AI Architect
At a glance
Mid-level AI Engineering role at Emergent Software. Remote, United States · full-time · no salary stated · we estimate $132,450–$205,151 across the United States.
Emergent Software has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Set the architecture for customer-facing AI features across the product portfolio, then build and scale them
- Create reusable approaches for prompts, memory, context handling, evaluation and AI orchestration
- Prototype AI capabilities and stay hands-on with development and reference implementations
- Help product and platform teams take AI ideas into production through design reviews and engineering support
- Set practices for model hosting, tenant separation, privacy and responsible AI with security and legal partners
What you bring
- At least seven years in software engineering, including substantial architecture and technical leadership work
- A track record of designing, launching and scaling production AI, machine learning, RAG or agent systems
- Hands-on engineering experience and the ability to contribute directly to software development
- Experience with agent orchestration, agent harnesses and MCP initiatives
Who this fits
This suits a hands-on technical leader who can set AI direction while prototyping and contributing to development. The role is fully remote, and applicants must be authorized to work in the US without visa sponsorship.
From the employer
**This is a direct hire for one of our clients. This role is fully remote. Eligible candidates must be authorized to work in the US without visa sponsorship.**
Our client is putting AI at the center of its product strategy and is seeking an experienced AI Architect to lead the architecture, roadmap, and delivery of customer-facing AI capabilities across its SaaS platform portfolio. This is a hands-on leadership role that combines AI strategy, software architecture, and team leadership. The ideal candidate has designed and delivered production AI solutions, led technical direction for AI initiatives, and remains actively involved in architecture, prototyping, and software development. You will guide a growing AI team while driving next-generation capabilities including agentic systems, personalization, MCP initiatives, and AI-powered product innovation.
Responsibilities
AI Architecture & Development
Define the architecture and technical direction for AI capabilities across the product portfolio.
Design and build scalable AI solutions, including agentic workflows, personalization, RAG, knowledge representation, and AI-driven customer experiences.
Establish reusable patterns and standards for prompts, memory, context management, evaluation, and AI orchestration.
Develop prototypes and reference implementations, remaining actively involved in software development.
Integrate AI capabilities across .NET, Node.js, Go, and Java platforms.
Evaluate emerging AI technologies, frameworks, and infrastructure, including build-versus-buy decisions.
Collaboration & Innovation
Partner with Platform Engineering and product teams to move AI capabilities from concept through production.
Provide architectural guidance, design reviews, and hands-on support to engineering teams adopting AI.
Explore new AI use cases and emerging capabilities, including agent harnesses, personalized content generation, and MCP.
Identify practical AI opportunities that create measurable customer and business value.
Contribute to technical due diligence and AI capability assessments for potential acquisitions.
AI Governance & Security
Establish best practices for model selection, hosting, tenant isolation, data privacy, and responsible AI development.
Partner with Legal, Information Security, IT, and Platform Engineering to ensure AI solutions meet enterprise security, compliance, and regulatory requirements.
Qualifications
7+ years of software engineering experience, with significant architecture and technical leadership responsibilities.
Proven experience designing, deploying, and scaling production AI, machine learning, RAG, or agentic systems.
Deep understanding of modern AI architecture, including LLM applications, retrieval-augmented generation (RAG), memory, context management, evaluation frameworks, knowledge graphs, ontologies, and other AI/ML techniques.
Experience with agentic AI, agent orchestration, agent harnesses, and MCP initiatives.
Experience working with graph databases, vector databases, knowledge representation frameworks, and semantic data models supporting AI applications.
Strong hands-on software engineering background with the ability to remain actively involved in development.
Experience leading technical strategy, architecture decisions, and AI roadmaps.
Ability to work across multiple technology stacks and integrate AI capabilities into existing platforms.
Strong communication and collaboration skills with technical and executive stakeholders.
Comfortable operating in fast-paced, evolving SaaS environments.
Nice to Have Skills
Experience designing AI systems leveraging knowledge graphs, ontologies, semantic search, graph databases, and retrieval-augmented generation (RAG) architectures.
Experience with Python, Node.js, or TypeScript.
AWS and AWS Bedrock experience.
Experience with evaluation platforms such as Braintrust, LangSmith, LangFuse, or similar tools.
Background as a Principal Engineer, Staff Engineer, Architect, consultant, startup leader, or innovation lab contributor.
Experience conducting technical due diligence or evaluating acquisition targets.
Financial services, wealth management, insurance, or other regulated industry experience.
Experience supporting AI initiatives within high-growth or private-equity-backed SaaS organizations.
Our Vetting Process
At Emergent Staffing, we work hard to find the best tech candidates capable of developing high quality results for our clients. Here are the steps of our vetting process for this position:
Application (5 minutes)
Online Assessment (40-60 minutes)
Initial Phone Interview (30-45 minutes)
Virtual Interview with Hiring Manager (30-45 minutes)
Final Client Interview (60-90 minutes)
Job Offer!
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