# Cleartelligence — AI Engineering Practice Director

## Posting metadata

- Original JD posting: https://www.linkedin.com/jobs/view/4457269856/
- Provider: LinkedIn
- Posting status: Live; public guest endpoint returned HTTP 200 with Apply/Save controls
- Job ID: 4457269856
- Company: Cleartelligence
- Title: AI Engineering Practice Director
- Location: United States
- Work model: Remote; verified by LinkedIn's role-specific Remote label. "United States" is the geographic scope and is not a work-model ambiguity.
- Employment type / seniority: Full-time; Director
- Job function: Engineering and Management
- Industry: Professional Services; IT Services and IT Consulting
- Compensation: $200,000–$250,000 base salary plus annual bonus; other incentives and benefits may apply
- Posting time: LinkedIn displayed “16 minutes ago” at approximately 2:57–3:00 PM EDT on Aug 26, 2026, implying approximately 2:41–2:44 PM EDT
- Applicants: “Be among the first 25 applicants”; exact count unavailable, displayed count below 25 at capture
- Travel: Not disclosed
- Job poster: Jill Austin, Talent Acquisition Specialist, CDR
- Captured / evaluated: 2026-08-26 03:01:53 PM EDT
- Approximate elapsed time since posting at evaluation: 18–21 minutes

## Normalized role mandate

Lead and grow Cleartelligence’s AI consulting practice, converting clients’ existing data and application investments into intelligent, AI-enabled solutions. Serve as a trusted executive technical advisor, expand the firm’s AI offerings, establish delivery standards and reusable accelerators, and build the next generation of AI consultants. The role combines practice strategy, consulting delivery, technical leadership, business development, and people management.

## Responsibilities

### Practice leadership

- Develop and execute the strategic vision and growth strategy for the AI consulting practice.
- Build, lead, and strategically manage a high-performing AI Engineering team, including workforce planning, resource allocation, capacity management, and skills development aligned to client demand.
- Establish delivery methodologies, governance standards, best practices, and reusable AI accelerators.
- Foster innovation, collaboration, technical excellence, and continuous learning.

### Client and technical leadership

- Serve as executive technical advisor on strategic client engagements and AI transformations.
- Guide clients from modern data platforms and application development to scalable enterprise AI.
- Develop AI roadmaps aligned with business objectives, cloud architecture, data strategy, and application modernization.
- Lead across Data Engineering, Application Development, cloud architecture, and AI solution design.
- Evaluate emerging AI technologies and enforce enterprise security, governance, and responsible-AI principles.

### Consulting delivery

- Lead AI engagements from strategy through implementation.
- Define roadmaps, scope, statements of work, and delivery plans with clients.
- Manage delivery quality and risk, consultant utilization, and client satisfaction while improving methodologies.

### Business development

- Partner with Sales and Client Partners to identify opportunities, develop AI strategy, and expand client relationships.
- Represent the firm through executive briefings, events, conferences, and published content.

### People leadership

- Recruit, coach, and develop consulting talent, including performance management and career development.
- Track practice performance, optimize effectiveness, and build a high-performing consulting organization.

## Required qualifications

- Bachelor’s degree in Computer Science, Software Engineering, Information Systems/Science, Data Science, or a related technical field.
- 15+ years leading enterprise technology initiatives, with a strong Data Engineering and modern Application Development foundation and experience leading AI/ML and Generative AI initiatives.
- Experience building high-performing consulting teams.
- Consulting or Professional Services background.
- Proven enterprise solution delivery spanning Data Engineering, cloud-native Application Development, AI, and modern software architecture.
- Experience with scalable data platforms, APIs, distributed systems, and cloud-native applications enabling enterprise AI.
- Deep enterprise AI and Generative AI expertise built on modern data platforms.
- Expertise in LLMs, RAG, AI agents, orchestration frameworks, vector databases, foundation models, and Generative AI.
- Strong experience with AWS, Azure, or GCP.
- Experience with APIs, microservices, CI/CD, DevOps, cloud architecture, and application integration.
- Deep experience in data architecture, engineering, governance, analytics, and enterprise integration.
- Executive advisory experience for legacy data/application modernization and AI adoption.
- Consulting, executive communication, client relationship management, and business development experience.
- Strategic mindset and commitment to responsible AI.

## Preferred qualifications

- Master’s degree.
- Certifications in Databricks, Snowflake, Sigma, and/or Anthropic.

## Management scope

Direct accountability for building and managing AI Engineers and the consulting organization, including recruiting, coaching, performance and career development, workforce/capacity/resource planning, utilization, team effectiveness, and practice performance. The posting does not disclose headcount, manager-of-managers structure, budget, or P&L scope.

## Domain and platform stack

AI consulting and professional services; enterprise AI transformation; Data Engineering; modern/cloud-native application development; data architecture, governance, analytics, and integration; LLMs; RAG; AI agents; orchestration; vector databases; foundation models; Generative AI; APIs; microservices; distributed systems; CI/CD; DevOps; AWS/Azure/GCP; Databricks; Snowflake; Sigma; Anthropic.

## Positioning track

Executive leader — Director-level AI consulting-practice leader with organization building, executive advisory, technical strategy, delivery governance, client development, and people accountability.

## Weighted evidence map

Scoring: 3 = direct/recent/outcome-backed; 2 = direct but older or less measurable; 1 = adjacent/transferable; 0 = unsupported. Weighted maximum is 78 points.

| Requirement | Weight | Evidence score | Weighted points | Keith’s strongest evidence |
|---|---:|---:|---:|---|
| Set AI-practice vision and growth strategy | 3 | 2 | 6 | Established NorthBay’s AI/ML consulting capability and defined IDW’s AI strategy, architecture, and commercialization roadmap; consulting-practice growth metrics are not documented. |
| Build and lead a high-performing AI consulting team | 3 | 3 | 9 | Built NorthBay’s AI/ML capability and led a 24-person remote product team; recruited and technically led an 11-engineer AI organization at IDW. |
| Enterprise AI/GenAI depth across LLMs, RAG, agents, orchestration, and vector databases | 3 | 3 | 9 | Architected AssistX with LLMs, RAG, LangChain, LangGraph, PostgreSQL/PGVector, AI agents, multi-agent patterns, and AWS; delivered 70+ automations across 20+ workflows. |
| Data Engineering, cloud-native applications, and modern architecture | 3 | 3 | 9 | Delivered TriMark’s first AWS data lake across 11 ERPs; built production cloud-native platforms at IDW, MassMutual, NorthBay, SuccessKPI, and DPI. |
| Executive advisory and client relationship leadership | 3 | 3 | 9 | Advised 200+ AWS enterprise customers and multiple C-level stakeholders on AI, ML, data, and cloud adoption; later advised NorthBay enterprise clients. |
| Business development, opportunity creation, SOWs, and account expansion | 3 | 1 | 3 | Adjacent evidence from NorthBay consulting, IDW commercialization, executive demonstrations, partnerships, and acquisition discussions; no direct source evidence for SOW ownership, quota, or consulting-account expansion metrics. |
| Practice operations: capacity, utilization, resource planning, and performance | 2 | 1 | 2 | Strong hiring, performance, delivery planning, and team leadership evidence; consultant utilization and practice-capacity management are not directly documented. |
| Strong public-cloud platform expertise | 2 | 3 | 6 | 15 years of AWS experience, four years at AWS, 200+ advised customers, and multiple production AWS platforms. |
| APIs, microservices, CI/CD, DevOps, and enterprise integration | 2 | 3 | 6 | Direct production evidence across FastAPI/REST, CI/CD, cloud automation, event-driven systems, container platforms, and enterprise integration. |
| Data governance, responsible AI, and enterprise controls | 2 | 3 | 6 | Led cloud engineering across MassMutual Data Privacy and AI Governance initiatives, including governance architecture, transparency, bias, drift, policy automation, and auditability. |

- Earned weighted points: 65 of 78
- Weighted capability coverage: 83.3%

## Fit outcome

**FAIL despite 83.3% capability coverage because the role is centered on GTM and consulting-practice growth responsibilities that conflict with Keith's no-GTM preference. Remote status is verified and is not a failure reason.**

### Hard gaps

1. Business development and consulting-practice growth are core required responsibilities. The role explicitly includes opportunity identification, client expansion, Sales/Client Partner collaboration, SOWs, consultant utilization, and practice growth. Keith has adjacent consulting and commercialization evidence, but his search criteria specify no GTM and the source materials do not establish direct ownership of these required consulting-business-development mechanics.

### Material caveats

- Travel is undisclosed; Keith’s maximum is 5%.
- No exact applicant count is available, although LinkedIn displayed fewer than 25 at capture.
- Preferred Sigma certification/experience is unsupported; the other listed certifications are also not established as held credentials.

### Strongest differentiators

- Recent, hands-on production GenAI platform leadership: 70+ automations across 20+ workflows, delivered in eight months while building and leading an 11-engineer team.
- Unusually strong combination of enterprise AI advisory and implementation: 200+ AWS customers plus multiple production data, governance, cloud, and AI platforms.

## JD/source-resume keyword diagnostic

- Covered: 16 of 20 significant JD terms (80.0%)
- Missing exact phrases in the source resume: practice leadership; business development; application development; microservices
- Interpretation: keyword overlap is strong but does not cure the business-development ownership gap or the role's conflict with Keith's no-GTM preference.

## Artifact metadata

- JD capture: generated and published after validation
- Tailored resume: not generated because the role failed hard gates
- Cover letter: not generated because the role failed hard gates
- LinkedIn connection note: not generated for a FAIL outcome
- Google Drive: not used