• AI clinical tool validation and LLM strengthening • Lead pre-deployment validation • Produce model cards/transparency (intended use, limits, monitoring, rollback). • Partner on data quality (provenance, representativeness, refresh cadence, privacy). • Build LLM evaluation datasets/gold standards; run clinical red-teams and prompt testing; refine prompts/guardrails; assess RAG fidelity. • Clinical-in-the-loop enablement: Train clinicians to oversee AI tools and adjudicate exceptions; create SOPs/checklists/escalations for LLM use. • Collaborate with engineering and product, security, compliance, legal, care and service line leaders. • AI governance and policy: Administer clinical AI governance (ethics, safety, regulatory, privacy, change control, documentation) in partnership with the Patient Safety Officer • Define clinical use criteria and human-in-the-loop guardrails; • Maintain governance artifacts (charter, SOPs, decision logs) and audit readiness. • Quality and patient safety: Support clinical QA; URAC/NCQA activities; policy/standards/rubrics management. • Lead/participate in event detection, RCA/FMEA, CAPA; education (CME/CE, targeted training). • Support client/payer audits, RFPs, VBC metrics (HEDIS, MIPS), implementations, and escalations, grievances/appeals. • Lead and/or support cross-functional efforts to analyze clinical quality performance data, identify improvement opportunities, and translate value-based care insights into health plan design enhancements that optimize outcomes, member experience, and cost efficiency. • Conduct ongoing assessments of clinical services, applying continuous improvement and evidence-based methodologies to ensure service effectiveness, measurable patient outcomes, and alignment with organizational quality standards.

In this role, you will own Achievers’ AI revenue strategy end to end, from use case discovery through deployment and measurement. This is a builder first role with the expectation that you will architect the IC facing tool stack, deploy AI agents that directly generate revenue, and operate them with the same rigor as a human team. You will partner with RevOps, Marketing, Sales, and CS leadership, but this role does not own or administer core systems (Salesforce, Marketo, NetSuite). Over time, this role may manage a group of agent operators.

• Be the domain credibility of the pod • Embed with partner teams to identify AI solutions • Lead discovery and requirements • Conduct hands-on demos tailored to workflows • Drive change management for successful deployments • Regular on-site travel expected, potentially 50%+ of time

Role Description The emphasis of this role is to be the dedicated technical lead for developing WWT’s defensive AI operations, specifically focused on utilizing massive open-source models to solve the vulnerability management problem at an enterprise scale. This position requires an elite technical leader who is adept at advanced machine learning, can speak to complex exploit mechanics, and ensure our defensive posture rapidly evolves to keep pace with AI-accelerated offense and frontier-model-class intelligence. This role will also involve guiding the organization away from manual triage by anticipating exploit chaining and integrating the largest open-source AI models to ensure our defensive strategies remain ahead of advanced adversaries. Responsibilities - Partner with the GS&A Cyber Practices to utilize models and evaluate attack paths and how AI can help defenders operate at the speed of attackers. - Deliver measurable outcomes to customers and partners as to how AI and ML-based science improves cybersecurity defenses. - Participate in industry forums on the topic of using AI for defense and perform technical demonstrations on how AI is used for offensive operations. - Architect and deploy advanced machine learning models that analyze, score, and prioritize vulnerabilities at an unprecedented scale. - Continuously evaluate, integrate, and fine-tune frontier models to match and counter frontier-model-class attack methodologies and AI-driven exploit chaining. - Shift organizational operations entirely away from manual triage by providing automated, model-assisted workflows for immediate remediation guidance. - Ingest and model complex threat data, scanning code with open-source models to train systems on handling the exploding volume of automated vulnerability reports. - Dedicate 100% of operational bandwidth to defensive cybersecurity measures, using AI to neutralize emerging threats before they can be weaponized against our customers. - Act as the technical expert for data architecture, statistical modeling, and advanced machine learning applied to massive enterprise datasets. - Drive the vulnerability prioritization problem space autonomously from concept to customer-facing deployment without distraction. - Apply deep cybersecurity domain knowledge, specifically regarding vulnerability management, exploit mechanics, and patch gap mitigation, to all AI models. Qualifications - Master’s degree or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Cybersecurity, or a related highly technical discipline. - 8+ years of progressive experience in data science, machine learning, or AI engineering, with a minimum of 3 years directly embedded in cybersecurity, threat intelligence, or vulnerability management. - Deep, hands-on expertise with the Hugging Face ecosystem (Transformers, Accelerate, PEFT). - Proven track record of deploying, quantizing, and fine-tuning (e.g., LoRA, QLoRA) large open-source models (Llama, Mistral, Qwen) for production environments. - Comprehensive understanding of the vulnerability lifecycle, patch gap analysis, exploit chaining, and standard industry frameworks (MITRE ATT&CK, CISA KEV, EPSS, CVSS). - Expert-level coding proficiency in Python and leading deep learning frameworks, specifically PyTorch. - Extensive experience operating in high-performance computing environments. - Adept at managing GPU workloads, CUDA optimization, and deploying models on distributed infrastructure (e.g., Kubernetes, Ray, vLLM). - Strong capability in building high-throughput data pipelines to ingest, clean, and process massive datasets of threat intelligence, code repositories, and telemetry. - Demonstrated ability to own a complex problem space entirely, translating theoretical data science concepts into highly scalable, real-world defensive tools at an accelerated pace. Requirements - A reasonable estimate of the current base pay range for this position is $240,000.00 to $260,000.00 annually. - Actual salary will be based on a variety of factors, including shift, location, experience, skill set, performance, licensure and certification, and business needs. - The range for this position in other geographic locations may differ. - Certain positions may also be eligible for variable incentive compensation, such as bonuses or commissions, that is not included in the base pay. Benefits - Health and Wellbeing: Health, Dental, and Vision Care, Onsite Health Centers, Employee Assistance Program, Wellness program. - Financial Benefits: Competitive pay, Profit Sharing, 401k Plan with Company Matching, Life and Disability Insurance, Tuition Reimbursement. - Paid Time Off: PTO and Sick Leave (starting at 20 days per year) & Holidays (10 per year), Parental Leave, Military Leave, Bereavement. - Additional Perks: Nursing Mothers Benefits, Voluntary Legal, Pet Insurance, Employee Discount Program.