AI Engineer

Cloud Analytics Technologies, LLC; Dallas (TX); On-site; USD 89,000 - 126,000; Full time

Job summary

Cloud Analytics Technologies, LLC in Dallas, TX seeks an AI Engineer to partner with business teams, embedding within domains to deliver AI-driven automation and measurable outcomes. This role blends hands-on coding, solution architecture, and customer-facing execution to turn AI potential into production value across cloud platforms and enterprise systems.

The ideal candidate has 4–8 years in AI-led engineering or related roles, with strong data-driven problem solving, API/databases experience,

Qualifications

• 4–8 years of AI led engineering, implementation, product, consulting, or customer-facing tech roles.
• AI proficiency is mandatory; candidates may come from software, data science, UX, or related fields with hands-on experience.
• Daily AI tool usage, demonstrable code contributions, and documented token usage.
• Strong analytical thinking and ability to derive AI solutions from data to solve business problems.
• Experience with APIs, databases, cloud services, authentication, integrations, and deployment.
• Experience with Data and analytics platforms; comfortable with structured and unstructured data.
• Experience with GenAI, LLMs, RAG, agents, AI workflow automation, prompt engineering, model integration.
• Cloud experience across AWS, Azure, or Google Cloud.
• Good communication, adaptability, and problem-solving in ambiguous environments.

Responsibilities

• Embed with business and engineering teams to own AI outcomes within a defined business domain.
• Build and deliver AI solutions hands-on; this is an execution role, not an advisory role.
• Convert AI potential into production value through code-first delivery and active repository contributions.
• Understand business processes, pain points, systems, data flows, and success metrics.
• Translate problems into MVPs, integrations, automations, and production-ready solutions.
• Build across APIs, databases, cloud platforms, workflow tools, enterprise systems, and AI/GenAI technologies.
• Own the journey from discovery to working solution, rapidly proving business value through pilots and POCs.
• Integrate with enterprise platforms, data systems, workflows, collaboration tools, and third-party APIs.
• Document architectures, implementation playbooks, reusable components, and customer-specific solution guides.
• Feed field learnings into product roadmap, accelerators, and go-to-market propositions.

Skills

AI engineering

Data analytics

Cloud computing

APIs integration

Problem solving

Tools

Salesforce

Jira

Rally

Oracle

ServiceNow

Microsoft Dynamics

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title: AI Engineer
Location: Dallas , TX Duration: 12 Months + Extension
Bill Rate: $78/hour
Job Type: W-2, 1099, C2C
Client: To Be Discussed Later
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD
Job Description :
Role Overview

We are looking for a Forward Deployed Engineer (FDE) who partners directly with business teams to identify high-value problems and deliver AI-led automation and innovation under centralized council oversight.

An FDE in UHG is an empowered AI builder embedded within business units to understand real-world context, build practical solutions, and drive measurable AI driven outcomes.

The role blends hands‑on engineering, solution architecture, product thinking, consulting, and customer‑facing execution.

Key Responsibilities :

1. Business Embedding and Outcome Ownership

• Embed with business and engineering teams to own AI outcomes within a defined business domain.
• Build and deliver AI solutions hands‑on; this is an execution role, not an advisory role.
• Convert AI potential into production value through code‑first delivery and active repository contributions.

2. Problem Discovery and Solution Design

• Understand business processes, pain points, systems, data flows, and success metrics.
• Translate problems into MVPs, integrations, automations, and production‑ready solutions with an ownership mindset
• Build across APIs, databases, cloud platforms, workflow tools, enterprise systems, and AI/GenAI technologies.

3. Rapid Prototyping and Value Validation

• Own the journey from discovery to working solution, rapidly proving business value through pilots and POCs

4. Integration, Adoption, and Scale

• Integrate with enterprise platforms, data systems, workflows, collaboration tools, and third‑party APIs.
• Document architectures, implementation playbooks, reusable components, and customer‑specific solution guides.
• Feed field learnings into product roadmap, accelerators, and go‑to‑market propositions.

Required Skills and Experience

• 4–8 years of experience in AI led engineering, implementation, product, consulting, or customer-facing technology roles.
• AI proficiency is mandatory; candidates may come from software engineering, data science, UX, or related domains with proven hands on experience.
• Daily AI tool usage, demonstrable code contributions, and documented token usage.
• Strong analytical thinking and expertise in effectively utilizing data to derive AI solutions to solve business problems.
• Strong understanding of APIs, databases, cloud services, authentication, integrations, and deployment.
• Experience in Data and analytics platforms.
• Comfortable with structured and unstructured data.
• Experience with GenAI, LLMs, RAG, agents, AI workflow automation, prompt engineering, model integration and model training.
• Cloud experience across AWS, Azure, or Google Cloud.
• Good communication, adaptability, and problem-solving in ambiguous environments.

Good to Have

• Knowledge of ML algorithms, model building, deployment, deep learning, and NLP.
• Experience integrating with Salesforce, Jira, Rally, Oracle, ServiceNow, Microsoft Dynamics or similar platforms.
• Familiarity with data engineering, ETL/ELT pipelines, BI dashboards, analytics, and reporting workflows.

Healthcare exposure, especially contact centers, claims automation, finance, or technology services

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.