Lead AI and automation initiatives for DTCC’s Client Interfaces platform, managing cross-functional teams and ensuring reliable, automated onboarding and provisioning processes.
Compensation
Competitive compensation, including base pay and annual incentive
Responsibilities
Manage and direct deep analysis to identify potential failure points and implement controls
Manage and direct analysis of multiple application alert trends
Ensure reviews of runbooks with stakeholders
Collaborate with Client Facing teams to provide answers to application issues
Validate accuracy and timeliness of responses to requests for information
Requirements
Bachelor's degree preferred or equivalent experience
Senior backend engineer responsible for building and maintaining customer-facing AI and LLM products, owning features from discovery to production, and shaping product direction with the founding team.
Locations (4)
United States
Canada
San Francisco, California, United States
Toronto, Ontario, Canada
Compensation
Base salary + meaningful founding-level equity
Responsibilities
Own customer-facing features from user discovery and scoping through backend development, launch, and iteration.
Build reliable LLM agents that reason over large, complex enterprise datasets.
Architect Knowledge Discovery: Design a scalable architecture for enterprise search and knowledge discovery using Glean’s hybrid search capabilities and knowledge-graph techniques. Build semantic layers (metadata, taxonomies, knowledge graphs) and Retrieval-Augmented Generation (RAG) pipelines to ensure the AI Assistant generates accurate, context-rich answers from internal data.
Orchestrate AI Agents: Lead the development and orchestration of intelligent agents using Glean Agents. Define workflows for autonomous tasks (e.g., routing requests, summarizing information) and configure event-driven triggers. Ensure agents always access up-to-date company data to deliver accurate, actionable insights.
Integrate Systems and Data: Connect Glean with the platform’s data sources and applications using APIs, connectors, and custom integration code. Configure out-of-the-box connectors to index all relevant content securely. Work with infrastructure teams to build secure data pipelines, ETL processes, and integration patterns.
Ensure Security & Governance: Implement enterprise-grade security for the Glean deployment. Define data governance policies, permission models, and compliance standards. Align Glean’s configuration with relevant compliance frameworks (SOC 2, GDPR, HIPAA) and enforce audit logging, SSO, and user governance.
Cross-team Collaboration: Serve as a liaison between business stakeholders, product owners, and engineering teams. Gather requirements, translate them into technical specifications, and guide development teams. Provide clear documentation, training, and support for ongoing adoption and maintenance.
Lead technical workstreams for secure AI agents and workloads, combining advisory and engineering to design identity architectures, integrations, and production controls.
Compensation
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. A reasonable estimate of the current range is $105,400 - $207,800. You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Responsibilities
Lead discovery sessions to map user-to-agent-to-tool access paths
Design identity architectures and integrations for AI agents and workloads
Engineer and review token exchange, on-behalf-of access, consent, session controls
Own identity workstreams, manage dependencies and delivery milestones
Lead the vision, strategy, and execution of BCG’s AI-first employee support products AVA and IT Connect, driving enterprise adoption and ROI across global teams.
Responsibilities
Set multi-year vision and strategy for AVA and IT Connect
Turn strategy into integrated roadmap with OKRs
Own ROI and track savings, capacity, and experience gains
Manage cost across initiatives and technology stack
Secure funding and resourcing through business reviews
Requirements
Nice to have: extending AI agents across business functions
Design, build, and deploy production AI use cases: prompt and agent engineering, RAG pipelines, and integrations into enterprise systems
Build against the organization's enterprise AI copilot and LLM platforms (Microsoft Copilot, Google Gemini) and the enterprise data lake
Partner with the Engagement Lead and business stakeholders to translate use‑case requirements into working solutions
Create reusable delivery patterns and templates that accelerate future use‑case builds
Work within data‑handling constraints tied to the ongoing integration program, in partnership with the Data Integration team and the AI Security & Risk Lead
Requirements
Nice to have: Microsoft Copilot Studio
Nice to have: Google Gemini/Vertex AI
Nice to have: manufacturing or industrial domain experience
Lead the design and development of large-scale AI systems that bring cutting-edge AI into production to transform Payment Integrity and Audit solutions.
Compensation
The salary for this position is based on an array of factors unique to each candidate: Such as years and depth of experience, set skills, certifications, etc. We are hiring for different levels and the base salary can range from $180k-$250k+ based on your assessed level.
Responsibilities
Lead development of document processing pipelines capable of annually handling hundreds of millions of documents
Design and implement agentic workflows that review and validate millions of healthcare claims per year
Evolve our agentic ecosystem by driving innovation in prompt development lifecycle
Collaborate across teams to deliver robust, end-to-end AI-powered systems
Address critical infrastructure needs by tracking and reducing tech debt
Requirements
Bachelor’s or Master’s degree in Computer Science or a related field
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