AI Architect

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 a hands-on AI Architect to design and build customer-facing AI capabilities across its SaaS product portfolio.

This is a highly technical role for someone who can move between architecture and implementation. You’ll design scalable AI systems, prototype new approaches, build reference implementations, and work directly with engineering teams to bring AI capabilities into production.

The work includes agentic systems, personalization, retrieval-augmented generation (RAG), knowledge and context management, evaluation frameworks, and emerging Model Context Protocol (MCP) capabilities. You’ll also help establish reusable AI patterns and technical standards as adoption grows across the organization.

Responsibilities

• Design the architecture for scalable, production-ready AI capabilities across multiple SaaS products.
• Prototype and build AI solutions, reference implementations, and reusable components.
• Design agentic workflows, personalization capabilities, RAG systems, and AI-powered customer experiences.
• Establish technical patterns for prompts, memory, context management, evaluation, knowledge representation, and AI orchestration.
• Integrate AI capabilities into existing .NET, Node.js, Go, and Java platforms.
• Work directly with engineering teams to move AI concepts from experimentation into production.
• Evaluate AI models, frameworks, platforms, infrastructure, and build-versus-buy options.
• Partner with Platform Engineering on AI infrastructure, runtime environments, evaluation systems, and governance.
• Help engineering teams adopt practical AI development patterns and architecture standards.
• Explore emerging capabilities including agent harnesses, MCP, semantic search, knowledge graphs, and personalized content generation.
• Identify and develop AI use cases that create measurable customer and business value.
• Partner with Information Security, Legal, and IT on data privacy, tenant isolation, security, model hosting, and responsible AI practices.
• Contribute technical expertise to AI capability assessments and potential acquisition due diligence.

Qualifications

• 7+ years of software engineering experience, including significant architecture responsibilities.
• Strong hands-on software engineering background with the ability and desire to prototype and develop solutions directly.
• Experience designing, deploying, and scaling production AI or machine learning systems.
• Hands-on experience with modern AI application architecture, including large language models, RAG, agentic systems, memory and context management, and evaluation.
• Experience designing or working with agent orchestration and multi-step AI workflows.
• Experience with vector databases, graph databases, knowledge graphs, ontologies, semantic data models, or similar knowledge representation approaches.
• Ability to integrate AI capabilities into existing software platforms and work across multiple technology stacks.
• Strong architectural judgment, including the ability to evaluate emerging tools and determine when to build, buy, or adapt.
• Strong communication skills and the ability to work collaboratively with software engineers, product teams, security, platform engineering, and technical leadership.
• Comfortable working in a fast-moving SaaS environment where AI technologies and best practices continue to evolve.

Nice-to-Have Skills

• Experience with Python, Node.js, or TypeScript.
• AWS and AWS Bedrock experience.
• Experience with Model Context Protocol (MCP).
• Experience with AI evaluation and observability platforms such as Braintrust, LangSmith, Langfuse, or similar tools.
• Experience building agent harnesses or production agentic systems.
• Background as a Principal Engineer, Staff Engineer, Software Architect, technical consultant, startup engineer, or innovation lab contributor.
• Experience conducting technical due diligence or evaluating acquisition targets.
• Experience in financial services, wealth management, insurance, or another regulated industry.
• Experience building AI capabilities within a high-growth SaaS organization.

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!