AI Solutions Lead at Lcs in Des Moines, IA | USD128,000-160,000 | Kablio

Role

Description

ai development

solution design

cloud platform

intake management

ai integration

kpi tracking

Hands‑on developing AI/ML solutions on cloud platforms.
Stand up and run intake for AI agents/use cases; maintain a transparent backlog. Drive prioritization decisions ensuring each effort has a clear scope and value.
Lead the AI Community of Practice (COP); publish playbooks/templates; enable safe no‑/low‑code patterns.
Design, build, and scale AI solutions (LLM/agentic applications; ML solutions) with clear exit criteria.
Partner with data science, data engineering, security, and governance to ensure the data, platforms and guardrails are AI-ready.
Define and maintain KPIs (hours saved, adoption/utilization, cycle‑time, quality/error rates, business outcomes)
Conduct discovery with business stakeholders to identify processes ripe for assist/augment/automate outcomes.
Partner closely with IT to integrate AI capabilities (summarization, synthesis, classification) into systems of engagement.

Requirements

bachelor’s

5+ years

ai/ml

rag

llm

python

Bachelor’s degree in Computer Science, Data Science, Machine learning, or related field; or equivalent experience. Graduate degree preferred.
Ability to translate ambiguous business problems into scoped, testable use cases with clear value hypotheses and success criteria.
5+ years designing and building AI/ML products with measurable business impact.
Demonstrated experience building AI agents using both programmatic frameworks (SDK-based, API-driven) and low-code orchestration platforms.
Hands-on experience with retrieval-augmented generation (RAG) architectures, including vector databases, embedding strategies, and retrieval optimization.
Hands on experience with modern LLM/agent frameworks (retrieval/RAG, tool use, reasoning frameworks, prompt design) and ML techniques.
Strong communication; able to tell the story of value to technical and non‑technical stakeholders.
Strong product skills: intake, prioritization stakeholder communication, and value tracking.
Experience partnering closely with data science, data engineering and governance to take solutions end-end.
Practical understanding of ML techniques, experimental design and model evaluation.
Expertise in LLM prompt engineering, tuning and evaluation to tailor models for business needs.
Proficiency with Python and common AI/ML libraries; grounding in AI and MLOps practices.

Benefits

Outstanding advancement opportunities.
Ongoing career development.
Inclusive & collaborative culture.

Training + Development

Information not given or found

Interview process

Information not given or found

Visa Sponsorship

Information not given or found

Security clearance

post-offer background check, including references required.

Company

Overview

Founded in 1971

Company origins

The company was established in 1971, marking the beginning of its journey as a family-owned operator.

$100M Revenue

Annual Revenue

The company generates approximately $100 million in annual revenue through its operations.

140 Communities

Managed Properties

The company manages approximately 140 senior-focused communities nationwide.

40,000 Residents

Serving Residents

The company serves over 40,000 residents across its communities.

As an innovative developer and operator, it handles master planning, new builds, expansions, renovations, and ancillary services.
Typical projects range from continuing care retirement communities to stand-alone assisted-living and memory-care campuses.
Specialisms span residential senior housing, healthcare operations, memory care, assisted living, community development.
Earned national recognition for workplace culture and customer satisfaction, including Gallup and J.D. Power honors.
Unusually, LCS integrates a chef-of-the-year contest across its communities, highlighting its hospitality flair.
Grounded in data, it uses proprietary analytics platforms to drive decisions across its senior-living portfolio.

Culture + Values

15 Culture Drivers

Employee Feedback Survey

Recognized through employee feedback in the Energage survey’s 15 Culture Drivers.

5 Consecutive Years

Top Workplaces USA Award

Earned Top Workplaces USA award for five consecutive years, reflecting consistent high employee engagement.

Committed to fostering an empowering environment for team members to make a difference in seniors' lives.
Built a culture driven by data and analytics to improve metrics.

Environment + Sustainability

No explicit environmental or sustainability strategy, net‑zero target, or disclosures located on public site or LinkedIn.

Inclusion & Diversity

No DEI strategy, gender stats, or inclusion outcomes publicly stated on official site or LinkedIn.

Articles

News & Insights

Careers

Case Studies

Role

Description

ai development

solution design

cloud platform

intake management

ai integration

kpi tracking

Hands‑on developing AI/ML solutions on cloud platforms.
Stand up and run intake for AI agents/use cases; maintain a transparent backlog. Drive prioritization decisions ensuring each effort has a clear scope and value.
Lead the AI Community of Practice (COP); publish playbooks/templates; enable safe no‑/low‑code patterns.
Design, build, and scale AI solutions (LLM/agentic applications; ML solutions) with clear exit criteria.
Partner with data science, data engineering, security, and governance to ensure the data, platforms and guardrails are AI-ready.
Define and maintain KPIs (hours saved, adoption/utilization, cycle‑time, quality/error rates, business outcomes)
Conduct discovery with business stakeholders to identify processes ripe for assist/augment/automate outcomes.
Partner closely with IT to integrate AI capabilities (summarization, synthesis, classification) into systems of engagement.

Requirements

bachelor’s

5+ years

ai/ml

rag

llm

python

Bachelor’s degree in Computer Science, Data Science, Machine learning, or related field; or equivalent experience. Graduate degree preferred.
Ability to translate ambiguous business problems into scoped, testable use cases with clear value hypotheses and success criteria.
5+ years designing and building AI/ML products with measurable business impact.
Demonstrated experience building AI agents using both programmatic frameworks (SDK-based, API-driven) and low-code orchestration platforms.
Hands-on experience with retrieval-augmented generation (RAG) architectures, including vector databases, embedding strategies, and retrieval optimization.
Hands on experience with modern LLM/agent frameworks (retrieval/RAG, tool use, reasoning frameworks, prompt design) and ML techniques.
Strong communication; able to tell the story of value to technical and non‑technical stakeholders.
Strong product skills: intake, prioritization stakeholder communication, and value tracking.
Experience partnering closely with data science, data engineering and governance to take solutions end-end.
Practical understanding of ML techniques, experimental design and model evaluation.
Expertise in LLM prompt engineering, tuning and evaluation to tailor models for business needs.
Proficiency with Python and common AI/ML libraries; grounding in AI and MLOps practices.

Benefits

Outstanding advancement opportunities.
Ongoing career development.
Inclusive & collaborative culture.

Training + Development

Information not given or found

Interview process

Information not given or found

Visa Sponsorship

Information not given or found

Security clearance

post-offer background check, including references required.