We are looking for a Manager, Customer Success Engineering (AI & Cloud Support) who is passionate about delivering exceptional support experiences and building high-performing teams.

As a Manager, CSE (AI & Cloud Support) at DigitalOcean, you will operate as a Support Manager leading a team of Customer Success Engineers (CSEs) supporting strategic customers across cloud infrastructure and emerging AI/ML workloads. Reporting to the Senior Manager of Customer Success Engineering, you will own day-to-day support operations, team performance, and customer experience outcomes.

This role is focused on driving operational excellence while building strong technical depth within the team across AI, GPUs, Kubernetes, Databases and core cloud offerings. You will play a key role in ensuring consistent support coverage, developing SMEs, and partnering cross-functionally with Product and Engineering to improve both customer experience and product quality.

The ideal candidate brings a deep understanding of cloud and AI/ML ecosystems, including machine learning operations (MLOps), and enterprise support, combined with a passion for innovation and automation, and a proven ability to lead teams in delivering “white-glove” experiences for strategic customers.

What You’ll Do:

Team Leadership & Development

• Lead, hire, train, mentor and develop a high-performing team of Customer Success Engineers (CSEs), driving accountability, performance, and career growth
• Establish performance metrics (KPIs/SLAs) and conduct regular 1:1s, performance reviews, and career development planning.
• Own end-to-end support operations, including queue management, escalations, and shift planning to ensure consistent 24x7 coverage.
• Drive improvements in key support metrics such as CSAT, response times, resolution times, and overall support quality.
• Build and strengthen technical expertise within the team across core areas such as Kubernetes (DOKS), Databases, Compute, and AI/ML workloads.
  
  

Strategic Customer Support

• Act as the ultimate point of technical escalation for our largest, most strategic enterprise customers across Cloud and AI/ML workloads, stepping in to manage critical incidents and high-severity (Sev1/Sev2) issues.
• Design and implement customized support plans, SLAs, and escalation pathways tailored to the needs of strategic accounts.
• Partner closely with Technical Account Managers (TAMs), Growth Account Managers (GAM) to conduct Executive Business Reviews (EBRs) and ensure customers are maximizing the value of our Cloud and AI/ML products.
• Proactively identify risks and opportunities within strategic accounts to improve customer experience, adoption, and retention.

Technical & Cross-Functional Operations

• Serve as the Voice of the Customer (VoC) to Product and Engineering teams, synthesizing support data to advocate for bug fixes, feature requests, and UX improvements.
• Own and continuously improve escalation protocols between AI/ML Support and CloudOps, Infrastructure Engineering, and Product — including Jira escalation routing, Sev1 bridge management, and post-incident documentation.
•  Own the development and maintenance of SOPs, escalation runbooks, HVC support playbooks, and knowledge base content — treating documentation infrastructure as a core operational lever for team scalability.
• Contribute to the vision for AI and automation within support—building intelligent tooling and driving the team toward an automation-first model to improve efficiency, scalability, and customer experience.
• Foster a culture of continuous learning, ensuring the team stays ahead of evolving cloud technologies, AI/ML frameworks, and industry trends.

Key Metrics:

• Customer Satisfaction (CSAT) for strategic accounts
• Time to Response and Resolution (TTR) for strategic customers
• Tier 1 resolution rate vs. escalation rate
• Time-to-escalation and engineering handoff SLA adherence
• SLA adherence and escalation response times
• Support productivity and quality (QA scores)
• Post-incident documentation completion rate

What You’ll Add to DigitalOcean:

• Experience: 5+ years of experience in Technical Support, Customer Success, or Technical Account Management within B2B SaaS, Cloud, or AI/ML environments ideally including experience supporting AI-native, high-growth companies with 24x7 production dependencies on GPU infrastructure.
• Leadership: 2+ years of people management experience leading technical, customer-facing teams, preferably in a high-growth, post-acquisition, or rapidly scaling environment.
• Technical Domain Expertise: Solid understanding of AI/ML concepts, including Generative AI, Large Language Models (LLMs), natural language processing (NLP), and MLOps. Deep familiarity with GPU infrastructure (NVIDIA H100/H200, bare metal GPU provisioning) and AI inference workloads is strongly preferred.
• Coding/Integration: Proficiency in reading and debugging code (Python preferred) and troubleshooting RESTful APIs and cloud architecture.
• Communication: Excellent verbal and written communication skills, with the ability to translate complex technical or AI concepts for diverse audiences OR to both highly technical engineers and non-technical business executives.
• Problem-Solving: Proven ability to remain calm under pressure and de-escalate high-stakes situations with enterprise clients.

Preferred Qualifications:

• Hands-on experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and AI toolchains (e.g., LangChain, Hugging Face).
• Experience with major cloud platforms (AWS, Google Cloud, Azure) and their native AI/ML services.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.
• ITIL or equivalent service management certification

Compensation Range: 

• $125,000 - $153,000

*This is a remote role

JR: 2026-7692

#LI-Remote

We are looking for a Strategic Technical Account Manager who is passionate about making an impact, builds genuine relationships with senior stakeholders, and understands how to integrate infrastructure choices into business strategy.

As a Strategic Technical Account Manager (TAM) at DigitalOcean, you will join a dynamic team dedicated to revolutionizing cloud computing and AI. 

What You’ll Do:

Strategic Relationship Management

• Own the technical relationship with DigitalOcean’s highest-value customers, including Fortune 500 companies and global technology leaders.
• Serve as the trusted technical advisor and executive-facing point of contact, building deep, lasting relationships with VP- and SVP-level stakeholders.
• Drive regular technical and strategic alignment sessions (QBRs, EBRs), proactively shaping the customer’s roadmap to maximize the value of DigitalOcean infrastructure.
• Operate as a thought partner, challenging customers to modernize, optimize, and scale AI/ML and GPU workloads using cutting-edge cloud architecture patterns.

Executive Presence & Influence

• Engage with C-level and VP-level contacts with confidence, clarity, and authority.
• Deliver high-impact, boardroom-ready presentations on architecture decisions, cost-performance tradeoffs, and innovation opportunities.
• Navigate complex org structures, ensuring DigitalOcean maintains executive alignment and account control at every level.

Technical Consultation & Innovation Support

• Provide expert guidance on designing and scaling AI/ML, containerized, and GPU-intensive workloads on DigitalOcean.
• Assist customers with architectural planning, workload migration, performance tuning, and incident response.
• Collaborate directly with engineering and product teams to address customer roadblocks and influence the product roadmap based on enterprise needs.

Growth, Retention & Advocacy

• Own technical success across a portfolio of DigitalOcean’s largest and most strategic accounts.
• Identify opportunities for workload expansion, cost optimization, and operational efficiency.
• Act as the voice of the customer, providing structured feedback to influence DigitalOcean's offerings and go-to-market strategies.
  Lead cross-functional account planning with Account Management, Product, and Engineering.

What You’ll Add to DigitalOcean:

Enterprise Customer Experience

• 7+ years supporting enterprise or strategic accounts in a customer-facing technical role (TAM, Solutions Architect, or equivalent).
• Experience working with large-scale organizations like AMD, Intel, or similar, including managing executive-level relationships and navigating matrixed stakeholders.
• Deep understanding of cloud architecture for AI/ML, including GPU orchestration, inference/training pipelines, and model deployment.

Technical Depth

• Proficient in at least one major cloud platform (AWS, GCP, Azure) and familiar with DigitalOcean or other developer-focused platforms.
• Strong hands-on skills with Linux systems, networking, containers (Docker/Kubernetes), and automation (Terraform, Ansible).
  Programming/scripting in Python, Go, or similar—especially relevant to AI/ML and MLOps use cases.
• Understanding of AI/ML infrastructure stacks: PyTorch, TensorFlow, ONNX, Hugging Face, NVIDIA Triton, etc.
• Understanding of AI/ML infrastructure, including frameworks like PyTorch, TensorFlow, and ONNX, with hands-on experience optimizing GPU workloads on both NVIDIA (CUDA, TensorRT) and AMD (ROCm, MIOpen) platforms.
• Comfort with modern DevOps and data stack tools (CI/CD, GitOps, observability, pipelines).

Executive Presence & Communication

• Proven ability to engage with and influence executive decision-makers.
• Exceptional communication skills, including the ability to translate complex technical topics into strategic business impact.
• Comfortable presenting to large audiences, running technical workshops, and defending architectural decisions.

Bonus Points

• Cloud certifications (AWS SA Pro, GCP PCA, Azure Architect) or NVIDIA certifications.
• Experience with high-performance computing, edge AI, or hybrid/multicloud strategies.
• Background in startup or high-growth environments where agility and influence matter.
• Familiarity with DigitalOcean’s developer ecosystem, API, and service portfolio.

Compensation Range: 

• $174,240 - $217,800

*This is a remote role

#LI-Remote

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. 

Method is a global design and engineering consultancy founded in 1999. We believe that innovation should be meaningful, beautiful and human. We craft practical, powerful digital experiences that improve lives and transform businesses. Our teams based in New York, Charlotte, Atlanta, London, Bengaluru, and remote work with a wide range of organizations in many industries, including Healthcare, Financial Services, Retail, Automotive, Aviation, and Professional Services.

Method is part of GlobalLogic, a digital product engineering company. GlobalLogic integrates experience design and complex engineering to help our clients imagine what’s possible and accelerate their transition into tomorrow’s digital businesses. GlobalLogic is a Hitachi Group Company.

We are seeking an experienced Principal Data Architect to join our Data & AI team. In this leadership role, you will help shape modern data and AI architecture strategies that enable organizations to achieve business outcomes through scalable, reliable, and secure data platforms. You will work closely with senior stakeholders, client teams, and engineering teams to define architectural direction, guide implementation approaches, and support the delivery of data-driven capabilities across analytics, AI, and operational use cases. You will exemplify Method culture and values by driving standards of excellence and mentoring and educating those who are accountable to you on projects or within the data engineering discipline. You will be reporting into the head of the Data & AI team. 

This role requires a strong blend of technical depth, architectural thinking, client engagement and team mentorship. You will be expected to navigate ambiguity, align business and technology priorities, and help teams deliver practical, high-quality solutions that support long-term value creation. In addition to shaping solution direction, you will play an important role in guiding and developing data engineering teams through coaching, knowledge sharing, and hands-on support.

Travel for team, client and sales meetings is required, typically up to 25%. This is a US-based position in the East Coast or Mid-Central time zone.

Job Responsibilities

• Lead complex data and AI platform initiatives, addressing architectural concerns while enabling delivery teams to meet defined standards, timelines, and budgets.
• Provide client-facing technical leadership on data architecture, data engineering, analytics platforms, and AI/ML infrastructure.
• Collaborate with enterprise architects and senior technology stakeholders to align on architectural decisions, trade-offs, and implementation approaches.
• Communicate architectural concepts clearly to both engineering teams and business stakeholders.
• Design architectures that bridge operational systems and analytical platforms, enabling data products, advanced analytics, and AI capabilities.
• Define and implement architectures for data governance, security, privacy, and regulatory compliance.
• Establish and integrate data quality frameworks, observability practices, and data reliability processes.
• Partner with sales and pre-sales teams to shape solution approaches, validate technical feasibility, and support proposals.
• Develop new value propositions and offerings for the data engineering at Method, create go to market strategies, test and refine the offerings during the sales pursuits.
• Grow and maintain the data engineering team. Provide career guidance and facilitate career development opportunities across Method. 
• Create an environment that brings together the best of various data disciplines with care for the uniqueness of each project. 
• Foster a culture of curiosity and learning, creating opportunities for employees to learn and grow into our future leaders.

Skills Required
Technical Skills

• 8+  years of experience in data engineering, with 3+ years in a technical leadership role. 
• Experience designing and implementing modern data architectures, including lakehouse, data mesh, and real-time data platforms, and evaluating technology trade-offs.
• Strong background in distributed systems and data-intensive applications.
• Experience building and operating large-scale data platforms, including data warehouses, streaming systems, and data lakes.
• Expertise in data modeling, data platform operations, observability, and reliability engineering for data systems.
• Proficiency with modern data and distributed technologies such as Spark, Kafka, Flink, Trino/Presto, Iceberg/Delta/Hudi, and distributed storage systems.
• Experience designing streaming and low-latency architectures and understanding their operational trade-offs.
• Experience designing and deploying AI/ML platforms, including feature stores, model training pipelines, and model serving systems.
• Familiarity with MLOps and ML productionization practices, including CI/CD, model monitoring, and governance.
• Strong experience working with cloud platforms (AWS, Azure, or GCP) and cloud-native data services.
• Experience with modern data platforms such as Snowflake, Databricks, or similar analytics environments.
• Understanding of data governance frameworks, data cataloging, lineage, and privacy controls.
• Experience implementing data-driven decision systems, advanced analytics, and machine learning solutions in enterprise environments.

Professional Skills

• Advise C-suite executives on data strategy, AI investment, and digital transformation at the highest organizational level.
• Strong experience supporting pre-sales, solution shaping, and technical discovery engagements.
• Support client partners in growing key accounts by identifying new opportunities, navigating complex situations, and educating clients on the value of our work beyond data and AI.
• Excellent stakeholder management skills and the ability to build trust with both business and technical leaders.
• Ability to cultivate strong partnerships across organizations to drive adoption of modern data and AI capabilities.
• Strong influencing skills, with the ability to galvanize, inspire, and align others around a shared direction.
• Contribute Thought Leadership through presentations, blogs, or public talks
• Strong conflict resolution and risk management skills.
• Team player with the capacity to mentor, guide, and champion engineering teams and architects.
• Commitment to technical excellence, pragmatic delivery, and continuous improvement. 

Why Method?

We look for individuals who are smart, kind and brave. Curious people with a natural ability to think on their feet, learn fast, and develop points-of-view for a constantly changing world find Method an exciting place to work. Our employees are excited to collaborate with dispersed and diverse teams that bring together the best in thinking and making. We champion the ability to listen, and believe that critique and dissonance lead to better outcomes. We believe everyone has the capacity to lead and look for proactive individuals who can take and give direction, lead by example, enjoy the making as much as they do the thinking, especially at senior and leadership levels.

We believe in work/life balance. Seriously. We offer a ton of competitive perks, including:

• Continuing education opportunities 
• Flexible PTO and work-from-home policies 
• Pension 
• Health and dental benefits
• Company lunches, company outings, along with a lot of snacks 
• Health and wellness programs 
• Other location specific perks (just ask!)

Next Steps

If Method sounds like the place for you, please submit an application. Also, let us know if you have a presence online with a portfolio, GitHub, Dribbble or other platform.

* For information on how we process your personal data please see Privacy.

* If you are a California resident, more details on how we process your personal information can be found in the CCPA Recruitment Privacy Notice (https://www.globallogic.com/privacy/ccpa-recruitment-privacy-notice/)"

Colorado Applicants (Colorado Equal Pay for Equal Work Act Disclosure):  The starting salary range for this role to be performed in Colorado is estimated to be between $160,000 to $200,000 annually.  This salary range is specific to Colorado residents only, and provided as a general estimate.  The amount offered may be higher or lower. Method  takes many factors into making an offer, including candidate qualifications, work experience, operational needs, travel and onsite requirements, internal peer equity, prevailing wage, responsibilities, and other market and business considerations. 

New York City Applicants (New York City Local Law 32;  Pay Transparency Law):  The starting salary range for this role to be performed in New York City is from $192,000 to $205,000. This salary range is specific to New York City residents only, and provided as a general, good faith estimate. The amount offered may be higher or lower. Method takes many factors into making an offer, including candidate qualifications, work experience, operational needs, travel and onsite requirements, internal peer equity, prevailing wage, responsibilities, and other market and business considerations.

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 THIS OPPORTUNITY

onX is seeking a Staff Software Engineer who will contribute to meaningful, real-world outcomes that have a lasting impact for customers and the business. In this role, you’ll focus on the design, development, and scaling of our core AI/ML platforms and product-facing services as part of the AI Foundations Team, supporting the integration of cutting-edge artificial intelligence solutions across onX's product lines. You’ll take ownership of your work, collaborate closely with partners across the organization, and help move initiatives forward in an environment where priorities evolve, learning is celebrated, and you’re encouraged to keep stretching your skills. This role will report to the Director of Engineering.

WHAT YOU'LL DO
^{Essential Job Duties & Functions}

• Work on the design, development, and deployment of large-scale AI systems and services, including models, pipelines, product experiences and infrastructure.
• Help Drive the technical strategy and roadmap for AI feature development, focusing on scalability, repeatability, reliability, and performance.
• Mentor and guide other engineers in best practices and productionizing AI technologies.
• Collaborate with Product and Data Science teams to translate business problems into technical requirements and deliver high-impact AI solutions (combining LLMs, Vector Databases, ML and other technology in novel ways to serve onX’ unique audience).
• Look for opportunities to embed AI as a repeatable mechanism in daily workflows by integrating experimentation into real work, and continuously refining its use with sound judgment and validation.
• Be a leader in AI safety, ensuring AI-enabled products are aligned with our values and mission.
• Look for opportunities to embed AI as a repeatable co-pilot in daily workflows by integrating experimentation into real work, and continuously refining its use with sound judgment and validation.

WHAT YOU’LL BRING

• Bachelor’s degree in Computer Science, Data Science, or a related technical field, or equivalent experience.
• 10+ years of professional software engineering experience, with at least 3 years focused on building and scaling production AI/ML systems, is required.
• Expertise in building scalable backend systems.
• Deep knowledge of MLOps practices, cloud infrastructure (AWS/GCP/Azure), and CI/CD pipelines for machine learning models and the common inference APIs/SDKs and frameworks.
• Experience with modern AI technologies, including Large Language Models (LLMs) and their various architectures, methods such as RAG, vector databases, and the common AI stack including TensorFlow/Keras, PyTorch, Transformers, etc.
• A strong curiosity for exploring new technologies, including AI
• A shared passion for and ability to demonstrate onX’s Company Values.
• Permanent US work authorization is a condition of employment with onX.

ADDED BONUSES

Though not required, we would be thrilled to consider candidates with any of the following:

• A history of engaging in AI development, from the early ML/NN (YOLO, Darknet) to the LLM era.
• Experience in monitoring and debugging production AI systems (inference, evals, judging, benchmarks) including cost and performance optimizations.
• Interest or experience in edge/on-device inference (MLX, JAX, transformers on TPU/NPU, etc.)
• Interest, experience or experimentation in training/fine-tuning transformer/diffusion models, dataset curation and captioning, etc.

THE ONX EXPERIENCE

onX is a distributed company with more than 400 employees across the country. We come together regularly to work in person and stay connected through regional basecamps and a culture that balances individual ownership with deep collaboration.

While we move quickly, we’re not a scrappy start-up. We operate with clear goals, structure, and frameworks that guide how we prioritize and execute. Priorities matter. While they may shift, data shapes how we evolve as our business, products, and the world around us change.

Clear priorities and structure don’t limit ownership - they make it possible. You’ll have the autonomy to define your work and make meaningful decisions within clear strategic boundaries. You’ll partner closely with others to solve complex problems and build solutions that scale across teams and platforms. Along the way, you’ll be supported with feedback, tools, and opportunities to grow your craft as you take on new challenges.

WHERE YOU CAN WORK

onX has created a thriving distributed workforce designed to foster connection, collaboration, and shared experience across several US locations. We have two HQ locations in Bozeman and Missoula, MT and established virtual workforce Basecamps in Austin, TX; Denver, CO; Kalispell, MT; Minneapolis, MN; Portland, OR; Salt Lake City, UT; and Seattle, WA.

HOW YOU’LL BE COMPENSATED

onX is committed to compensating all employees fairly and equitably for their contributions.  Applicants can expect to make between $169,000 to $211,000 upon hire. The pay range will vary based on experience, skills, certifications, and education among other factors as required in the job description. In addition, full-time onX employees are eligible for a grant of common share options with a vesting schedule and a potential annual bonus of 10% based on company performance.

WHAT WE’RE OFFERING YOU

• Competitive salaries, annual bonuses, equity, and opportunities for growth
• Comprehensive health benefits, including a no-monthly-cost medical plan
• Paid parental leave of 13 weeks for birthing parents and 5 weeks for non-birthing parents
• 401k matching at 100% for the first 3% you save and 50% from 3-5%
• Company-wide outdoor adventures and amazing outdoor industry perks
• Annual “Get Out, Get Active” funds to fuel your active lifestyle
• Flexible time away package that includes PTO, STO, VTO, and paid holidays

PERFORMANCE ESSENTIALS

In this role, success is driven by cognitive abilities such as concentration and problem-solving, essential for our computer-centric tasks. onX will explore reasonable accommodations to ensure that individuals with diverse abilities can fully engage in and contribute to the essential physical and mental functions of the job. If you need assistance or accommodation, please contact us at PC@onxmaps.com. 

Application Deadline is [day of week], [month] [day] at [0:00 pm] MST

Position open until filled. 

#LI-Remote

About the Opportunity

We are seeking a Senior Software Engineer to design, build, deploy, monitor, and optimize production-ready ML services in regulated healthcare. You will work hands-on to package, test, orchestrate, deploy, and maintain ML models, improve workflows, and implement CI/CD and automated testing to ensure reliability, performance, and faster delivery of business value.

Responsibilities

• Design, build, and deploy scalable AI/ML services with clear service boundaries, making pragmatic trade-offs across performance, maintainability, security, and long-term extensibility.

• Own full lifecycle delivery of complex features from architectural planning and API design to implementation and post-release observability.

• Define and enforce robust verification and validation for AI services including unit, integration, and end-to-end testing to ensure reliability of code in production and compliance with our Quality Management System and regulatory standards. 

• Integrate CI/CD and MLOps practices for automated model builds, testing, and deployment.

• Translate product requirements into well-defined technical designs proactively shaping implementation details.

• Contribute to the necessary technical documentation required for regulatory submissions.

• Collaborate cross functionally to reduce knowledge silos and ensure continuity in critical systems through cross-training and documentation. 

Requirements

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field

• 7+ years of software engineering experience, with expertise in AI production systems (Python, PyTorch) and data services (SQL, Postgres, NoSQL, Redis or similar).

• Experience with unit, integration testing for ML models, including data validation, correctness checks, and reproducibility.

• Experience with CI/CD, Orchestration tools (Airflow, MLflow, Kubernetes, Terraform) and ML/data platforms(SageMaker, Databricks, Unity Catalog, Snowflake/Snowpark) to build scalable ML data pipelines and model workflows.

• Strong collaboration skills to work effectively with ML scientists, engineers, and regulatory teams.

• Comfortable operating in ambiguity and driving clarity across product, engineering, and business stakeholders.

This role is eligible for a 15% target annual bonus, resulting in the following base salary and Total Target Compensation (TTC) ranges:

• Base Salary: $153,000 - $179,000
• TTC: $176,000 - $206,000

*Total Target Compensation (TTC): Total Cash Compensation (including base pay, variable pay, commission, bonuses, etc.) Additionally, stock options, paid benefits, and employee perks are part of your total rewards.

About the Opportunity

We are seeking a senior machine learning software engineer to design, build, deploy, monitor, and optimize production-ready ML services in regulated healthcare. You will work hands-on to package, test, orchestrate, deploy, and maintain ML models, improve workflows, and implement CI/CD and automated testing to ensure reliability, performance, and faster delivery of business value.

Responsibilities

• Collaborate with AI scientists to package and deploy ML models, ensuring reproducibility, versioning, and compliance.
• Build and maintain model serving infrastructure including monitoring, drift detection, automated retraining, and logging.
• Implement unit, integration, and system-level testing for ML models, covering data validation, model correctness, and deployment workflows.
• Develop and operate end-to-end ML pipelines: ingestion → preprocessing → feature engineering → evaluation → deployment → monitoring.
• Integrate CI/CD and MLOps practices for automated model builds, testing, and deployment.
• Identify and resolve workflow inefficiencies or gaps between research and production.
• Recommend and integrate frameworks, libraries, and infrastructure to improve pipeline efficiency, maintainability, and observability.
• Collaborate cross-functionally to ensure compliance with regulatory requirements (FDA/HIPAA) in production ML workflows.
  
  

Requirements

• 7+ years of experience in software engineering for ML production or ML platform delivery.
• Hands-on experience deploying ML models via APIs, batch pipelines, or streaming inference.
• Proficiency in Python (required), Java, or similar, with software engineering best practices for ML workflows.
• Experience with unit, integration, and pipeline-level testing for ML models, including data validation, correctness checks, and reproducibility.
• Familiarity with cloud platforms (AWS preferred: SageMaker, S3, EC2) and reproducible ML pipelines.
• Experience with CI/CD, Orchestration tools (Airflow, MLflow, Kubernetes, Terraform) and ML/data platforms(SageMaker, Databricks, Unity Catalog, Snowflake/Snowpark) to build scalable ML data pipelines and model workflows.
• Strong collaboration skills to work effectively with AI scientists, software engineers, and regulatory teams.

The base salary range for this role varies by location and is aligned to market benchmarks.

• Candidates located in higher-cost labor markets, including California, Washington, New York, New Jersey, Connecticut, Massachusetts, and Washington, DC represent the middle to high end of the range, while candidates located in all other U.S. locations represent the low to middle end of the range.
• Final compensation is determined based on location, experience, skills, and internal equity.

This role is eligible for a 15% target annual bonus, resulting in the following base salary and Total Target Compensation (TTC) ranges:

• Base Salary: $153,000 - $179,000
• TTC: $176,000 - $206,000

*Total Target Compensation (TTC): Total Cash Compensation (including base pay, variable pay, commission, bonuses, etc.) Additionally, stock options, paid benefits, and employee perks are part of your total rewards.

ABOUT THIS OPPORTUNITY

We are looking for a Data Scientist who views machine learning as a product, not just a research project. You will be a foundational member of our AI team, responsible for designing, building, and deploying sophisticated models that solve complex business problems. You aren't just an expert in XGBoost or Transformers; you are an expert in building the pipelines that make these models reliable, scalable, and impactful.

WHAT YOU'LL DO
^{Essential Job Duties & Functions}

• End-to-End Model Development: Design and implement the full ML lifecycle—from exploratory data analysis (EDA) and feature engineering to model selection, tuning, and validation.
• GCP Architecture: Leverage the full Google Cloud AI suite (Vertex AI, BigQuery ML, Dataflow, and Pub/Sub) to build robust, cloud-native ML solutions.
• MLOps & Engineering: Implement CI/CD for machine learning (CT - Continuous Training) to ensure models remain performant in production environments.
• Strategic Leadership: Partner with stakeholders to translate ambiguous business challenges into technical roadmaps. Mentor junior scientists and advocate for best practices in code quality and experiment tracking.
• Look for opportunities to embed AI as a repeatable co-pilot in daily workflows by integrating experimentation into real work, and continuously refining its use with sound judgment and validation.

WHAT YOU’LL BRING

• 5+ years in a professional Data Science role with a track record of deploying models at scale.
• Proficiency in Vertex AI, BigQuery, Cloud Storage, and Looker. Experience with Kubeflow is a major plus.
• Expert-level Python (pandas, scikit-learn, PyTorch/TensorFlow), Spark, and advanced SQL.
• Deep understanding of statistics and ML theory (e.g., Gradient Descent, Bias-Variance tradeoff, Bayesian inference).
• Experience with ETL/ELT processes, specifically using dbt.
• A strong curiosity for exploring new technologies, including AI
• A shared passion for and ability to demonstrate onX’s Company Values.
• Permanent US work authorization is a condition of employment with onX.

Our Tech Stack

• Data Warehouse: BigQuery
• Orchestration: Airflow (Cloud Composer)
• Modeling: Vertex AI Pipelines, JupyterLab
• Deployment: Docker, GKE (Google Kubernetes Engine)

Pro Tip for the Candidate: We value "clean code" as much as "smart math." If you treat your notebooks like production scripts and your Git history is a work of art, you’ll fit right in.

What Sets You Apart

• The "Product" Mindset: You understand that a model with 99% accuracy is useless if it costs more to run than the value it creates.
• Infrastructure as Code: You are comfortable with Terraform or similar tools to manage your cloud resources.
• Communication: You can explain the "why" behind a complex neural network architecture to an executive without using jargon.

THE ONX EXPERIENCE

onX is a distributed company with more than 400 employees across the country. We come together regularly to work in person and stay connected through regional basecamps and a culture that balances individual ownership with deep collaboration.

While we move quickly, we’re not a scrappy start-up. We operate with clear goals, structure, and frameworks that guide how we prioritize and execute. Priorities matter. While they may shift, data shapes how we evolve as our business, products, and the world around us change.

Clear priorities and structure don’t limit ownership - they make it possible. You’ll have the autonomy to define your work and make meaningful decisions within clear strategic boundaries. You’ll partner closely with others to solve complex problems and build solutions that scale across teams and platforms. Along the way, you’ll be supported with feedback, tools, and opportunities to grow your craft as you take on new challenges.

WHERE YOU CAN WORK

onX has created a thriving distributed workforce designed to foster connection, collaboration, and shared experience across several US locations. We have two HQ locations in Bozeman and Missoula, MT and established virtual workforce Basecamps in Austin, TX; Denver, CO; Kalispell, MT; Minneapolis, MN; Portland, OR; Salt Lake City, UT; and Seattle, WA.

HOW YOU’LL BE COMPENSATED

onX is committed to compensating all employees fairly and equitably for their contributions. For this position, applicants can expect to make between $126,000 to $149,000 upon hire. The pay range will vary based on experience, skills, certifications, and education among other factors as required in the job description. In addition, full-time onX employees are eligible for a grant of common share options with a vesting schedule and a potential annual bonus of 10% based on company performance.

WHAT WE’RE OFFERING YOU

• Competitive salaries, annual bonuses, equity, and opportunities for growth
• Comprehensive health benefits, including a no-monthly-cost medical plan
• Paid parental leave of 13 weeks for birthing parents and 5 weeks for non-birthing parents
• 401k matching at 100% for the first 3% you save and 50% from 3-5%
• Company-wide outdoor adventures and amazing outdoor industry perks
• Annual “Get Out, Get Active” funds to fuel your active lifestyle
• Flexible time away package that includes PTO, STO, VTO, and paid holidays

PERFORMANCE ESSENTIALS

In this role, success is driven by cognitive abilities such as concentration and problem-solving, essential for our computer-centric tasks. onX will explore reasonable accommodations to ensure that individuals with diverse abilities can fully engage in and contribute to the essential physical and mental functions of the job. If you need assistance or accommodation, please contact us at PC@onxmaps.com. 

Application Deadline is [day of week], [month] [day] at [0:00 pm] MST

Position open until filled. 

#LI-Remote

CSQ127R318

As a Big Data Solutions Architect (Resident Solutions Architect) in our Professional Services team you will work with clients on short to medium term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of  professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps 
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time
• Databricks Certification

About the Opportunity

We're seeking a Software Engineer 3 to drive key technical initiatives across our computational imaging pipeline. In this high-impact role, you'll be part of the team owning the complex systems responsible for deploying, scaling, and monitoring our regulated AI algorithms end-to-end. You will influence the architecture of our system, ensuring our solutions meet medical standards for quality and performance, while mentoring other engineers and helping shape our technical culture.

About the Team

You will join our expert Computational Imaging team, where we develop sophisticated algorithms to enhance and improve medical imaging. We are focused on improving the quality and clinical value of medical images, creating powerful, extra software components that correct artifacts, standardize data, and ensure the utmost precision before the final analysis. Our work is essential for elevating the reliability and accuracy of Cleerly’s regulated products.

Responsibilities

• Build and deploy scalable AI services and computational imaging pipelines to production, ensuring robust, high-availability infrastructure for our machine learning algorithms.
• Contribute to the system architecture's design and make pragmatic trade-offs that balance performance, security, and maintainability.
• Own full lifecycle delivery of complex features, from architectural planning and API design to implementation and post-release observability.
• Support the high availability and observability of our services; improve alerting, logging, and incident response across the stack.
• Uphold strong engineering standards via code reviews, technical mentorship, and design documentation.
• Collaborate closely across AI and engineering to reduce knowledge silos and ensure continuity in critical systems through cross-training and documentation.
• Implement robust testing mechanism and validation strategies to ensure compliance with our Quality Management System and regulatory standards 

Requirements 

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field (or equivalent experience).
• 5–8 years of software engineering experience, with expertise in AI production systems (Python, PyTorch) and data services (SQL, Postgres, NoSQL, Redis or similar).
• Demonstrable capability in designing, implementing, and securing RESTful web services
• Experience in MLOps orchestration and cloud deployment (Docker, Kubernetes).
• Experience with AWS, GitHub, and continuous integration pipelines
• Proven track record of delivering scalable systems in production environments.
• Strong systems thinking with the ability to evaluate tradeoffs in scalability, reliability, and maintainability.
• Experience designing for observability and operational excellence (e.g., logs, alerts, dashboards, runbooks).
• Comfortable operating in ambiguity and driving clarity across product, engineering, and business stakeholders.

Preferred:

• Experience designing and optimizing end-to-end medical imaging pipelines in a production environment and familiarity with HIPAA/HITRUST security requirements.
• Hands-on experience with Computer Vision and Deep Learning techniques used for medical image processing.

OUR COMPANY IS AN EQUAL OPPORTUNITY EMPLOYER.  We do not discriminate on the basis of race, color, national origin, ancestry, citizenship status, protected veteran status, religion, physical or mental disability, marital status, sex, sexual orientation, gender identity or expression, age, or any other basis protected by law, ordinance, or regulation.

Job duties, activities, and responsibilities are subject to change by our company.

The base salary range for this role varies by location and is aligned to market benchmarks.

• Candidates located in higher-cost labor markets, including California, Washington, New York, New Jersey, Connecticut, Massachusetts, and Washington, DC represent the middle to high end of the range, while candidates located in all other U.S. locations represent the low to middle end of the range.
• Final compensation is determined based on location, experience, skills, and internal equity.

This role is eligible for a 15% target annual bonus, resulting in the following base salary and Total Target Compensation (TTC) ranges:

• Base Salary: $129,000 - $152,000
• TTC: $142,000 - $168,000

*Total Target Compensation (TTC): Total Cash Compensation (including base pay, variable pay, commission, bonuses, etc.) Additionally, stock options, paid benefits, and employee perks are part of your total rewards.

About the Opportunity

We're seeking a Senior Software Engineer to drive key technical initiatives across our computational imaging pipeline. In this high-impact role, you'll own the complex systems responsible for deploying, scaling, and monitoring our regulated AI algorithms end-to-end. You will influence the architecture of our system, ensuring our solutions meet medical standards for quality and performance, while mentoring other engineers and helping shape our technical culture.

About the Team

You will join our expert Computational Imaging team, where we develop sophisticated algorithms to enhance and improve medical imaging. We are focused on improving the quality and clinical value of medical images, creating powerful, extra software components that correct artifacts, standardize data, and ensure the utmost precision before the final analysis. Our work is essential for elevating the reliability and accuracy of Cleerly’s regulated products.

Responsibilities

• Design, build, and deploy scalable AI services and computational imaging pipelines to production, ensuring robust, high-availability infrastructure for our machine learning algorithms.
• Design extensible system architectures and make pragmatic trade-offs that balance performance, security, and maintainability.
• Own full lifecycle delivery of complex features, from architectural planning and API design to implementation and post-release observability.
• Ensure high availability and observability of our services; improve alerting, logging, and incident response across the stack.
• Set and uphold strong engineering standards via code reviews, technical mentorship, and design documentation.
• Lead technical design reviews and system decomposition efforts across teams.
• Proactively identify risks and gaps in operational or architectural resilience, and drive durable improvements.
• Collaborate closely across AI and engineering to reduce knowledge silos and ensure continuity in critical systems through cross-training and documentation.
• Design and implement robust testing mechanism and validation strategies to ensure compliance with our Quality Management System and regulatory standards 
• Contribute to the necessary technical documentation required for regulatory submissions.

Requirements 

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field (or equivalent experience).
• 8–12 years of software engineering experience, with expertise in AI production systems (Python, PyTorch) and data services (SQL, Postgres, NoSQL, Redis or similar).
• Demonstrable capability in designing, implementing, and securing RESTful web services
• Experience in MLOps orchestration and cloud deployment (Docker, Kubernetes).
• Experience with AWS, GitHub, and continuous integration pipelines
• Proven track record of architecting and delivering scalable systems in production environments.
• Experience mentoring engineers and raising the technical bar through reviews and design feedback.
• Strong systems thinking with the ability to evaluate tradeoffs in scalability, reliability, and maintainability.
• Experience designing for observability and operational excellence (e.g., logs, alerts, dashboards, runbooks).
• Comfortable operating in ambiguity and driving clarity across product, engineering, and business stakeholders.

Preferred:

• Experience designing and optimizing end-to-end medical imaging pipelines in a production environment and familiarity with HIPAA/HITRUST security requirements.
• Hands-on experience with Computer Vision and Deep Learning techniques used for medical image processing.

The base salary range for this role varies by location and is aligned to market benchmarks.

• Candidates located in higher-cost labor markets, including California, Washington, New York, New Jersey, Connecticut, Massachusetts, and Washington, DC represent the middle to high end of the range, while candidates located in all other U.S. locations represent the low to middle end of the range.
• Final compensation is determined based on location, experience, skills, and internal equity.

This role is eligible for a 15% target annual bonus, resulting in the following base salary and Total Target Compensation (TTC) ranges:

• Base Salary: $153,000 - $179,000
• TTC: $176,000 - $206,000

*Total Target Compensation (TTC): Total Cash Compensation (including base pay, variable pay, commission, bonuses, etc.) Additionally, stock options, paid benefits, and employee perks are part of your total rewards.