Lead the administration and user enablement of Peraton[x], our enterprise generative AI and agentic analytics platform, accountable for configuration, governance, and successful adoption across the enterprise.
Compensation
Target Salary Range
$146,000 - $234,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual’s experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.
Responsibilities
Lead all Peraton[x] system administration, including user and program provisioning, role-based access and data-tier management, environment configuration, and platform settings.
Set and enforce administrative standards, policies, and procedures for access requests, onboarding and offboarding, project and workspace management, and knowledge-base (cortex) governance.
Oversee release readiness and change management from the administrator and end-user side.
Run the service desk and tiered user support model: ticket intake, triage, escalation to engineering, and resolution tracking against service-level targets.
Manage AI usage, cost, and license administration: track consumption and spend by program, attribute costs, and enforce usage policies.
Embed inside a bank, an insurer, or a health system, learn the work, and ship a Claude + AWS system into their real, regulated production.
Compensation
Base salary $180k to $250k + bonuses; OTE up to $300k.
Responsibilities
Spend the first weeks of each engagement in the operator’s seat, learning the constraints from the inside
Rebuild the function from first principles alongside the client and a Forward Deployed Executive
Be part of the customer’s team, inside their process; work on real tasks, not scoped deliverables, and own the method autonomously
Deliver across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare
Help shape how leading enterprises adopt AI, from strategy through first deployment; help build the tooling and frameworks of a growing AI delivery practice
The Senior AI/ML Engineer is responsible for designing, architecting, and implementing enterprise-scale AI solutions involving structured and unstructured data sources (PDFs, documents, databases, APIs, enterprise applications, knowledge repositories, etc.) to develop intelligent systems using Machine Learning, Generative AI, Large Language Models (LLMs), Agentic AI, and advanced AI frameworks.
Responsibilities
Design, architect, develop, and implement scalable AI/ML, Generative AI, and Agentic AI solutions to solve complex business problems
Lead the development of enterprise AI architectures involving traditional machine learning models, LLMs, Retrieval-Augmented Generation (RAG), vector databases, and autonomous agent systems
Design and implement intelligent multi-agent workflows using Microsoft Azure AI Agents Framework, Azure AI Foundry, Semantic Kernel, LangChain, LangGraph, and similar agent orchestration frameworks
Collaborate with business stakeholders, product owners, architects, and engineering teams to identify and prioritize AI/ML opportunities across the organization
Develop and deploy production-grade AI solutions utilizing Azure OpenAI Service, Azure AI Search, Azure Machine Learning, and related cloud AI services
Requirements
Nice to have: LLMs
Nice to have: Agentic AI
Nice to have: Retrieval-Augmented Generation (RAG)
Design and lead the delivery of sophisticated cloud-native applications and AI-powered solutions for enterprise clients, combining client-facing solution architecture and pre-sales responsibilities.
Responsibilities
Lead solution architecture for client engagements, defining technical approaches, technology choices, integrations, security requirements, and cost considerations.
Design cloud-native applications on AWS, including serverless, event-driven, and container-based architectures with integrated generative and agentic AI capabilities.
Develop end-to-end AWS architectures covering compute, data, networking, security, and AI services, ensuring alignment with the AWS Well-Architected Framework.
Translate business requirements into technical designs, implementation roadmaps, and clear architectural recommendations.
Lead client discovery sessions to assess existing systems, business requirements, technical constraints, integrations, and potential risks.
Requirements
Current AWS Certified Solutions Architect – Professional certification
Nice to have: AWS Certified Generative AI Developer – Professional (AIP-C01)
The ServiceNow Lead, Business Analyst will drive the functional delivery of a ServiceNow engagement, taking ownership of process design, requirements, and solution alignment, applying generative and agentic AI to accelerate delivery.
Compensation
Hourly compensation of $70–$80.
Responsibilities
Lead process design and fit-gap analysis, prioritizing out-of-the-box ServiceNow functionality over unnecessary customization.
Collaborate with the client's Product Owner to define, refine, and prioritize the product backlog.
Manage incident (INC) and request item (RITM) backlogs, ensuring requirements are clearly documented and prioritized.
Own Agile delivery artifacts, including user stories, acceptance criteria, and sprint plans.
Facilitate Scrum ceremonies and support the team throughout the Agile delivery lifecycle.
Leverage extensive pharmaceutical manufacturing expertise and advanced artificial intelligence knowledge to drive innovation within regulated production environments, advising senior stakeholders on AI opportunities and regulatory readiness.
Responsibilities
Analyze end-to-end autogenous vaccine development and manufacturing processes to identify operational bottlenecks, inefficiencies, and decision-making challenges.
Assess opportunities to introduce AI-driven solutions, including predictive analytics, document automation, workflow optimization, and intelligent decision-support systems.
Develop, evaluate, and prioritize AI initiatives based on technical feasibility, business value, operational impact, and implementation potential.
Support the development of regulatory-compliant organizational frameworks aligned with current and emerging AI regulations.
Assess manufacturing sites to evaluate their technological maturity, operational readiness, and suitability for AI implementation.
Leverage extensive pharmaceutical manufacturing expertise and advanced artificial intelligence knowledge to drive innovation within regulated production environments, advising senior stakeholders on AI opportunities and implementation strategies.
Responsibilities
Analyze end-to-end autogenous vaccine development and manufacturing processes to identify operational bottlenecks, inefficiencies, and decision-making challenges.
Assess opportunities to introduce AI-driven solutions, including predictive analytics, document automation, workflow optimization, and intelligent decision-support systems.
Develop, evaluate, and prioritize AI initiatives based on technical feasibility, business value, operational impact, and implementation potential.
Support the development of regulatory-compliant organizational frameworks aligned with current and emerging AI regulations.
Assess manufacturing sites to evaluate their technological maturity, operational readiness, and suitability for AI implementation.
This role will lead strategic programs that improve pricing operations, deal execution, and commercial efficiency across Sales and Go-to-Market (GTM) teams. You will own programmatic pricing initiatives, support product launch readiness, and help evolve the tools and processes used by the Deal Desk organization.
Locations (4)
San Francisco, California, United States
New York City, New York, United States
Seattle, Washington, United States
United States
Compensation
San Francisco, California: $144,000–$198,000.
New York City metropolitan area and Seattle, Washington: $125,000–$172,000.
Other US locations: $126,000–$173,000.
Potential eligibility for restricted stock units, depending on the role and applicable compensation arrangements.
Leverage extensive pharmaceutical manufacturing expertise and advanced artificial intelligence knowledge to drive innovation within regulated production environments, advising senior stakeholders on AI opportunities and regulatory readiness.
Responsibilities
Analyze end-to-end autogenous vaccine development and manufacturing processes to identify operational bottlenecks, inefficiencies, and decision-making challenges.
Assess opportunities to introduce AI-driven solutions, including predictive analytics, document automation, workflow optimization, and intelligent decision-support systems.
Develop, evaluate, and prioritize AI initiatives based on technical feasibility, business value, operational impact, and implementation potential.
Support the development of regulatory-compliant organizational frameworks aligned with current and emerging AI regulations.
Assess manufacturing sites to evaluate their technological maturity, operational readiness, and suitability for AI implementation.
Leverage extensive pharmaceutical manufacturing expertise and advanced artificial intelligence knowledge to drive innovation within regulated production environments, advising senior stakeholders on AI opportunities and implementation strategies.
Responsibilities
Analyze end-to-end autogenous vaccine development and manufacturing processes to identify operational bottlenecks, inefficiencies, and decision-making challenges.
Assess opportunities to introduce AI-driven solutions, including predictive analytics, document automation, workflow optimization, and intelligent decision-support systems.
Develop, evaluate, and prioritize AI initiatives based on technical feasibility, business value, operational impact, and implementation potential.
Support the development of regulatory-compliant organizational frameworks aligned with current and emerging AI regulations.
Assess manufacturing sites to evaluate their technological maturity, operational readiness, and suitability for AI implementation.
Own programmatic pricing initiatives for partnerships, franchises, networks, and promotions, developing pricing frameworks, intake processes, approval paths, and operational playbooks.
Lead Deal Desk support for product launches by defining pricing guardrails, CPQ and SKU readiness, approval requirements, and seller guidance in collaboration with Product, Finance, and Enterprise Systems.
Develop and deliver pricing enablement programs, including onboarding materials, training sessions, deal-structuring guides, and launch communications.
Track adoption of pricing programs and enablement initiatives across the Sales organization.
Design and implement approval matrix updates and process improvements, establishing clear communication around program changes, risks, and blockers.
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