Senior AI Prototyping & Solutions Architect

📍 Job Overview

Job Title: Senior AI Prototyping & Solutions Architect

Company: Computer Task Group, Inc (CTG)

Location: Dallas, Texas, United States

Job Type: CONTRACTOR

Category: AI & Machine Learning Solutions Architecture

Date Posted: 2026-08-25

Experience Level: Senior (5-10 years)

Remote Status: On-site

🚀 Role Summary

• This role focuses on the rapid design, development, and delivery of high-impact Proofs of Concept (PoCs) for AI, Generative AI (GenAI), and Agentic AI technologies.

• Responsibilities include building, configuring, and managing autonomous AI agents and intelligent automation workflows, demanding strong AI development lifecycle and MLOps understanding.

• The Senior AI Prototyping & Solutions Architect will partner closely with AI Solution Principals, providing technical expertise and architectural guidance for client engagements and strategy sessions, emphasizing GTM strategy enablement through technical innovation.

• Leveraging Java Full Stack expertise is crucial for integrating experimental AI workflows with robust enterprise systems, requiring a solid grasp of enterprise integration patterns and API development.

📝 Enhancement Note: While the job title and description lean heavily into AI/ML, the request specifies enhancing for Revenue Operations, Sales Operations, and GTM roles. This enhancement will frame the AI/ML aspects through the lens of how they can support and drive operational efficiencies and GTM strategies, focusing on the application of AI/ML for business outcomes rather than pure AI research. The "Contractor" status and 12-month duration suggest a project-focused engagement, likely aimed at accelerating innovation and client solutions within CTG or for their clients.

📈 Primary Responsibilities

• Rapidly design, develop, and deliver high-impact Proofs of Concept (PoCs) showcasing the capabilities of AI, Generative AI (GenAI), and Agentic AI, directly supporting solution development and product innovation.

• Build, configure, and manage autonomous AI agents and intelligent automation workflows, focusing on workflow automation and process optimization through AI.

• Partner closely with the business-focused AI Solution Principal to provide technical expertise and architecture support during client pitches and strategy sessions, acting as a key technical advisor for go-to-market strategy execution.

• Leverage Java Full Stack expertise to integrate experimental AI workflows with robust enterprise systems, ensuring technical feasibility and scalability for future deployments.

• Explore and evaluate emerging AI frameworks, tools, technologies, and architectures to maintain a competitive edge and identify opportunities for operational efficiency gains.

• Translate innovative AI concepts and abstract business goals into functioning technical prototypes and PoCs, demonstrating strong business-to-technical translation skills.

• Focus on technical innovation, architecture, rapid experimentation, and PoC delivery rather than routine project management or operations, aligning with a fast-paced innovation cycle.

📝 Enhancement Note: The responsibilities highlight a strong focus on rapid prototyping and technical innovation. For an operations professional, this translates to understanding how these AI capabilities can be leveraged to improve sales processes, customer engagement, data analysis, and overall business efficiency. The partnership with an AI Solution Principal is key, indicating a need for strong communication and the ability to translate technical possibilities into business value, a critical skill in GTM operations.

🎓 Skills & Qualifications

Education:

• Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, Information Technology, or a related technical field.

• Equivalent combination of education and relevant experience may be considered, emphasizing practical application over formal degrees. Experience:

• Senior-level experience designing and developing AI/ML solutions and technical prototypes, with a focus on solution architecture and proof-of-concept development.

• Demonstrated experience building AI agents, Agentic AI solutions, and/or multi-agent architectures, showcasing expertise in autonomous systems design.

• Hands-on experience developing with Python and modern AI/ML frameworks, essential for AI model development and data science workflows.

• Experience with Java Full Stack development and enterprise application integration, critical for system interoperability and back-end development.

• Experience supporting technical sales, client pitches, or strategy sessions is preferred, indicating a need for strong client-facing communication and business development support.

• Proven ability to rapidly prototype and demonstrate innovative technical solutions, highlighting agile development methodologies and rapid iteration. Required Skills:

• Strong hands-on programming experience with Python and modern AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn), crucial for data science and machine learning implementation.

• Deep expertise in Agentic AI, multi-agent architectures, and building functional AI agents, demonstrating proficiency in advanced AI concepts.

• Solid Java Full Stack development background, including front-end (e.g., Spring Boot, React/Angular) and back-end development, for comprehensive solution building.

• Strong understanding of AI, Generative AI, intelligent automation, and rapid prototyping principles, essential for AI strategy formulation.

• Exceptional ability to translate high-level, abstract business goals into functioning technical prototypes and Proofs of Concept, a core skill for GTM alignment.

• Strong problem-solving skills with an agile, experiment-driven technical mindset, vital for iterative development and innovation.

• Ability to rapidly evaluate and adopt new AI technologies, frameworks, tools, and architectures, crucial for staying current in a fast-evolving field.

• Strong technical architecture and enterprise integration skills, necessary for scalable and robust system design. Preferred Skills:

• Experience with cloud platforms (AWS, Azure, GCP) for AI/ML deployments.

• Knowledge of containerization technologies (Docker, Kubernetes).

• Familiarity with MLOps practices and tools.

• Experience with natural language processing (NLP) and large language models (LLMs).

• Understanding of data engineering principles and pipelines.

📝 Enhancement Note: The emphasis on "senior-level" and specific technical stacks like Python, Java Full Stack, and AI/ML frameworks indicates a need for experienced technical professionals. For operations roles, this translates to candidates who can not only understand these technologies but also articulate their business value and potential impact on sales processes, customer experience, and operational efficiency. The preference for technical sales support experience is a strong indicator of the role's client-facing and GTM aspects.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrate successful design and development of AI/ML solutions and technical prototypes through concrete case studies.

• Showcase projects involving AI agents, Agentic AI solutions, or multi-agent architectures, highlighting problem-solving approaches and technical implementation.

• Provide examples of Python and Java Full Stack projects, illustrating code quality, architectural design, and integration capabilities.

• Include examples of translating abstract business goals into functioning technical prototypes, emphasizing the process of innovation.

• Present projects that highlight strong technical architecture and enterprise integration skills, demonstrating the ability to build scalable and robust systems. Process Documentation:

• Document the workflow for rapid prototyping, from ideation and technical feasibility assessment to development and demonstration.

• Outline the process for building and managing autonomous AI agents and intelligent automation workflows, including testing and deployment strategies.

• Detail the methodology for evaluating and adopting new AI technologies, frameworks, tools, and architectures.

• Illustrate the collaboration process with business stakeholders (e.g., AI Solution Principals) in client pitches and strategy sessions, showing how technical expertise supports GTM efforts.

📝 Enhancement Note: For a role focused on prototyping and solutions architecture, a portfolio is critical. It should go beyond just listing technologies and demonstrate the candidate's ability to apply these technologies to solve business problems. For operations professionals, this means highlighting how their work has led to measurable improvements, such as increased sales velocity, enhanced customer insights, or streamlined operational workflows. The emphasis on "rapid experimentation" suggests a need to showcase iterative development processes.

💵 Compensation & Benefits

Salary Range:

• Given the Senior AI Prototyping & Solutions Architect role in Dallas, Texas, with a focus on advanced AI technologies and a 12-month contract, a competitive hourly rate or equivalent annual salary range is expected. Based on industry benchmarks for senior technical roles in AI/ML and full-stack development in a major tech hub like Dallas, an estimated range of $90 - $140 per hour (or an equivalent annual salary of $187,200 - $291,200 for a full-time equivalent) is reasonable. This estimate considers the specialized skill set, senior experience level, and the contract nature of the position. Benefits:

• As a contractor position, benefits may vary. Typical contractor benefits through agencies or directly with CTG might include:

• Health, Dental, and Vision Insurance (potentially through a third-party provider).

• 401(k) plan options (may be available depending on contract terms and duration).

• Paid Time Off (PTO) or holiday pay (often accrued or provided based on contract agreement).

• Access to CTG's internal training and development resources.

• Potential for contract extension or conversion to a full-time role based on performance and business needs. Working Hours:

• Standard full-time working hours, typically 40 hours per week.

• Flexibility may be offered based on project needs and client demands, but the role is specified as on-site, implying a commitment to office presence during core business hours.

📝 Enhancement Note: The salary range is estimated based on typical market rates for senior-level AI/ML and Full Stack Architects in Dallas, TX, considering the contract nature and specialized skills. It's important to note that CTG's specific compensation package will depend on the ultimate client agreement and the contractor's experience. Benefits for contractors can differ significantly from full-time employees and should be clarified during the offer stage.

🎯 Team & Company Context

🏢 Company Culture

Industry: Information Technology and Services, Staffing and Recruiting. CTG, a Cegeka company, operates within the IT solutions and consulting space, focusing on enhancing clients’ digital agility.

Company Size: CTG (as a Cegeka company) has over 9,000 team members in over 15 countries, indicating a large, global organization with significant resources and reach. This size provides stability and a broad network of expertise.

Founded: CTG was founded in 1966, bringing over 60 years of experience to its clients, emphasizing a long-standing reputation for reliability and results.

Team Structure:

• This role is likely part of a specialized AI or innovation team within CTG, possibly a dedicated practice area or a project-specific team formed for client engagements.

• The Senior AI Prototyping & Solutions Architect will report to a project lead or a practice manager, working closely with an AI Solution Principal and potentially other technical specialists.

• Cross-functional collaboration is a hallmark of this role, involving close partnerships with business stakeholders, client IT teams, and potentially sales and account management teams to understand needs and deliver solutions. Methodology:

• The team likely employs agile and iterative methodologies for rapid prototyping and PoC development, focusing on quick feedback loops and continuous improvement.

• Data-driven decision-making is expected, leveraging performance metrics from prototypes and PoCs to inform further development and client strategy.

• Emphasis on innovation and experimentation, encouraging the exploration of new AI technologies and their application to solve complex business challenges.

Company Website: www.ctg.com

📝 Enhancement Note: CTG's culture, as described, emphasizes being a reliable, results-driven partner and fostering a workplace where employees are encouraged to grow. For operations professionals, this means a focus on delivering tangible value to clients and a supportive environment for skill development. The global presence of CTG and Cegeka suggests opportunities to work on diverse projects and gain exposure to different markets.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned at a senior technical level, focusing on specialized AI/ML prototyping and solutions architecture. While not a traditional "operations" role in the sense of managing ongoing business processes, it directly contributes to operational efficiency and GTM strategy enablement through innovation. It represents a pathway for highly technical individuals to influence business outcomes.

Reporting Structure: The Senior AI Prototyping & Solutions Architect will likely report to a Project Manager, Innovation Lead, or a Practice Director within CTG. They will collaborate closely with AI Solution Principals and potentially client-side technical and business teams.

Operations Impact: The primary impact of this role is enabling clients and CTG to leverage cutting-edge AI technologies for competitive advantage. This includes accelerating innovation cycles, demonstrating the value of AI for business processes (e.g., sales automation, customer service enhancement, data analysis), and providing technical foundations for future operational improvements.

Growth Opportunities:

• Specialization: Deepen expertise in specific AI domains such as Generative AI, Agentic AI, or specific industry applications, becoming a recognized subject matter expert.

• Leadership: Transition into technical leadership roles, managing teams of AI engineers and architects, or moving into AI Solution Principal roles to drive client strategy.

• Cross-Functional Exposure: Gain experience in technical sales, client relationship management, and strategic consulting by working closely with GTM teams and clients.

• Skill Expansion: Develop broader architectural skills across different technology stacks and cloud platforms, enhancing overall solution design capabilities.

📝 Enhancement Note: For an operations-focused individual, this role offers a unique opportunity to bridge the gap between advanced technology and business application. Growth could involve moving into roles that more directly manage operational transformations powered by AI, or into leadership positions that define the strategic direction of AI adoption within organizations. The contract nature might also lead to opportunities to work with various clients, broadening exposure.

🌐 Work Environment

Office Type: The role is explicitly stated as "On-site" in Dallas, TX. This implies a traditional office environment where collaboration and in-person interaction are expected.

Office Location(s): Dallas, Texas, specifically within the 75201 postal code area. This location is in a major metropolitan hub, likely offering good accessibility and proximity to business districts.

Workspace Context:

• The workspace is expected to be collaborative, facilitating interaction with colleagues, including the AI Solution Principal and other technical team members.

• Access to necessary development tools, hardware, and potentially cloud environments for rapid prototyping and experimentation will be provided.

• Opportunities for direct engagement with project teams and stakeholders, fostering a dynamic and interactive work setting. Work Schedule:

• The standard working hours are 40 hours per week. While the role is on-site, some flexibility might be available depending on project deadlines and CTG's client agreements, but a consistent presence during business hours is generally expected.

📝 Enhancement Note: The "on-site" requirement in Dallas suggests a need for candidates who are comfortable working within a physical office setting and engaging directly with colleagues and potentially clients. This environment can be conducive to rapid brainstorming and problem-solving, which are key to the prototyping nature of this role.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A review of your resume and application to assess technical qualifications and experience against the job requirements. Emphasis will be placed on your Python, Java, AI/ML, and prototyping experience.

• Technical Interview(s): In-depth discussions focusing on your technical skills, architectural design principles, and experience with AI/ML frameworks and agentic AI. Expect questions about your approach to rapid prototyping and enterprise integration.

• Portfolio Review/Case Study: You will likely be asked to present examples from your portfolio showcasing your ability to design, develop, and deliver AI/ML solutions and PoCs. Prepare to discuss specific projects, your role, the technical challenges, and the outcomes.

• Behavioral/Situational Interview: Assessment of your problem-solving skills, agile mindset, ability to translate business goals into technical solutions, and collaboration style, particularly in a client-facing context.

• Final Interview: May involve meeting with senior leadership or the AI Solution Principal to discuss strategic alignment and cultural fit.

Portfolio Review Tips:

• Quantify Impact: For each project, clearly articulate the business problem, your technical solution, and any measurable outcomes (e.g., efficiency gains, improved accuracy, speed of delivery).

• Showcase Process: Detail your approach to rapid prototyping, including how you iterate, test, and integrate solutions. Highlight your ability to translate abstract ideas into tangible prototypes.

• Technical Depth: Be prepared to discuss your architectural decisions, technology choices (Python, Java, AI frameworks), and integration strategies.

• Agentic AI Focus: Highlight any experience with building AI agents or multi-agent systems, explaining the architecture and functionality.

• Conciseness: Select 3-5 of your most relevant and impactful projects to present concisely.

Challenge Preparation:

• Be ready for potential technical challenges that might involve a short coding exercise in Python or Java, or a design problem related to AI architecture or agent development.

• Practice articulating technical concepts clearly and concisely, as you'll need to explain complex AI solutions to both technical and non-technical stakeholders.

• Prepare to discuss how you would approach building a PoC for a given business problem, demonstrating your rapid experimentation mindset.

📝 Enhancement Note: The interview process will heavily scrutinize technical expertise, particularly in AI/ML and full-stack development. A strong portfolio demonstrating practical application, rapid prototyping skills, and the ability to deliver functional PoCs is paramount. For candidates with an operations background, emphasizing how their AI/ML projects have driven business value and operational efficiencies will be key.

🛠 Tools & Technology Stack

Primary Tools:

• Programming Languages: Python (essential for AI/ML), Java (essential for Full Stack and enterprise integration).

• AI/ML Frameworks: TensorFlow, PyTorch, scikit-learn, Keras, and other modern libraries for machine learning and deep learning.

• Generative AI & Agentic AI Tools: LangChain, OpenAI API, Hugging Face, or similar platforms for building LLM-powered applications and AI agents.

• Full Stack Development: Java frameworks (e.g., Spring Boot), front-end technologies (e.g., React, Angular, Vue.js), RESTful APIs, microservices architecture.

Analytics & Reporting:

• Data Science Libraries: Pandas, NumPy for data manipulation and analysis within Python.

• Visualization Tools: Matplotlib, Seaborn, Plotly for creating visualizations of AI model performance and prototype results.

• Cloud-based Analytics: Services like AWS SageMaker, Azure ML, Google AI Platform for model training, deployment, and monitoring.

CRM & Automation:

• While not explicitly stated as a primary focus, understanding how AI prototypes can integrate with or enhance CRM systems (e.g., Salesforce, Dynamics 365) and automation platforms (e.g., UiPath, Automation Anywhere) would be beneficial for demonstrating business impact.

• Cloud Platforms: Experience with AWS, Azure, or GCP for deploying, scaling, and managing AI workloads.

• Containerization: Docker, Kubernetes for application packaging and orchestration.

📝 Enhancement Note: Proficiency in Python and Java, along with modern AI/ML and Generative AI frameworks, is non-negotiable. The ability to integrate these AI capabilities into enterprise systems using Java Full Stack expertise is a key differentiator. Candidates should be prepared to discuss their experience with specific tools and how they leverage them for rapid prototyping and solution architecture.

👥 Team Culture & Values

Operations Values:

• Innovation & Experimentation: A strong drive to explore new technologies and build novel solutions, embracing a "fail fast, learn faster" mentality.

• Technical Excellence: Commitment to high-quality code, robust architecture, and efficient system design.

• Business Impact: A focus on delivering solutions that provide tangible business value and drive client success.

• Collaboration: Working effectively with cross-functional teams, sharing knowledge, and supporting colleagues.

• Agility: Adaptability to changing requirements and technologies, with a focus on rapid delivery.

Collaboration Style:

• Highly collaborative, involving close partnership with AI Solution Principals, other technical experts, and client stakeholders.

• Emphasis on clear communication, active listening, and constructive feedback to ensure alignment and drive project success.

• A proactive approach to knowledge sharing, contributing to a culture of continuous learning and improvement within the team.

📝 Enhancement Note: The culture appears to be fast-paced, innovation-driven, and client-focused. For operations professionals, this means being comfortable with ambiguity, embracing new technologies, and understanding how technical solutions can directly impact business performance and client relationships. The emphasis on collaboration suggests a team environment where contributions are valued and shared.

⚡ Challenges & Growth Opportunities

Challenges:

• Rapid Pace of AI Evolution: Keeping up with the constantly evolving landscape of AI, GenAI, and agentic technologies requires continuous learning and adaptation.

• Translating Abstract Concepts: Effectively bridging the gap between high-level business needs and concrete, functional technical prototypes can be challenging.

• Integration Complexity: Seamlessly integrating experimental AI workflows with diverse and potentially legacy enterprise systems requires strong architectural and integration skills.

• Proof of Concept to Production: Demonstrating the viability of a PoC while acknowledging the path to production readiness and scalability.

Learning & Development Opportunities:

• Cutting-Edge Technology: Direct exposure to and hands-on experience with the latest advancements in AI, GenAI, and agentic systems.

• Cross-Functional Skill Development: Opportunities to enhance skills in technical sales support, client consulting, and strategic architecture.

• Industry Exposure: Working with a variety of clients across different industries, providing broad exposure to diverse business challenges and AI applications.

• Professional Development: CTG likely offers access to training, certifications, and internal knowledge-sharing sessions to support continuous learning in AI and related fields.

📝 Enhancement Note: The primary challenge is the dynamic nature of AI. The growth opportunities lie in becoming a specialist in emerging AI fields and gaining broad experience across different client environments, which can significantly enhance one's profile for future roles in AI strategy and implementation, including those that drive operational transformation.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you translated a complex business requirement into a functional AI prototype. What was your process?" (Focus on your methodology, technical choices, and how you demonstrated value.)

• "How would you approach building a PoC for an AI agent designed to automate lead qualification for a sales team?" (Demonstrate your understanding of agentic AI, Python/Java development, and potential integration points.)

• "Discuss your experience with integrating AI models or workflows into enterprise systems. What were the key challenges and how did you overcome them?" (Highlight your enterprise integration skills and understanding of system architecture.) Company & Culture Questions:

• "What interests you about CTG and this specific role focused on AI prototyping?" (Showcase your understanding of CTG's mission and your passion for AI innovation.)

• "How do you stay current with the rapidly evolving AI landscape?" (Emphasize continuous learning and your proactive approach to skill development.)

• "Describe your experience working in a fast-paced, experimental environment." (Highlight your agile mindset and ability to thrive under pressure.) Portfolio Presentation Strategy:

• Structure: For each project, clearly outline: Problem, Solution (your technical approach), Technologies Used (Python, Java, AI frameworks), Your Role & Contributions, and Results/Impact (quantifiable if possible).

• Demonstrate Rapid Prototyping: Show how you iterated on designs, quickly developed functional components, and gathered feedback.

• Highlight AI Agent/GenAI Experience: If applicable, showcase specific examples of building agents or leveraging GenAI, detailing the architecture and capabilities.

• Technical Architecture: Be prepared to explain the architectural decisions behind your prototypes and how they address scalability and integration.

📝 Enhancement Note: Candidates should prepare to articulate their technical expertise with specific examples, focusing on their ability to rapidly prototype and deliver functional AI solutions. The interview will assess not only technical skills but also problem-solving acumen and the capacity to translate business needs into actionable technical designs. For operations professionals, framing AI's impact on business efficiency and GTM goals will be crucial.

📌 Application Steps

To apply for this operations-aligned AI Prototyping & Solutions Architect position:

• Submit your application directly through the CTG careers portal using the provided link.

• Customize Your Resume: Tailor your resume to highlight your most relevant experience in Python, Java Full Stack development, AI/ML, Generative AI, Agentic AI, and rapid prototyping. Use keywords from the job description.

• Prepare Your Portfolio: Curate 3-5 strong examples of AI/ML solutions, prototypes, or agent development projects. Be ready to articulate the problem, your solution, the technologies used, and the outcomes. Focus on projects that demonstrate rapid development and business impact.

• Research CTG and Cegeka: Understand CTG's mission, values, and recent work in AI. Familiarize yourself with their client-centric approach and commitment to digital agility.

• Practice Technical Explanations: Prepare to clearly and concisely explain complex AI concepts, your architectural decisions, and the functionality of your prototypes. Practice presenting your portfolio with a focus on business value and operational efficiency.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.