Solutions Architect

CapTech is a team of master builders, creators, and problem solvers who help clients grow efficient, successful businesses. We unite diverse skills and perspectives to transform how data, systems, and ingenuity enable each client to advance what’s possible in a changing world.

As perceptive partners, our U.S-based consultants find inspiration in the unknown and enjoy getting our hands dirty solving our clients’ myriad of challenges. Across industries and business goals, we fuse technical depth and analytical prowess with creative savvy to move clients forward. This drive helps each organization use technology, management, and insight to turn ideas into action. Together, we create outcomes that exceed the expected — which is one of the reasons we’ve been on the Inc. 500/5000 list for over a decade.

Overview

We are seeking an experienced Solutions Architect – AI to design, lead, and deliver innovative artificial intelligence solutions for our clients. This role blends deep technical expertise with strong consulting skills, enabling you to translate business challenges into scalable, AI-driven architectures. You will work closely with client stakeholders, delivery teams, and leadership to drive successful outcomes across a variety of industries.

What Success Looks Like

- Delivering scalable, high-impact AI solutions that drive measurable business outcomes

- Building strong client relationships and becoming a trusted advisor

- Contributing to the growth of AI capabilities and offerings within the firm

- Enabling teams through best practices, innovation, and technical leadership

Responsibilities

Client Engagement & Advisory; Partner with client stakeholders to understand business objectives and identify opportunities to leverage AI/ML solutions; Serve as a trusted advisor, guiding clients on AI strategy, roadmap development, and best practices; Lead workshops, discovery sessions, and solution envisioning engagements; Solution Architecture & Design; Design end-to-end AI/ML architectures, including data pipelines, model development, deployment, and monitoring; Define scalable, secure, and high-performing solutions across cloud platforms (AWS, Azure, GCP); Evaluate and recommend tools, frameworks, and platforms for AI development (e.g., LLMs, NLP, computer vision); AI/ML Delivery Oversight; Provide technical leadership across AI initiatives from concept through production; Collaborate with data scientists, engineers, and developers to ensure successful implementation; Establish AgenticOps practices, including CI/CD for models, model versioning, and lifecycle management; Pre-Sales & Business Development; Support sales teams with solutioning, proposals, and client presentations; Develop reusable assets, accelerators, and AI solution offerings; Contribute to thought leadership, whitepapers, and go-to-market strategies; Governance & Best Practices; Ensure responsible AI practices, including ethics, bias mitigation, and compliance; Define architecture standards, design patterns, and governance frameworks; Stay current on emerging AI trends and technologies

Requirements

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field; 10 + years of experience in technology consulting, software architecture, or solution architecture; Hands-on experience designing and delivering AI/ML solutions in production environments; Experience with API design, microservices architecture, and containerization (Docker, Kubernetes); Experience working with Frontier AI models, local and open source models; Experience with cloud platforms (AWS, Azure, or GCP) and their AI/ML services; Proficiency in multiple programming languages; Experience designing data architectures and working with large-scale data platforms; Strong problem-solving and analytical thinking; Excellent communication and stakeholder management skills; Ability to translate complex technical concepts into business value; Leadership and mentoring capabilities; Adaptability in fast-paced, client-facing environments

Nice to have

Familiarity with tools such as LangChain, vector databases, and prompt engineering techniques; Knowledge of data engineering tools (Spark, Kafka, Databricks, Snowflake); AI/ML certifications or cloud certifications (e.g., AWS Certified Machine Learning, Azure AI Engineer); Experience with Legacy Systems and Architectures including SaaS