AI First Engineering Consultant

Role Summary :

Help launch our new Engineering Advisory & Consulting practice that delivers 6- to 8-week, outcome-focused assessments for U. healthcare-technology clients.

You'll uncover high-value improvements by combining value-stream mapping, time-and-motion analysis, and AI-enabled process mining with design-thinking workshops.

The goal : identify, size, and roadmap Generative- and Agentic-AI interventions that eliminate TIMWOOD wastes and measurably boost engineering speed, quality, and cost efficiency.

Key Responsibilities :

Phase What You'll Do :

1. Engagement :

- Setup - Define scope, baseline KPIs, and success criteria (lead time, DORA metrics, escaped defects, etc.) - Align with multi-location, cross-functional healthcare stakeholders (engineering, product, security, compliance, clinical informatics)

2. Current-State Assessment :

- Facilitate value-stream mapping (VSM) sessions across the SDLC - Run time-and-motion studies to capture cycle times and wait states - Use AI-based process-mining / task-mining tools to surface hidden TIMWOOD wastes (Transportation, Inventory, Motion, Waiting, Over-production, Over-processing, Defects)

3. Opportunity Analysis :

- Quantify waste in $$ and hours; prioritize by ROI and feasibility - Apply AI/ML techniques (e.g., predictive quality, code-gen, test-gen, infra-as-code) to eliminate or automate wasteful steps - Model future-state capacity gains and quality uplift

4. Solution Design :

- Lead design-thinking workshops; co-create AI-infused future workflows - Define guardrails for responsible AI (HIPAA, PHI, IP, model governance) - Produce reference architectures and phased pilot plans

5. Executive Read-Out :

- Deliver an outcome-driven roadmap with business-case financials, KPI targets, and change-management strategy - Present findings to C-suite; facilitate decision workshops

6. Advisory & Enablement :

- Support pilot kickoff, vendor/tool selection, and internal capability building - Mentor client teams on lean-AI operating models and continuous-improvement loops

Required Qualifications :

Experience :

- 12 to 15 years in software engineering / DevOps, including 5+ years leading productivity or transformation programs.

Healthcare Domain :

- Solid background with U.S. payers, providers, or health-tech platforms; working knowledge of HIPAA, HITRUST, and FDA/ISO software-quality regulations.

Lean & Value Excellence :

- Hands-on mastery of Value-Stream Mapping, Time-and-Motion Study, Value Analysis, and TIMWOOD waste elimination.

- Demonstrated ability to convert findings into quantified business outcomes (cycle-time reduction, $ savings, FTE redeployment).

AI Expertise :

- Practical experience applying GenAI and Agentic-AI in engineering : code-gen, test-gen, doc-gen, infrastructure automation, conversational agents.

- Deep appreciation of limitations (hallucination, prompt injection, cost models, context size) and mitigation strategies.

Consulting Skill Set :

- Structured interviewing, hypothesis-driven analysis, executive storytelling, and workshop facilitation across multi-site, multi-skilled, heterogeneous teams.

Technical Breadth :

- Cloud-native DevSecOps (Azure/AWS), CI/CD, Infrastructure-as-Code, microservices, data platforms (e.g., Databricks), observability, and value-stream management tooling (e.g., Planview, ServiceNow VSM, Celonis).

Communication & Presence :

- Exceptional written/verbal skills; able to energize and influence engineering leaders, clinicians, and executives alike.

Preferred Qualifications :

- Lean Six Sigma Black Belt, SAFe VSM Practitioner, or equivalent.

- Track record publishing or speaking on AI-driven engineering or healthcare innovation.

- Experience deploying AI in regulated or validated environments (21 CFR Part 11, GxP).

- Advanced degree in Computer Science, Data Science, or Healthcare Informatics.

Soft-Skill & Personality Traits :

- Outcome-Obsessed : Relentlessly focuses on measurable value delivery.

- Dynamic & Empathetic : Inspires change while respecting clinical and compliance realities.

- Systems Thinker : Connects technology, process, and people into a coherent strategy.

- Continuous Learner : Stays ahead of rapid AI and lean-engineering advancements.

Travel & Work Style :

- Travel 25 to 40 % within the U.S. for onsite assessments and co-creation workshops.

- Operate in a hybrid model; adept with Miro, Figma, Confluence, Teams, and value-stream management dashboards