Role: Technical Project Manager - AI, Data & Knowledge Graph Platforms
Location: Mettawa, IL (Hybrid)
Role Overview:
We are seeking an experienced Onsite Technical Project Manager to lead the successful delivery of enterprise AI, Generative AI, Data Engineering, and Knowledge Graph programs.
The successful candidate will serve as the primary onsite delivery leader, partnering closely with customer stakeholders, product owners, technical architects, engineering teams, and offshore delivery organizations to ensure successful program execution.
This role requires a strong combination of technical understanding, project management expertise, stakeholder management, delivery governance, risk management, and cross-functional leadership. The individual must be capable of driving complex programs involving multiple workstreams while ensuring alignment between business objectives, technical architecture, delivery plans, budgets, quality expectations, and customer outcomes.
Key Responsibilities
1. Technical Leadership
Serve as the onsite technical and delivery leader for the program.
Provide clear technical direction across Data Engineering, Knowledge Graph, Neo4j, GenAI, Agentic AI, API, UI, Testing, DevOps, and platform integration streams.
Lead technical discussions with customer architects, engineering leaders, product owners, domain experts, and delivery teams.
Establish a shared technical vision and ensure all workstreams remain aligned with the approved architecture.
Facilitate key technical decisions and help teams resolve implementation challenges and dependencies.
Work closely with technical architects and engineering leads to ensure solution feasibility and delivery readiness.
Mentor technical leads and engineering teams while fostering effective collaboration between onsite and offshore teams.
2. Program and Project Management
Own end-to-end program planning, execution, governance, and delivery.
Develop and manage integrated project plans covering all workstreams.
Define milestones, deliverables, success criteria, schedules, and release plans.
Coordinate activities across business, technical, data, AI, QA, DevOps, and infrastructure teams.
Drive sprint planning, backlog prioritization, roadmap execution, and release governance in collaboration with Product Owners.
Establish delivery governance processes, reporting mechanisms, KPIs, and program dashboards.
Ensure project execution remains aligned to scope, schedule, budget, and quality objectives.
Manage program dependencies across customer teams, vendors, and offshore delivery teams.
Facilitate daily, weekly, and executive-level project governance meetings.
Ensure timely escalation and resolution of delivery risks, issues, and blockers.
3. Knowledge Graph and Data Architecture
Define architecture for integrating structured, semi-structured, and unstructured enterprise data.
Guide teams in ontology, taxonomy, metadata, entity, relationship, and provenance design.
Architect knowledge graph solutions supporting cross-domain discovery, semantic relationships, natural-language querying, and hypothesis generation.
Provide direction on graph data modeling, Cypher or equivalent query generation, indexing, graph analytics, and multi-modal retrieval.
Ensure data lineage, quality, governance, traceability, access control, and lifecycle management are incorporated into the solution.
Drive alignment between ingestion pipelines, curated data models, graph stores, vector stores, search services, APIs, and consuming applications.
Lead the design and adoption of Graph Data Science (GDS) capabilities.
4. Delivery Governance and Risk Management
Establish and run program governance forums with customer and internal stakeholders.
Maintain RAID (Risks, Assumptions, Issues, Dependencies) logs and ensure proactive mitigation.
Track progress across all workstreams and ensure timely completion of committed deliverables.
Identify schedule, resource, technology, and dependency risks early and drive mitigation plans.
Coordinate cross-functional teams to resolve delivery bottlenecks.
Ensure compliance with project governance, quality standards, security requirements, and regulatory expectations.
Monitor program health using defined metrics and provide transparency to stakeholders.
Drive corrective actions when project performance deviates from plan.
Ensure successful readiness for UAT, deployment, production rollout, and operational handover.
5. Resource and Financial Management
Manage resource planning, capacity forecasting, utilization tracking, and onboarding activities.
Coordinate staffing requirements across onsite and offshore teams.
Monitor project budgets, forecasts, burn rate, effort consumption, and financial performance.
Support project budgeting, change requests, statement-of-work management, and scope control.
Track project profitability, revenue milestones, and resource utilization targets.
Ensure delivery commitments are supported with adequate capacity and skills.
Collaborate with leadership to address resource gaps and future staffing needs.
6. Customer and Stakeholder Management
Build trusted relationships with customer technology leaders, business stakeholders, and delivery teams.
Act as the primary onsite point of contact for delivery status, risks, escalations, and overall program health.
Facilitate steering committee meetings, executive reviews, workshops, and project governance sessions.
Communicate project progress, dependencies, budgets, risks, and mitigation plans to customer leadership.
Translate technical challenges into business-impact language for executive stakeholders.
Manage customer expectations and ensure alignment on priorities, scope, and delivery commitments.
Drive stakeholder consensus when competing priorities or conflicting requirements arise.
Demonstrate ownership and accountability for successful project outcomes and customer satisfaction.
Required Technical Skills
Strong experience managing enterprise AI, Data Engineering, Knowledge Graph, Analytics, and cloud-based technology programs.
Good understanding of:
Knowledge Graphs and Graph Databases
Ontology Engineering and Semantic Modeling
Data Engineering and Enterprise Data Platforms
Agentic AI and Generative AI solutions
API-led Integration Architecture
NLP, Enterprise Search, RAG, and Vector Databases
Strong understanding of Agile, Scrum, SAFe, and hybrid project delivery methodologies.
Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.
Experience delivering large-scale data, AI, analytics, or digital transformation programs.
Ability to understand technical architecture, review solution designs, assess risks, and facilitate technical decision-making.
Strong experience with Jira, Azure DevOps, Confluence, project governance tools, and executive reporting.
Familiarity with Python, SQL, Data Engineering, and cloud-native architectures is preferred.
Educational and Experience Requirements
Bachelor''s or Master''s degree in Computer Science, Engineering, Information Systems, Data Science, Business Technology, or a related discipline.
Typically 12-15+ years of overall technology experience.
Minimum 5-8 years of Technical Project Management or Program Management experience leading complex technology programs.
Experience managing AI, Data Engineering, Knowledge Graph, Analytics, Cloud, or Digital Transformation initiatives.
Strong customer-facing experience managing executive stakeholders and global delivery teams.
Proven experience working with geographically distributed onsite and offshore teams.
PMP, PMI-ACP, SAFe, Scrum Master, or equivalent project management certifications are preferred.
Experience in regulated industries such as Life Sciences, Healthcare, Financial Services, or Insurance is preferred.
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