Lead Enterprise AI Architect - Secure GenAI & MLOps

Swingtech; Washington; Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

15 PTO days

11 paid holidays

Medical Insurance (3 options)

Dental Insurance

Vision Insurance

Disability insurance

Life insurance and AD&D

Supplemental Life Insurance

Critical Care and Accident Insurance

Pet Insurance

Employee Assistance Program

401k with company deferral

Annual training budget

Referral bonus

Merit and discretionary bonus

Flexible work arrangements

Job summary

Swingtech seeks a Lead AI Engineer/Architect to serve as the senior technical authority for an enterprise AI engineering program. You will lead AI solution architecture, engineering direction, hands-on delivery, security alignment, and delivery oversight across the AI lifecycle.

You will establish architecture standards, reusable patterns, Responsible AI practices, and security controls for enterprise AI solutions, including Generative AI, LLMs, RAG, agentic AI, MCP, and AI-enabled automation.

Qualifications

• At least seven years of hands-on experience in AI/ML engineering, enterprise architecture, cloud engineering, data engineering, or software engineering.
• Experience must include direct technical delivery of AI-enabled systems.
• At least two years of hands-on experience with Generative AI, LLM integration, Retrieval-Augmented Generation, model evaluation, or agentic AI.

Responsibilities

• Lead architecture, design, integration, deployment, and oversight of secure enterprise AI solutions.
• Provide hands-on technical leadership for AI engineering, development, testing, deployment, and production support.

Skills

AI/ML engineering

Enterprise architecture

Cloud engineering

Data engineering

Software engineering

Tools

MLOps

APIs

Vector databases

Model evaluation

Job description

Swingtech seeks a Lead AI Engineer/Architect to serve as the senior technical authority for an enterprise AI engineering program. You will lead AI solution architecture, engineering direction, hands-on delivery, security alignment, and delivery oversight across the AI lifecycle.

You will establish architecture standards, reusable patterns, Responsible AI practices, and security controls for enterprise AI solutions, including Generative AI, LLMs, RAG, agentic AI, MCP, and AI-enabled automation.