, and CMMC obligations. 

• Coordinate with external assessors, third-party auditors, and government partners during assessment engagements, serving as a knowledgeable point of contact for evidence walkthroughs and control discussions. 

Qualifications 

• 7+ years of experience in IT security compliance, GRC, or a closely related discipline, with direct ownership of compliance program activities. 

• Demonstrated expertise in NIST SP 800-171, CMMC (Level 2 or 3), and NIST SP 800-53, with hands-on experience conducting gap assessments, implementing controls, and preparing organizations for external audits. 

• Extensive, hands-on experience with AI/LLM systems, including practical knowledge of platforms such as OpenAI (GPT-4/o-series), Anthropic Claude, Meta Llama, Microsoft Azure OpenAI Service, and/or comparable commercial and open-source LLM ecosystems. 

• Demonstrated ability to design, implement, and operationalize compliance controls within LLM pipelines, including guardrail layers, content filtering, audit logging hooks, and data classification enforcement. 

• Working knowledge of AI security risks, including prompt injection, jailbreaking, data exfiltration via LLM outputs, model inversion, and supply chain risks associated with third-party AI APIs. 

• Familiarity with NIST AI Risk Management Framework (AI RMF) and its application to enterprise and defense AI deployments. 

• Strong understanding of SSP development and maintenance, POA&M management, and audit evidence lifecycle practices in an organizational (non-product) compliance context. 

• Proven experience developing and operationalizing information security policies, standards, and procedures across a multi-disciplinary organization. 

• Strong communication skills with the ability to explain compliance requirements — including AI risk concepts — clearly to both technical practitioners and non-technical business stakeholders. 

• Highly organized, with demonstrated ability to manage multiple concurrent compliance workstreams and deadlines in a fast-paced environment. 

• Active or ability to obtain SECRET or TS/SCI security clearance. 

• Must be a U.S. citizen, lawful permanent resident, or protected individual per ITAR requirements (8 U.S.C. 1324b(a)(3)). 

Preferred Qualifications 

• Strong EAR/ITAR background as it pertains to cybersecurity, AI-generated outputs, and policy development. 

• J.D. focusing on technology law, export compliance (EAR and ITAR), AI regulation, or cyber law. 

• Experience building MLOps or AI DevSecOps pipelines with integrated compliance gates, including automated policy enforcement, prompt review workflows, or model change management processes. 

• Hands-on experience with AI safety and alignment tooling (e.g., LangChain guardrails, NeMo Guardrails, Azure Content Safety, OpenAI Moderation API, Anthropic Constitutional AI/policy layer configurations). 

• Experience evaluating AI vendor agreements and data processing agreements against DoD/CMMC/ITAR data handling requirements. 

• Familiarity with DoD AI Ethics Principles, Responsible AI (RAI) frameworks, and emerging federal AI governance requirements (e.g., EO 14110, OMB AI guidance). 

• Industry certifications such as:  

• Certified Information Systems Auditor (CISA) 

• Certified in Risk and Information Systems Control (CRISC) 

• Certified Information Systems Security Professional (CISSP) 

• CMMC Registered Practitioner (RP) or Certified Professional (CP) 

• CompTIA Security+ or equivalent 

• AWS/Azure AI or Security certifications 

• Background in startup, aerospace, defense technology, or SaaS environments operating under DoD compliance obligations. 

• Familiarity with cloud environments — particularly Azure Government, AWS GovCloud, or Azure OpenAI Government deployments — as they relate to organizational control implementation and AI boundary scoping. 

• Experience coordinating with C/3PAOs or supporting CMMC assessments. 

• Working knowledge of DFARS 252.204-7012, ITAR, and supply chain compliance obligations. 

• Familiarity with Agile/Scrum environments and hybrid project delivery models. 

Compensation 

• Base Salary: Denver - $145,000 to $195,000, Long Beach - $150,000 to $205,000, Washington, DC - $150,000 to $205,000 

• Equity + Benefits including Health, Dental, Vision, HRA/HSA options, PTO and paid holidays, 401K, Parental Leave 

Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, location, and experience. 

Additional Requirements 

• Work Location: Successful candidates will be located near Denver, CO, Long Beach, CA, or Washington D.C. While we observe a hybrid work environment, some work must be done on site. #LI-Onsite

• Work Environment: Standard office setting, working at a desk or in a production factory environment. 

• Physical Demands: May include frequent standing, sitting, walking, bending, and lifting or carrying items up to 20 lbs. 

This position will be open until it is successfully filled. 

To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR), you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State. 

We value diversity of experience, knowledge, backgrounds, and perspectives and harness these qualities to create extraordinary impact. True Anomaly is committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, maternity or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know. 

What You Will Do and Learn 

We are hiring an AI Training & Enablement Lead to drive firm-wide adoption of our AI platform and agentic tools. In this role, you are responsible for end-to-end execution, not just strategy. You will design, create, and deliver the training programs, enablement materials, release communications, and change management plans that help 700+ consultants integrate AI into their daily work. 

You will own the full lifecycle of user enablement: from onboarding new users, to managing release rollouts, to measuring adoption and identifying friction points. You’ll have access to support resources, while playing a leading role in building and delivering impactful solutions. 

In this role, you can expect to: 

Training Program Design & Delivery 

• Build and maintain role-based training curricula for different personas (consultants, architects, engagement leads, practice leaders) aligned to the AI platform's capabilities and governance requirements. 

• Create hands-on workshops, quick-start guides, video walkthroughs, prompt libraries, and reference materials that consultants can use in the flow of work. 

• Facilitate live training sessions (virtual and in-person) for platform onboarding, new feature releases, and advanced use-case enablement. 

• Develop and manage an internal certification or proficiency program to track and incentivize AI skill development. 

Release Management & User Enablement 

• Own the user-facing release process: coordinate with the AI platform vendor and internal technical teams to translate product updates into clear, actionable enablement content. 

• Manage release notes, feature announcements, and "what's new" communications for each platform update. 

• Build and maintain a centralized enablement hub (knowledge base, FAQ, resource library) that serves as the single source of truth for all AI-related guidance. 

• Establish feedback loops with end users to surface adoption blockers, training gaps, and feature requests. 

Change Management & Communications 

• Design and execute change management strategy for the AI platform rollout, including stakeholder mapping, resistance planning, and leadership alignment. 

• Draft internal communications (emails, Teams updates, town hall talking points) that build excitement and reduce friction around new AI capabilities. 

• Identify and activate AI Champions across practices to scale peer-to-peer learning and create organic adoption momentum. 

• Partner with practice leaders and HR to integrate AI enablement into performance reviews, career development, and onboarding for new hires. 

Adoption Measurement & Continuous Improvement 

• Define and track adoption KPIs: active user rates, feature utilization, training completion, satisfaction scores, and time-to-value metrics. 

• Conduct regular pulse surveys and user interviews to assess enablement effectiveness and identify areas for improvement. 

• Report adoption progress and risks to leadership on a regular cadence, providing actionable recommendations. 

• Continuously iterate on training content and delivery methods based on data and user feedback. 

Skills & Experience: 

Required 

• 5-8+ years of experience in training, enablement, change management, or L&D, with at least 2 years focused on technology or platform adoption. 

• Proven ability to design and build training programs from the ground up, including curriculum development, content creation, resource design, and hands-on delivery. 

• Strong facilitation skills: you are comfortable leading workshops for groups ranging from 10 to 200 people, both virtually and in person. 

• Proven ability to translate complex technical concepts into accessible, engaging content for non-technical audiences. 

• Outstanding written and verbal communication skills, with a proven ability to craft clear, concise internal communications that effectively engage audiences. 

• Experience working in professional services, consulting, or technology firms. 

• Comfortable working in fast-paced environments with evolving priorities, and able to navigate ambiguity without a predefined playbook. 

Preferred 

• Prior experience with change management frameworks (Prosci, ADKAR, or equivalent). Certification. 

• Hands-on experience with generative AI tools (ChatGPT, Claude, Copilot, or similar). You do not need to be an engineer, but you should be a confident, daily user. 

• Experience managing enablement for SaaS platform rollouts (Salesforce, Anaplan, ServiceNow, or similar enterprise tools). 

• Familiarity with instructional design principles and e-learning authoring tools (Articulate, Loom, Camtasia, or equivalent). 

• Background in or exposure to consulting delivery models, T&M billing, and the dynamics of utilization-based businesses. 

• Experience building and activating champion or ambassador networks within large organizations. 

About the Team

At Dice, we believe that delivering an exceptional candidate experience — the end-to-end journey a job seeker takes to discover, evaluate, and land their next role — is essential to the success of our platform. This team plays a critical role in building the next generation of that experience, contributing across a modern full-stack environment. We value engineers who are curious, collaborative, and committed to making an impact for thousands of job seekers.

We are an AI-native team. We actively use AI coding assistants (e.g., Claude Code, Codex, Gemini CLI) to accelerate development, sharpen code quality, and focus our energy on higher-impact engineering work.

About the Role

As a Senior Software Engineer at Dice, you’ll contribute to the design, development, and delivery of high-impact product features in a modern, cloud-native stack. As a senior engineer you’ll be expected to provide technical leadership within the team by driving architectural decisions, mentoring teammates, and helping maintain a high standard of quality and maintainability. You’ll collaborate cross-functionally with Product, Design, and Data partners to align on outcomes and advocate for sound technical solutions.

Being AI-native is central to how we work. We expect engineers in this role to go beyond using AI as a simple chat assistant, embracing tools like Claude Code as core parts of the development workflow to increase productivity such as automating repetitive tasks by generating skills and leveraging subagents, and apply best practices through prompt engineering to get the most out of the AI tools we use at every stage of the software lifecycle.

Why We’re Hiring for This Role

As we scale and modernize our platform, we’re looking for experienced senior engineers who can take ownership of complex systems, communicate effectively with stakeholders, deploy AI-powered features, and contribute to product and architectural decisions. This role is ideal for someone who enjoys working across the stack, solving real user problems, working with AI, and influencing both code and culture.

In the Short Term, You Will:

Ramp Up on Systems and Codebases

Gain familiarity with our applications, services, tools, and infrastructure. Develop an understanding of how your team’s work fits into the broader product and architecture.

Establish Technical Ownership

Take responsibility for features and systems, provide thoughtful code reviews, and contribute to team design discussions. You’ll be trusted to make solid technical decisions and defend them clearly when needed while staying open to feedback.

Collaborate and Align

Work closely with engineers, product managers, designers, and stakeholders to align on priorities and deliver incremental value. Help improve the team's planning and execution rhythm.

In the Long Term, You Will:

Drive Technical Excellence

Help evolve our systems through well-designed, scalable AI architecture. Reduce tech debt, improve performance, and contribute to shared engineering standards.

Mentor and Elevate the Team

The Senior Software Engineer at Dice plays a key role in mentoring peers, reviewing designs, and helping grow the technical capabilities of those around you.

Deliver Meaningful Business Impact

Own end-to-end delivery of AI-powered product features that support business goals and enhance user experience. Influence the roadmap by advocating for technical investments that align with long-term value.

What You Bring to the Team:

• Proven experience building and deploying production-grade applications with a track record of delivering value through practical, maintainable solutions
• Strong technical skills and experience in cloud-based technologies
• Track record of development and deployment of ML and AI features into a Production environment.
• Ability to navigate ambiguity, make sound decisions, and adapt to changing priorities
• A collaborative, team-first mindset — you know the best outcomes come from working well together, and you actively contribute to a supportive, inclusive team environment
• Technical depth and experience that allows you to lead design discussions, break down complex tasks into meaningful deliverables, and ensure a high standard of engineering quality
• A sense of urgency, accountability, and ownership, you take pride in your work and team achievements.
• Strong communication, problem-solving, and collaboration skills, with the confidence to advocate for ideas while being open to alternative perspectives

Required:

• Proven experience building and maintaining business-critical applications using Node.js and TypeScript in a production setting
• Hands-on experience developing scalable, maintainable RESTful and GraphQL services in production environments
• Working knowledge of container-based technologies (Docker, Fargate, Kubernetes, or other)
• Experience with front-end frameworks such as NextJS, React, or Angular
• Demonstrated experience building highly available applications on AWS infrastructure
• Experience implementing and working with CI/CD pipelines to support automated testing and deployments
• Ability to apply quality best practices and implement automated testing using tools such as Playwright
• Solid understanding of architectural patterns (event-driven, serverless, SOA, and others)
• Practical understanding of how to implement traditional Machine Learning models and LLMs in production, including knowledge of model selection criteria and architectural trade-offs
• Hands-on experience deploying LLM-powered features into production, such as simple LLM API calls, RAG (Retrieval-Augmented Generation) systems, Vector Stores, and MCP Servers
• Familiarity with AI/ML tooling such as LangChain, LangGraph, LangSmith, Vercel AI SDK, LiteLLM, or equivalent frameworks

Preferred:

• Understanding of different programming paradigms such as OOP and Functional
• Experience with highly available, highly scalable SaaS applications
• Working knowledge of logging and observability best practices
• Familiarity with DevOps principles and the ability to work closely with platform teams
• Knowledge of performance tuning, cost optimization, or scalability in a cloud-native environment
• Comfort navigating ambiguity to define and implement technical solutions
• Experience collaborating with cross-functional partners (Product, Design, Data)
• Experience designing and deploying Agentic features or autonomous AI Agents in a production environment
• Experience with LLM evaluation techniques (e.g., LLMs-as-judges), prompt engineering, and context engineering
• Familiarity with LLM guardrails and safeguards, monitoring, and observability practices for production AI systems
• Experience working as an AI-native engineer — including creating agent skill files, configuring and orchestrating subagents, or building custom AI tooling to accelerate engineering workflows

NOTE: This job description is not intended to be an all-inclusive list of the duties and responsibilities of the job described, nor are they intended to be such a listing of the skills and abilities required to do the job. Rather, they are intended only to describe the general nature of the job as of the date this job description was prepared. Management reserves the right to modify this job in order to meet business needs. 

The Role

Ping Identity is seeking a technically strong, hands-on AI Automation Engineer to join the Data & AI team within the Office of the CIO. This is a builder role — you won't just configure platforms, you'll write code, design custom agent architectures, and deliver production-grade AI automation that drives measurable business impact across the enterprise.

As our second AI Automation Engineer, you'll work alongside our existing AI Automation Engineer and report to the Director of AI & Data. Where the first hire focuses on business process design and low-code/no-code delivery, you will own the programmatic side of our agent stack — building custom agents in Databricks, developing integrations and connectors, and tackling automation challenges that require real engineering depth.

This role is for someone who is equally comfortable in a Jupyter notebook and a stakeholder meeting — someone who can translate a complex business problem into a working, governed solution.

What You'll Do

• Build and deploy custom AI agents using Python and Databricks, including complex, multi-step agents that go beyond what low-code platforms can handle.
• Design and implement integrations between Glean, Databricks, and enterprise systems (Salesforce, Jira, Freshservice, etc.) — including custom connectors and data pipelines that feed our AI stack.
• Own the technical delivery of high-code agent use cases in our AI operating model — from requirements through deployment, monitoring, and iteration.
• Collaborate with the AI Automation Engineer (business-focused) to divide and conquer the agent backlog: they own the canvas/low-code layer, you own the programmatic layer.
• Partner with data engineers to ensure agents have access to clean, reliable, well-governed data via Databricks Unity Catalog and our lakehouse architecture.
• Support the agent governance process — writing technical specs, participating in governance reviews, and ensuring custom agents meet security, PII, and compliance requirements before production deployment.
• Contribute to the agent framework and tooling used by the broader AI team — prompt templates, evaluation harnesses, reusable agent components, and CI/CD pipelines for agent deployment.
• Triage and resolve technical escalations from the AI platform support queue that require engineering-level investigation.

What You'll Bring

• 3–5 years of hands-on software engineering or data engineering experience, with a track record of delivering production systems — not just prototypes.
• Proficiency in Python — you write clean, maintainable code, are comfortable working in data and AI engineering contexts, and actively use coding assistants (e.g., GitHub Copilot, Cursor, or similar) as part of your development workflow.
• Experience building on Databricks — specifically with AgentBricks and building custom agents on the Databricks platform. You know your way around notebooks, Delta Lake, and production-grade agent deployment.
• Demonstrated proficiency in building AI agents — you've designed, built, and shipped production agents (Glean canvas, LangChain, LlamaIndex, or similar), and you understand the engineering tradeoffs involved (retrieval, tool use, evaluation, latency, cost). This is a core expectation of the role, not a nice-to-have.
• Proficiency with agentic coding frameworks (e.g., DSPy, LangChain, CrewAI, or similar) — you've used these in production contexts, not just tutorials, and know how to evaluate the right tool for the job.
• Familiarity with agent tracing and monitoring concepts — you understand how to observe agent behavior in production (e.g., trace logs, token usage, latency, failure modes) and know why it matters for reliability and governance.
• API and integration experience — you can read API docs, build connectors, and wire systems together without hand-holding.
• Strong communication skills — you can explain technical architecture to non-technical stakeholders and write documentation people actually use.
• Collaborative and cross-functional — comfortable working across IT, data, and business teams in a fast-moving environment.

You Have an Advantage If

• You've played a hands-on technical role in top-down, enterprise AI transformation initiatives — where the work was tied to clear business outcomes, P&L targets, or measurable productivity gains, not just engineering deliverables.
• You have hands-on experience with Glean — building agents, configuring connectors, or working with the Glean API.
• You've built production-grade agentic workflows incorporating RAG, tool use, orchestration layers (LangGraph, CrewAI, custom), or multi-agent patterns.
• You have experience with Salesforce integrations or have built agents that take actions inside enterprise SaaS platforms.
• You're familiar with MLOps or LLMOps practices — model evaluation, prompt versioning, observability, and deployment pipelines.
• You have a background in data engineering and are comfortable with SQL, Delta tables, and Unity Catalog governance patterns.
• You've contributed to AI governance or responsible AI programs — specifically around agent safety, PII handling, and access control.
• You've worked in a B2B SaaS or enterprise software environment and understand how to build solutions that are supportable at scale.

Base Salary Range: $130,766 - $150,000

In accordance with Colorado's Equal Pay for Equal Work Act (SB 19-085), the approximate compensation range for this role in Colorado is listed above. Final compensation will be determined by various factors, such as knowledge, skills, and abilities.

About the Role:

We're looking for a Legal AI Engineer for a fixed engagement to build foundational legal team AI infrastructure. You'll design and stand up these systems, document them thoroughly, and hand them off to the team in a state where they can be maintained and iterated on internally.

You'll provide services to a legal team that is already building its own AI tooling and infrastructure through Claude. Your engagement will be with the Senior Manager of Legal Contracting Operations & AI Systems. Your project will be to add the technical depth that turns promising experiments into robust, shared systems, and to deliver a coherent stack of tools and workflows.

During this engagement, you'll design workflows that are fast, measurable, and safe based on specifications from legal, legal ops, and cross-functional stakeholders. You'll leave behind documented systems and run books so the team can maintain and evolve what you've built. This engagement is equal parts legal infrastructure + applied AI, ideal for a hybrid legal/technical practitioner who can translate legal work into scalable systems and then make those systems real.

Here’s what you’ll do day-to-day during this engagement:

• Connect the AI Stack
  • Take the skills, workflows, and dashboards that individual team members have already built in Claude and package them into shared, maintainable assets the whole team can use.
  • Wire together current AI tooling — build MCP integrations so data flows where it's needed without manual handoffs; engage with Gusto's AIT team on connections where native integrations don't exist.
  • Further operationalize AI tools and integrations as agreed upon.
• Build a Legal Repository
  • Stand up a structured, queryable knowledge layer fed by the team's existing research, positions, precedents, and playbooks — one that can be searched by any team member, can be invoked by automated workflows, and continuously ingests new information as the team works in the tool.
• Implement AI Workflows
  • Working from priorities set by legal ops and attorneys, implement AI-assisted workflows for the team's highest-volume use cases — likely including contract first-pass review, matter intake and routing,  litigation operations to enable intake, routing and response drafting for subpoenas, demand letters and notices and prompt libraries for recurring legal tasks.
• Document and Hand Off
  • Deliver a maintenance runbook for every system built and train designated team members on administration, so nothing requires the contractor to maintain it after the engagement ends. Establish adoption baselines so the team can measure progress and know what to iterate on next.

Here’s what we're looking for:

• Hands-on experience building and shipping AI-assisted workflows — not evaluating tools or writing specs, but actually standing systems up. Be ready to walk through something you built from prompt to production.
• Direct, working proficiency with Claude or comparable LLMs: prompt engineering, agentic workflows, and iterating on outputs until they're reliable. This is the core technical skill for everything we're building.
• Integration experience — you've wired tools together using APIs, MCPs, or similar patterns, and you know what breaks and why. Coordinating with engineering or IT teams to scope and execute those connections is second nature to you.
• Comfort operating in ambiguity. You can take a business problem and context from attorneys or legal ops — not a technical spec — and turn it into a working system. You know how to ask the right questions, fill in gaps with judgment, and move forward.
• Comfort working within internal technology governance processes. You know how to communicate with an IT or AI team on tool approvals, data access, and security reviews — and you don't try to go around them. You build within the guardrails, and you help the team understand why those guardrails matter.
• Bonus: Experience working alongside attorneys: you understand contracting workflows, matter intake, research cycles, and how legal teams make decisions.

Compensation will be $150/hr, approximately 20 hours per week, commensurate with experience and expertise. This is a 3-month engagement.

Where we Work

Udemy is a global company headquartered in San Francisco, with additional U.S. offices in Denver and Austin, and international hubs in Australia, India, Ireland, Mexico, and Türkiye. 

About your skills

• Communication & Stakeholder Management – Ability to articulate technical concepts to both technical and non-technical audiences, including customers, sales teams, and internal stakeholders.

• Collaboration & Cross-Functional Coordination – Works effectively across sales, customer success, engineering, and product teams to drive successful customer implementations.

• Adaptability & Fast Learning – Thrives in a fast-paced environment, quickly learning new technologies and adjusting to evolving business and customer needs.
   

About the role

We are looking for a Solution Engineer to partner with our sales teams in engaging our top enterprise customers. This role is responsible for helping customers map the Udemy platform to their business outcomes, guiding them through discovery conversations, and delivering compelling presentations to audiences ranging from small executive groups to large-scale rooms of 100+ stakeholders.

This is not a programming role. Instead, it requires the ability to tell a story, uncover the “why” behind customer needs, and translate those insights into meaningful value with Udemy’s platform in a solution consulting manner.

What you'll be doing

• Partner with Account Executives on strategic accounts to lead discovery, understand customer goals, and identify how Udemy can drive measurable outcomes.

• Deliver compelling presentations and demos that resonate with diverse audiences, from frontline managers to C-level executives.

• Ask insightful discovery questions to uncover root challenges and the "why" behind a customer’s initiative.

• Translate business challenges into a tailored Udemy solution narrative.

• Serve as the trusted advisor on Udemy’s learning solutions, guiding prospects and customers on best practices.

• Participate in workshops, webinars, and events as a thought leader to showcase the value of Udemy to larger audiences.

• Collaborate cross-functionally with product, marketing, and customer success teams to ensure feedback loops from the field.

• Support RFPs/RFIs by providing clear, value-focused responses aligned to customer objectives.

• Proof of Concepts: Develop and handle effective Proof of Concepts (PoCs) for executives and decision-makers.

• Understanding of sales process/ methodology (MEDDPICC etc.)

What Success Looks Like

• You consistently uncover the real business drivers behind customer interest in Udemy.

• You deliver high-impact presentations that inspire confidence and action.

• You help close deals by mapping Udemy’s capabilities to customer priorities.

• Customers view you as a trusted advisor who understands both their industry challenges and how Udemy can solve them.

• You become an expert on understanding the Udemy technology stack

What you'll have

• 4+ years in a pre-sales, solution engineering, solution consulting, or similar role at a SaaS or enterprise software company.

• Exceptional presentation skills; comfortable presenting to executive audiences and large groups (100+ people).

• Strong discovery skills — ability to uncover, clarify, and articulate business drivers.

• Proven ability to craft compelling stories that connect customer needs to platform value.

• Strong business acumen and ability to connect technology to measurable business outcomes.

• Experience partnering closely with enterprise sales teams.

• Excellent communication, relationship-building, and influencing skills.

• Experience with AI prompt engineering and foundational AI agent configuration is required, with the expectation that candidates will actively deploy these capabilities to extend presales capacity and improve deal-cycle efficiency
   

Nice to Have

• Experience in learning technology, HR tech, or related SaaS solutions.

• Familiarity with enterprise learning and development challenges.

Posting Date: 3/23/2026
Application Window: We anticipate the application window will be open until April 13th, 2026. Based on business needs, this opportunity may remain posted beyond or closed before the anticipated application window.

Where we Work

Udemy is a global company headquartered in San Francisco, with additional U.S. offices in Denver and Austin, and international hubs in Australia, India, Ireland, Mexico, and Türkiye. 

About your skills

• Communication & Stakeholder Management – Ability to articulate technical concepts to both technical and non-technical audiences, including customers, sales teams, and internal stakeholders.

• Collaboration & Cross-Functional Coordination – Works effectively across sales, customer success, engineering, and product teams to drive successful customer implementations.

• Adaptability & Fast Learning – Thrives in a fast-paced environment, quickly learning new technologies and adjusting to evolving business and customer needs.
   

About the role

We are looking for a Solution Engineer to partner with our sales teams in engaging our top enterprise customers. This role is responsible for helping customers map the Udemy platform to their business outcomes, guiding them through discovery conversations, and delivering compelling presentations to audiences ranging from small executive groups to large-scale rooms of 100+ stakeholders.

This is not a programming role. Instead, it requires the ability to tell a story, uncover the “why” behind customer needs, and translate those insights into meaningful value with Udemy’s platform in a solution consulting manner.

What you'll be doing

• Partner with Account Executives on strategic accounts to lead discovery, understand customer goals, and identify how Udemy can drive measurable outcomes.

• Deliver compelling presentations and demos that resonate with diverse audiences, from frontline managers to C-level executives.

• Ask insightful discovery questions to uncover root challenges and the "why" behind a customer’s initiative.

• Translate business challenges into a tailored Udemy solution narrative.

• Serve as the trusted advisor on Udemy’s learning solutions, guiding prospects and customers on best practices.

• Participate in workshops, webinars, and events as a thought leader to showcase the value of Udemy to larger audiences.

• Collaborate cross-functionally with product, marketing, and customer success teams to ensure feedback loops from the field.

• Support RFPs/RFIs by providing clear, value-focused responses aligned to customer objectives.

• Proof of Concepts: Develop and handle effective Proof of Concepts (PoCs) for executives and decision-makers.

• Understanding of sales process/ methodology (MEDDPICC etc.)

What Success Looks Like

• You consistently uncover the real business drivers behind customer interest in Udemy.

• You deliver high-impact presentations that inspire confidence and action.

• You help close deals by mapping Udemy’s capabilities to customer priorities.

• Customers view you as a trusted advisor who understands both their industry challenges and how Udemy can solve them.

• You become an expert on understanding the Udemy technology stack

What you'll have

• 4+ years in a pre-sales, solution engineering, solution consulting, or similar role at a SaaS or enterprise software company.

• Exceptional presentation skills; comfortable presenting to executive audiences and large groups (100+ people).

• Strong discovery skills — ability to uncover, clarify, and articulate business drivers.

• Proven ability to craft compelling stories that connect customer needs to platform value.

• Strong business acumen and ability to connect technology to measurable business outcomes.

• Experience partnering closely with enterprise sales teams.

• Excellent communication, relationship-building, and influencing skills.

• Experience with AI prompt engineering and foundational AI agent configuration is required, with the expectation that candidates will actively deploy these capabilities to extend presales capacity and improve deal-cycle efficiency
   

Nice to Have

• Experience in learning technology, HR tech, or related SaaS solutions.

• Familiarity with enterprise learning and development challenges.

Posting Date: 3/30/2026
Application Window: We anticipate the application window will be open until April 13th, 2026. Based on business needs, this opportunity may remain posted beyond or closed before the anticipated application window.

About the Team

At Dice, we believe that delivering an exceptional candidate experience — the end-to-end journey a job seeker takes to discover, evaluate, and land their next role — is essential to the success of our platform. This team plays a critical role in building the next generation of that experience, contributing across a modern full-stack environment. We value engineers who are curious, collaborative, and committed to making an impact for thousands of job seekers.

We are an AI-native team. We actively use AI coding assistants (e.g., Claude Code, Codex, Gemini CLI) to accelerate development, sharpen code quality, and focus our energy on higher-impact engineering work.

About the Role

As a Software Engineer at Dice, you’ll contribute to the design, development, and delivery of high-impact product features in a modern, cloud-native stack. As a Software Engineer, you’ll be expected to provide technical support within the team by adhering to architectural decisions, working collaboratively teammates, and helping maintain a high standard of quality and maintainability. You’ll contribute cross-functionally with Product, Design, and Data partners to achieve ongoing outcomes and implement sound technical solutions.

Being AI-native is central to how we work. We expect engineers in this role to go beyond using AI as a simple chat assistant, embracing tools like Claude Code as core parts of the development workflow to increase productivity such as automating repetitive tasks by generating skills and leveraging subagents, and apply best practices through prompt engineering to get the most out of the AI tools we use at every stage of the software lifecycle.

Why We’re Hiring for This Role

As we scale and modernize our platform, we’re looking for engineers who can take ownership of complex systems, communicate effectively with collaborators and team members, deploy AI-powered features, and contribute to product and architectural decisions. This role is ideal for someone who enjoys working across the stack, solving real user problems, working with AI, and influencing both code and culture.

In the Short Term, You Will:

Ramp Up on Systems and Codebases

Gain familiarity with our applications, services, tools, and infrastructure. Develop an understanding of how your team’s work fits into the broader product and architecture.

Establish Technical Ownership

Take responsibility for features and systems, provide thoughtful code reviews, and contribute to team design discussions. You’ll be trusted to make solid technical decisions and defend them clearly when needed while staying open to feedback.

Collaborate and Align

Work closely with engineers, product managers, designers, and stakeholders to align on priorities and deliver incremental value. Help improve the team's planning and execution rhythm.

In the Long Term, You Will:

Drive Technical Excellence

Help evolve our systems through well-designed, scalable architecture. Reduce tech debt, improve performance, and contribute to shared engineering standards.

Deliver Meaningful Business Impact

Own end-to-end delivery of product features that support business goals and enhance user experience. Influence the roadmap by advocating for technical investments that align with long-term value.

What You Bring to the Team:

• Proven experience building and deploying production-grade applications with a track record of delivering value through practical, maintainable solutions
• Strong technical skills and experience in cloud-based technologies
• Ability to navigate ambiguity, make sound decisions, and adapt to changing priorities
• A collaborative, team-first mindset — you know the best outcomes come from working well together, and you actively contribute to a supportive, inclusive team environment
• Technical depth and experience that allows you to contribute to design discussions, assist in breaking down complex tasks into meaningful deliverables, and ensure a high standard of engineering quality
• A sense of urgency, accountability, and ownership, you take pride in your work and team achievements.
• Strong communication, problem-solving, and collaboration skills, with the confidence to advocate for ideas while being open to alternative perspectives

Required:

• Proven experience building and maintaining business-critical applications using Node.js and TypeScript in a production setting
• Hands-on experience developing scalable, maintainable RESTful APIs in production environments
• Experience with front-end frameworks such as NextJS or React
• Demonstrated experience building highly available applications on AWS infrastructure
• Experience implementing and working with CI/CD pipelines to support automated testing and deployments
• Ability to apply quality best practices and implement automated testing using tools such as Playwright
• Solid understanding of architectural patterns (event-driven, serverless, SOA, and others)

Preferred:

• Understanding of different programming paradigms such as OOP and Functional
• Experience with highly available, highly scalable SaaS applications
• Working knowledge of logging and observability best practices
• Familiarity with DevOps principles and the ability to work closely with platform teams
• Knowledge of performance tuning, cost optimization, or scalability in a cloud-native environment
• Comfort navigating ambiguity to define and implement technical solutions
• Experience collaborating with cross-functional partners (Product, Design, Data)
• Familiarity with GraphQL APIs
• Working knowledge of container-based technologies (Docker, Fargate, Kubernetes, or other)

About the Team 

At Dice, we believe that delivering an exceptional candidate experience — the end-to-end journey a job seeker takes to discover, evaluate, and land their next role — is essential to the success of our platform. This team plays a critical role in building the next generation of that experience, contributing across a modern full-stack environment. We value engineers who are curious, collaborative, and committed to making an impact for thousands of job seekers. 

We are an AI-native team. We actively use AI coding assistants (e.g., Claude Code, Codex, Gemini CLI) to accelerate development, sharpen code quality, and focus our energy on higher-impact engineering work. 

About the Role 

As a Software Engineer at Dice, you’ll contribute to the design, development, and delivery of high-impact product features in a modern, cloud-native stack. As a Software Engineer, you’ll be expected to provide technical support within the team by adhering to architectural decisions, working collaboratively teammates, and helping maintain a high standard of quality and maintainability. You’ll contribute cross-functionally with Product, Design, and Data partners to achieve ongoing outcomes and implement sound technical solutions.  

Being AI-native is central to how we work. We expect engineers in this role to go beyond using AI as a simple chat assistant, embracing tools like Claude Code as core parts of the development workflow to increase productivity such as automating repetitive tasks by generating skills and leveraging subagents, and apply best practices through prompt engineering to get the most out of the AI tools we use at every stage of the software lifecycle.  

Why We’re Hiring for This Role 

As we scale and modernize our platform, we’re looking for engineers who can take ownership of complex systems, communicate effectively with collaborators and team members, deploy AI-powered features, and contribute to product and architectural decisions. This role is ideal for someone who enjoys working across the stack, solving real user problems, working with AI, and influencing both code and culture. 

In the Short Term, You Will: 

Ramp Up on Systems and Codebases 

Gain familiarity with our applications, services, tools, and infrastructure. Develop an understanding of how your team’s work fits into the broader product and architecture. 

Establish Technical Ownership 

Take responsibility for features and systems, provide thoughtful code reviews, and contribute to team design discussions. You’ll be trusted to make solid technical decisions and defend them clearly when needed while staying open to feedback. 

Collaborate and Align 

Work closely with engineers, product managers, designers, and stakeholders to align on priorities and deliver incremental value. Help improve the team's planning and execution rhythm. 

In the Long Term, You Will: 

Drive Technical Excellence 

Help evolve our systems through well-designed, scalable AI architecture. Reduce tech debt, improve performance, and contribute to shared engineering standards. 

Deliver Meaningful Business Impact 

Own end-to-end delivery of product features that support business goals and enhance user experience. Influence the roadmap by advocating for technical investments that align with long-term value. 

What You Bring to the Team: 

• Proven experience building and deploying production-grade applications with a track record of delivering value through practical, maintainable solutions 

• Strong technical skills and experience in cloud-based technologies 

• Exposure to the development and deployment of ML and AI features into a Production environment. 

• Ability to navigate ambiguity, make sound decisions, and adapt to changing priorities 

• A collaborative, team-first mindset — you know the best outcomes come from working well together, and you actively contribute to a supportive, inclusive team environment 

• Technical depth and experience that allows you to contribute to design discussions, assist in breaking down complex tasks into meaningful deliverables, and ensure a high standard of engineering quality 

• A sense of urgency, accountability, and ownership, you take pride in your work and team achievements. 
• Strong communication, problem-solving, and collaboration skills, with the confidence to advocate for ideas while being open to alternative perspectives 

Required: 

• Proven experience building and maintaining business-critical applications using Node.js and TypeScript in a production setting 

• Hands-on experience developing scalable, maintainable RESTful APIs in production environments 

• Experience with front-end frameworks such as NextJS or React 

• Demonstrated experience building highly available applications on AWS infrastructure 

• Experience implementing and working with CI/CD pipelines to support automated testing and deployments 

• Ability to apply quality best practices and implement automated testing using tools such as Playwright 

• Solid understanding of architectural patterns (event-driven, serverless, SOA, and others) 

• Practical understanding of how to implement traditional Machine Learning models and LLMs in production, including knowledge of model selection criteria and architectural trade-offs 

• Familiarity with AI/ML tooling such as LangChain, LangGraph, LangSmith, Vercel AI SDK, LiteLLM,or equivalent frameworks 

• Hands-on experience deploying LLM-powered features into production, such as simple LLM API calls, RAG (Retrieval-Augmented Generation) systems, Vector Stores, and MCP Servers 
• Familiarity with LLM guardrails and safeguards, monitoring, and observability practices for production AI systems 

Preferred: 

• Understanding of different programming paradigms such as OOP and Functional 

• Experience with highly available, highly scalable SaaS applications 

• Working knowledge of logging and observability best practices 

• Familiarity with DevOps principles and the ability to work closely with platform teams 

• Knowledge of performance tuning, cost optimization, or scalability in a cloud-native environment 

• Comfort navigating ambiguity to define and implement technical solutions 

• Experience collaborating with cross-functional partners (Product, Design, Data) 

• Familiarity with GraphQL APIs 

• Working knowledge of container-based technologies (Docker, Fargate, Kubernetes, or other) 

• Experience working as an AI-native engineer — including creating agent skill files, configuring and orchestrating subagents, or building custom AI tooling to accelerate engineering workflows 

The ideal candidate is local to and interested in working from any of our offices (Silver Spring, NYC, SF, Miami, Denver) local to them 1-2x per week.

ABOUT ROCKET MONEY 🔮

Rocket Money's mission is to empower people to live their best financial lives. Rocket Money offers members a unique understanding of their finances and a suite of valuable services that save them time and money – ultimately giving them a leg up on their financial journey.

ABOUT THE TEAM 🤝

Machine Learning Engineers at Rocket Money further our mission by building products that deepen customer relationships with our many financial products. Our work ranges from transaction enrichment to personalization to cross-functional tools that support various AI product initiatives. We work closely with product teams to develop features that help customers understand, track, and improve their personal finances. We have a strong preference for team players that are comfortable collaborating across teams, know how to support strategy with ML and AI powered user experiences, can deliver scalable and high quality user experiences, and understand the effects of their products on end users. At the Staff level, Machine Learning Engineers are expected to build broad expertise into our products and the ML solutions that power them as well as drive technical progress for the team.

ABOUT THE ROLE 🤹

As a Staff Machine Learning Engineer at Rocket Money, you will be at the forefront of our ML and AI product development, bringing your expertise to design, implement, and maintain sophisticated ML systems that drive our product experiences. You will:

• Lead the architecture and development of complex AI and ML powered features across Rocket Money's product suite, proactively identifying technical challenges before they become issues.
• Design, implement, and maintain robust evaluation frameworks. You ensure that ML/AI systems can be constantly improved and create frameworks so that others can do the same.
• Develop novel new product experiences that you are uniquely positioned to enable for users. Help Rocket Money capitalize on it’s unique dataset and scale. Guide others to help generate impact through effective technical leadership and partnership with product.
• Own end to end development and implementation of ML and AI product features in collaboration with cross-functional product development teams. Rigorous technical critique and oversight coupled with effective communication of business impact are musts.
• Provide technical mentorship, fostering an environment where everyone can contribute to high-impact work. You will raise the level of everyone around you.

Potential Projects:

• Develop comprehensive evaluation and ML Ops frameworks that enable systematic assessment of model performance, supporting rapid iteration and improvement of AI/ML product features.
• Scale transaction metadata generation systems to billions of financial transactions in a consumer facing app. Implement AI assisted transaction management and personalization features such as personalized categories, income and rent detection, and subscription identification.
• Implement effective user feedback mechanisms that enable measurement of ML feature product quality and constant improvement.
• Architect user facing predictive features that depend on fast moving and large scale user transaction data.

ABOUT YOU 🦄

• 8+ years of professional experience in machine learning engineering or data science roles, with a proven track record of designing and implementing ML systems at consumer tech scale and speed.
• Extensive hands-on experience integrating ML and AI methods into production workflows, including creating evaluation tooling and effective user feedback mechanisms to support rapid product development cycles and systematic model evaluation.
• Experience with prompt engineering and management, creating robust systems for testing and optimizing LLM-based applications.
• Expert-level proficiency in Python, SQL, and at least a handful of common ML frameworks. Working Typescript knowledge is a plus. You understand ML methods at a fundamental level - deep experience in NLP techniques is a plus.
• You are a master at taking ambiguous problems, creating clarity, and breaking down work into manageable chunks for implementation. You’ve owned the development, launch, and maintenance for several scaled ML/AI powered product experiences.
• You understand basic software engineering and computer science fundamentals and have applied them at consumer grade scale to build ML powered products in production environments.
• You are a technical leader who can identify both emergent technical opportunities and gaps relative to best practice. Your strong communication skills enable your team to capitalize on these opportunities and generate impact.
• You care about products and user experiences, not publications. You are a practitioner first and thrive at the (messy) intersection of the real world and cutting edge approaches.

WE OFFER 💫

• Health, Dental & Vision Plans
• Competitive Pay
• 401k Matching
• Unlimited PTO
• Lunch daily (in-office only)
• Snacks & Coffee (in-office only)
• Commuter benefits (in-office only)

Additional information: Salary range of $210,000 - $260,000/year + bonus + benefits. Base pay offered may vary depending on job-related knowledge, skills, and experience.

Rocket Money is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.