Technical Account Manager -
AI Solutions

Job Title: AI Solutions Consultant

 

Location:

[Location] (Opportunities for remote/hybrid/flexible work available)

 

Reports to:

Director or Head of AI, Data Science, or Advanced Analytics

 

Role Purpose

At [Company Name], we specialize in providing Artificial Intelligence solutions and services that address a wide spectrum of industry needs. In this position, you will help guide our clients through the complete life cycle of AI implementations—starting with the identification of use cases, moving through technical feasibility, and concluding with fully operationalized solutions. This role combines strategic thinking, hands-on technical acumen, and the ability to translate complex processes into clear business outcomes.

 

Company Overview

[Company Name] is a technology-focused organization in the [Industry] sector, known for delivering high-impact results in the AI and Machine Learning arena. We are committed to ethical innovation, collaborative problem-solving, and continuous professional development. Named as an industry leader by multiple publications, we pride ourselves on our team-driven culture and forward-looking solutions that address real-world challenges. Our environment values creativity, knowledge-sharing, and the application of advanced methods to generate lasting benefits for our clients.

 

Key Responsibilities

• Client Engagement & Discovery

  • Conduct detailed assessments with clients to clarify AI project goals, success criteria, and resource needs.

  • Present possible AI use cases that align with each client’s specific objectives, identifying both benefits and potential roadblocks.

• Solution Architecture & Design

  • Collaborate with data scientists, data engineers, and software developers to create robust AI solution designs.

  • Oversee the mapping of AI workflows, from data ingestion and model development to final deployment.

• Project Coordination & Delivery

  • Manage timelines, budgets, and resource allocation to ensure on-time, high-quality deliverables.

  • Serve as the primary point of contact for stakeholders, addressing technical and strategic queries.

• Technical Oversight & Best Practices

  • Guide the application of frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and relevant data-processing libraries.

  • Recommend appropriate development standards and version control practices to maintain model integrity.

  • Review code, data pipelines, and documentation to confirm compliance with organizational and industry standards.

• Performance Monitoring & Optimization

  • Set up measurement criteria to gauge AI model performance and interpret results in the context of client objectives.

  • Suggest enhancements, additional training data, or alternative algorithms to increase model accuracy and reliability.

• Knowledge Sharing & Training

  • Lead client workshops, offering educational materials that clarify AI concepts and best practices.

  • Mentor internal team members, fostering cross-functional collaboration and the exchange of AI expertise.

• Market & Technology Awareness

  • Track developments in AI technologies, such as new machine learning algorithms, data platforms, and emerging tools.

  • Propose innovative methods or technologies that enhance the breadth and quality of solutions offered to clients.

 

Required Skills and Qualifications

• Education & Certification

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related discipline.

• Technical Competencies

  • Practical experience with machine learning, deep learning, natural language processing, or data analytics.

  • Skilled with Python or R, including libraries (NumPy, pandas, scikit-learn, and others) used in AI development.

  • Knowledge of cloud environments (AWS, Azure, GCP) for deploying and managing AI models at scale.

  • Proficiency in handling version control tools (e.g., Git) and containerization frameworks (e.g., Docker).

• Consulting & Stakeholder Management

  • Prior experience in a client-facing or consulting role, demonstrating an ability to distill complex technical insights into actionable business recommendations.

  • Strong project leadership, capable of coordinating between multiple stakeholders and interdisciplinary teams.

• Communication & Collaboration

  • Proven ability to communicate with both technical and non-technical audiences, ensuring alignment on objectives and outcomes.

  • Clear, concise writing skills for documentation, presentations, and proposals.

• Analytical & Problem-Solving Mindset

  • Talent for diagnosing business issues, designing data-driven solutions, and evaluating performance metrics.

  • Capacity to suggest adjustments in models or processes based on findings and changing requirements.

 

Preferred Attributes

• Familiarity with advanced AI topics such as reinforcement learning, time series forecasting, or computer vision.

• Experience with MLOps practices, including automated model deployment, monitoring, and updates.

• Understanding of data governance principles, ensuring adherence to data privacy and security standards.

• Ability to work effectively with diverse teams, welcoming a range of perspectives.

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Perks and Benefits:

Clearly outline the benefits and perks of the role.

 

How to Apply:

End with a strong call to action encouraging candidates to apply. Include a direct link to the application page and provide contact information for further queries.

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• Salary Information: Provide a clear salary range to maintain transparency and meet legal requirements.

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• Equality & Non-Discrimination: Include an equal opportunity statement to uphold our commitment to a diverse, inclusive workplace that does not discriminate based on race, gender, age, disability, or any other protected characteristic.

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• Environmental and Social Responsibility: If your company has sustainability initiatives or community engagement programs, mentioning them briefly can attract candidates who prioritize working for socially responsible employers.

• Transparent Hiring Process: Briefly explain the hiring process (e.g., “Our interview process typically includes three stages: an initial screening, a technical interview, and a final interview”) to help candidates know what to expect.