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Data Strategy Engineer Jobs in Rio Rancho, NM (NOW HIRING)

Senior Applied & Agentic AI Engineer

Albuquerque, NM · On-site

$101K - $139K/yr

... data reconstruction. · Define prompt engineering standards and reusable reasoning templates for consistent, domain-aware outputs. · Oversee embedding strategies, vector indexing architecture ...

Senior Engineer

Albuquerque, NM · On-site

$101K - $139K/yr

Engineering, data science, design, and product all work together directly. There is not a lot of ... Make informed decisions about bundle size, lazy loading, caching, and rendering strategies. Full ...

Cloud Engineer

Albuquerque, NM · Remote

$85K - $95K/yr

AZURE CLOUD ENGINEER POSITION SUMMARY We are seeking a highly motivated Azure Cloud Engineer to ... strategies across Azure environments. * Collaborate with development, production support and data ...

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Data Strategy Engineer information

See Rio Rancho, NM salary details

$41.9K

$122K

$167K

How much do data strategy engineer jobs pay per year?

As of Jun 16, 2026, the average yearly pay for data strategy engineer in Rio Rancho, NM is $122,012.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,700.00 and $129,300.00 per year, depending on experience, location, and employer.

What is the difference between Data Strategy Engineer vs Data Analyst?

AspectData Strategy EngineerData Analyst
Required CredentialsBachelor's/Master's in Data Science, Computer Science, or related fields; certifications in data management or cloud platformsBachelor's in Statistics, Mathematics, or related fields; certifications in data analysis tools
Work EnvironmentCollaborates with data engineers, business strategists, and IT teams to develop data strategiesWorks with data sets to generate reports, dashboards, and insights for business decisions
Employer & Industry UsageUsed in tech, finance, and consulting firms focusing on data-driven strategiesCommon across various industries for operational and marketing insights

The Data Strategy Engineer focuses on designing and implementing data strategies to support business goals, often working on data architecture and governance. In contrast, the Data Analyst primarily interprets data to generate reports and insights. Both roles require strong analytical skills, but the Data Strategy Engineer has a broader scope involving strategic planning and data infrastructure.

What are the 4 pillars of data strategy?

The four pillars of data strategy typically include data governance, data quality, data architecture, and data analytics. For a Data Strategy Engineer, understanding these pillars helps in designing effective data systems, ensuring data integrity, security, and usability across an organization.

What profession makes $400,000 a year?

In the field of data strategy engineering, professionals with extensive experience, advanced skills in data architecture, and certifications in data management can reach or exceed a $400,000 annual salary, especially in senior or leadership roles within large organizations. High compensation often correlates with expertise in data analytics, cloud platforms, and strategic planning.

Is AI replacing data engineers?

AI is transforming the role of data engineers by automating routine tasks such as data cleaning and integration, but it does not replace the need for skilled professionals who design data architectures, manage data pipelines, and ensure data quality. Data engineers are essential for building and maintaining the infrastructure that enables effective AI and analytics solutions. Their expertise in tools like SQL, cloud platforms, and programming languages remains critical in the evolving data landscape.

What engineers make $500,000?

Senior data engineers, machine learning engineers, and software engineers with extensive experience and specialized skills can earn $500,000 or more annually, especially in high-demand industries or companies. Achieving this level often requires advanced certifications, expertise in cloud platforms, and leadership roles within organizations.
Senior Applied & Agentic AI Engineer

Senior Applied & Agentic AI Engineer

Sedgwick

Albuquerque, NM • On-site

$101K - $139K/yr

Other

Posted 24 days ago


Sedgwick rating

7.5

Company rating: 7.5 out of 10

Based on 308 frontline employees who took The Breakroom Quiz

186th of 261 rated insurance


Job description

By joining Sedgwick, you'll be part of something truly meaningful. It's what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there's no limit to what you can achieve.

Newsweek Recognizes Sedgwick as America's Greatest Workplaces National Top Companies

Certified as a Great Place to Work®

Fortune Best Workplaces in Financial Services & Insurance

Senior Applied & Agentic AI Engineer

Job Responsibilities

· Lead the architecture and delivery of enterprise-grade LLM and agentic AI systems that transform claims, risk, and operational workflows.

· Define technical strategy for retrieval-augmented generation (RAG), multi-agent orchestration, and autonomous workflow automation.

· Design and implement advanced agentic systems capable of planning, reasoning, tool selection, execution, reflection, and recovery.

· Architect stateful, memory-aware AI systems that manage long-running claims processes across multiple touchpoints.

· Build multi-agent collaboration models that coordinate coverage analysis, document validation, fraud signals, compliance checks, and decision support.

· Establish orchestration frameworks that manage task routing, context persistence, structured outputs, and failure handling.

· Design secure tool integration layers connecting agents to claims systems, policy platforms, data warehouses, document repositories, and external data services.

· Implement deterministic guardrails, schema validation, and output verification pipelines to reduce hallucination and execution risk.

· Lead development of document intelligence systems leveraging LLMs for summarization, entity extraction, discrepancy detection, and structured data reconstruction.

· Define prompt engineering standards and reusable reasoning templates for consistent, domain-aware outputs.

· Oversee embedding strategies, vector indexing architecture, retrieval optimization, and knowledge grounding approaches.

· Design evaluation frameworks to measure reasoning depth, workflow completion accuracy, hallucination rates, latency, and cost efficiency.

· Implement observability layers that track agent decisions, tool usage, retrieval effectiveness, and drift across models and prompts.

· Drive optimization strategies for token efficiency, caching, batching, and inference scaling.

· Ensure compliance with Responsible AI principles, enterprise governance standards, audit requirements, and regulatory constraints.

· Partner with enterprise architecture, cybersecurity, and data governance teams to define secure deployment patterns.

· Mentor engineers on LLM orchestration patterns, workflow decomposition, and safe agent design.

· Translate executive-level business objectives into scalable AI platform capabilities.

· Lead proof-of-concepts through full production deployment with measurable ROI outcomes.

· Continuously evaluate emerging foundation models, orchestration frameworks, and agent tooling for enterprise readiness.

Qualifications

· Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Engineering, or related discipline.

· 7-10+ years of experience in AI engineering, machine learning systems, or distributed software architecture.

· 3-5+ years designing and deploying LLM-powered systems in production environments.

· Demonstrated experience architecting full agentic AI systems with planning, reflection, memory, and tool execution components.

· Deep expertise in RAG architectures, embedding strategies, vector databases, and retrieval optimization.

· Strong experience designing multi-agent orchestration frameworks and workflow engines.

· Advanced proficiency in Python and enterprise API integration patterns.

· Experience building secure, scalable microservices in cloud-native environments.

· Strong understanding of distributed systems, event-driven architectures, and system reliability principles.

· Experience implementing structured output enforcement, guardrails, and audit logging mechanisms.

· Demonstrated ability to design evaluation and benchmarking frameworks for LLM and agent reliability.

· Experience operating in regulated industries such as insurance, financial services, or healthcare preferred.

· Proven leadership in technical design reviews, architecture governance, and cross-functional collaboration.

· Strong ability to balance innovation with enterprise risk management and operational stability.

Sedgwick is an Equal Opportunity Employer and a Drug-Free Workplace.

If you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, consider applying for it anyway! Sedgwick is building a diverse, equitable, and inclusive workplace and recognizes that each person possesses a unique combination of skills, knowledge, and experience. You may be just the right candidate for this or other roles.

Sedgwick is the world's leading risk and claims administration partner, which helps clients thrive by navigating the unexpected. The company's expertise, combined with the most advanced AI-enabled technology available, sets the standard for solutions in claims administration, loss adjusting, benefits administration, and product recall. With over 33,000 colleagues and 10,000 clients across 80 countries, Sedgwick provides unmatched perspective, caring that counts, and solutions for the rapidly changing and complex risk landscape. For more, see sedgwick.com


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