AI Solutions/Enterprise Architect--15 + Years exp--Remote w2 contract

Invovia; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Invovia is seeking a senior AI/ML architect to drive strategic discovery and design of AI-native solutions. You will lead hands-on workshops, align stakeholders, and define scalable architectures that leverage LLMs, RAG, and orchestration of workflows.

You will collaborate with field engineers to accelerate delivery, codify best practices, and influence platform evolution. This role requires deep expertise in GenAI tooling and cloud infrastructure, with a track record of delivering

Qualifications

• 15+ years overall tech experience with 5–7+ years in enterprise AI/ML architecture or field engineering.
• Proven ability to lead cross-functional technical initiatives from conception to delivery.
• Deep knowledge of LLM-based systems, GenAI tooling, and data modeling.

Responsibilities

• Lead strategic discovery workshops to identify high-impact AI opportunities and align stakeholders.
• Architect AI-native solutions using LLMs, RAG, retrieval logic, and workflow orchestration.
• Collaborate with engineers to build, test, and iterate production-grade AI solutions.
• Codify best practices into repeatable frameworks, templates, and modular components.
• Influence customer and executive buy-in through clear storytelling and solution framing.
• Capture deployment feedback to shape product strategy and platform evolution.

Skills

LLM-based architectures

GenAI pipelines

RAG workflows

Cloud & infra fluency

Python & SQL

Leadership & delivery

Tools

LangChain

Semantic Kernel

Terraform

Container tooling

Job description

Lead Strategic Discovery: Identify high-impact AI opportunities by running hands-on workshops and aligning stakeholders.

Architect AI-Native Solutions: Design systems using LLMs, RAG pipelines, retrieval logic, and workflow orchestration.

Accelerate Delivery with Engineers: Collaborate closely with FDSEs to build, test, and iterate functional solutions quickly.

Codify Best Practices: Create repeatable frameworks, reusable templates, and modular components.

Drive Alignment: Influence customer and executive buy-in through clear storytelling and solution framing.

Advocate Field Insights: Capture feedback from deployments to shape product strategy and prioritize platform needs.

Enable Scale: Equip internal teams and customers to expand success through documentation and technical onboarding assets.

What Success Looks Like:

Solution-Ready Build Delivered: You deliver a validated AI solution-ready build within 8–12 weeks that directly addresses a business-critical problem.

Widespread Reuse: Your assets—from prompts to orchestration logic—are leveraged by other teams and codified for scale.

Platform Evolution: Your work contributes to shaping the Now Platform through structured product feedback and architectural influence.

Business Transformation: The AI solution you’ve led results in measurable gains in efficiency, automation, adoption, or satisfaction.

Production Trajectory: Your delivered solution becomes the foundation for scaled production deployment across customer environments.

Trusted Field Partner: Customers and internal stakeholders see you as a strategic, dependable, and technically credible partner.

Qualifications

What You Bring:

Experience: In leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI’s potential impact on the function or industry.

Enterprise Experience: 15+ years of overall experience, with 5–7+ years in enterprise AI/ML architecture, field engineering, or solution consulting. Proven ability to lead initiatives from conception to delivery over at least 3+ years.

Technical Mastery: Strong grasp of LLM-based systems and GenAI pipelines including prompt engineering, retrieval-augmented generation (RAG), orchestration, and data modeling. Experience designing full-stack intelligent workflows.

Cloud & Infrastructure Fluency: Deep hands-on experience with AWS, Azure, or GCP, including use of containers, infrastructure-as-code (Terraform, CloudFormation), and enterprise integration patterns.

Engineering Depth: Proficient in Python and SQL, with working knowledge of GenAI tooling frameworks like LangChain, Semantic Kernel, or similar. Ability to contribute to engineering discussions and code-level decisions.

• Customer & Delivery Leadership: Comfortable operating in ambiguous, high-stakes environments. Experienced in guiding cross-functional technical teams, influencing executive stakeholders, and ensuring clarity from ideation to implementation.

About Invovia:

Invovia is an AI-native engineering services firm headquartered in Pleasanton, California, operating globally across North America and APAC(India). We specialize in Forward Deployed Engineering, AI-accelerated delivery, legacy modernization, and safe agentic architecture — for enterprises that need AI working in production.