AI Solutions / AI Technical Strategist

Synechron is seeking a forward-thinking AI Solutions Lead to drive the development, deployment, and strategic planning of AI-based solutions across enterprise platforms. You will oversee cross-functional teams, evaluate emerging AI technologies, and ensure alignment with organizational goals. Your role is pivotal in fostering innovation, advancing AI capabilities, and delivering scalable, high-impact AI solutions that contribute to our business growth and digital transformation objectives.

Must Have

• Solid understanding of AI concepts including machine learning, deep learning, NLP, and data science fundamentals.
• Experience in designing and implementing AI models or solutions using frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Awareness of cloud platforms offering AI services (AWS SageMaker, Azure Machine Learning, Google AI/Vertex AI).
• Knowledge of software architecture and design patterns relevant to scalable AI applications.
• Familiarity with project management tools and Agile development methodologies.
• Lead and manage AI projects from concept to deployment, ensuring solutions meet business needs and technical standards.
• Design scalable AI architectures, including data pipelines, model deployment, and inference systems.
• Collaborate with product managers, data scientists, and engineering teams to identify opportunities for AI integration.
• Evaluate emerging AI technologies and industry trends; recommend adoption strategies.
• Mentor and guide teams in best practices for AI model development, deployment, and monitoring.
• Establish and maintain AI governance practices, including model validation, fairness, and ethical standards.
• Develop and maintain technology roadmaps aligned with organizational growth and innovation strategies.
• Oversee AI solution performance, operationalization, and continuous improvement efforts.
• Communicate complex AI concepts clearly to stakeholders, including non-technical leadership.
• Experience with TensorFlow, PyTorch, or scikit-learn for model development and training.
• Hands-on experience deploying AI models on AWS, Azure, or GCP platforms.
• Knowledge of data processing tools like Spark, Hadoop, Kafka, or comparable systems.
• Familiarity with scalable microservices architectures, REST APIs, and containerization (Docker).
• Agile project management (Jira, Confluence), version control (Git), and CI/CD pipelines for model deployment.
• 2+ years of experience leading or designing AI solutions in enterprise or large-scale environments.
• Proven success in delivering scalable AI models or applications from prototype to production.
• Experience with cloud deployment, MLOps, and model monitoring.
• Knowledge of data science tools, data management, and AI software lifecycle management.
• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related fields.

Good to Have

• Support certifications in AI, Data Science, or Cloud (e.g., AWS Certified Machine Learning, Microsoft AI Engineer, GCP Professional AI Engineer).
• Experience with big data processing and data management tools (Spark, Hadoop, Kafka).
• Knowledge of deployment pipelines for AI models including MLOps tools such as Kubeflow, MLflow, or TFX.
• Skills in data visualization tools (Tableau, Power BI) linked to AI data insights.
• Experience with ML Ops tools such as Kubeflow, MLflow, TFX, or Seldon.
• Use of respective cloud AI services like SageMaker, AzureML, or Vertex AI, and data lakes.
• Data pipeline design, ETL processes, and feature engineering techniques.
• Advanced knowledge of MLOps pipelines, model versioning, and automated deployment workflows.
• Automation of model training, validation, and deployment with DevOps practices.
• Industry experience in financial services, retail, healthcare, or other data-intensive sectors.

Job Summary

Synechron is seeking a forward-thinking AI Solutions Lead to drive the development, deployment, and strategic planning of AI-based solutions across enterprise platforms. You will oversee cross-functional teams, evaluate emerging AI technologies, and ensure alignment with organizational goals. Your role is pivotal in fostering innovation, advancing AI capabilities, and delivering scalable, high-impact AI solutions that contribute to our business growth and digital transformation objectives.

Software Requirements

Required Skills:

• Solid understanding of AI concepts, including machine learning, deep learning, NLP, and data science fundamentals
• Experience in designing and implementing AI models or solutions using frameworks such as TensorFlow, PyTorch, or scikit-learn
• Awareness of cloud platforms offering AI services (AWS SageMaker, Azure Machine Learning, Google AI/Vertex AI)
• Knowledge of software architecture and design patterns relevant to scalable AI applications
• Familiarity with project management tools and Agile development methodologies

Preferred Skills:

• Support certifications in AI, Data Science, or Cloud (e.g., AWS Certified Machine Learning, Microsoft AI Engineer, GCP Professional AI Engineer)
• Experience with big data processing and data management tools (Spark, Hadoop, Kafka)
• Knowledge of deployment pipelines for AI models including MLOps tools such as Kubeflow, MLflow, or TFX
• Skills in data visualization tools (Tableau, Power BI) linked to AI data insights

Overall Responsibilities

• Lead and manage AI projects from concept to deployment, ensuring solutions meet business needs and technical standards
• Design scalable AI architectures, including data pipelines, model deployment, and inference systems
• Collaborate with product managers, data scientists, and engineering teams to identify opportunities for AI integration
• Evaluate emerging AI technologies and industry trends; recommend adoption strategies
• Mentor and guide teams in best practices for AI model development, deployment, and monitoring
• Establish and maintain AI governance practices, including model validation, fairness, and ethical standards
• Develop and maintain technology roadmaps aligned with organizational growth and innovation strategies
• Oversee AI solution performance, operationalization, and continuous improvement efforts
• Communicate complex AI concepts clearly to stakeholders, including non-technical leadership

Technical Skills (By Category)

AI & Data Science Frameworks:

• Required: Experience with TensorFlow, PyTorch, or scikit-learn for model development and training
• Preferred: Experience with ML Ops tools such as Kubeflow, MLflow, TFX, or Seldon

Cloud & Data Platforms:

• Required: Hands-on experience deploying AI models on AWS, Azure, or GCP platforms
• Preferred: Use of respective cloud AI services like SageMaker, AzureML, or Vertex AI, and data lakes

Data Management & Processing:

• Required: Knowledge of data processing tools like Spark, Hadoop, Kafka, or comparable systems
• Preferred: Data pipeline design, ETL processes, and feature engineering techniques

Architecture & Design:

• Required: Familiarity with scalable microservices architectures, REST APIs, and containerization (Docker)
• Preferred: Advanced knowledge of MLOps pipelines, model versioning, and automated deployment workflows

Tools & Development Practices:

• Required: Agile project management (Jira, Confluence), version control (Git), and CI/CD pipelines for model deployment
• Preferred: Automation of model training, validation, and deployment with DevOps practices

Experience Requirements

• 2+ years of experience leading or designing AI solutions in enterprise or large-scale environments
• Proven success in delivering scalable AI models or applications from prototype to production
• Experience with cloud deployment, MLOps, and model monitoring
• Knowledge of data science tools, data management, and AI software lifecycle management
• Industry experience in financial services, retail, healthcare, or other data-intensive sectors is an advantage but not mandatory

Day-to-Day Activities

• Lead the end-to-end development, deployment, and operationalization of AI models and solutions
• Collaborate with cross-functional teams to define project scope, requirements, and KPIs
• Evaluate new AI frameworks, tools, and platforms, making strategic recommendations
• Mentor team members on AI model best practices, ethical considerations, and operational deployment
• Oversee data pipeline development, model training, validation, and inference workflows
• Monitor deployed models, troubleshoot issues, and implement enhancements for performance and accuracy
• Develop technical documentation, governance policies, and operational guidelines
• Keep abreast of industry trends, research breakthroughs, and emerging best practices

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related fields
• Certifications in AI/ML (such as AWS Certified ML, Microsoft AI Engineer, or Google Cloud AI) are desirable
• Demonstrated experience leading AI projects across all stages — from data collection and model training to deployment and monitoring

Professional Competencies

• Strong analytical and problem-solving mindset, with a focus on innovative solutions
• Effective communication skills to articulate complex AI concepts to diverse audiences
• Leadership and mentorship capabilities to foster team growth and knowledge sharing
• Strategic thinking aligned with organizational goals and industry standards
• Adaptability to rapidly evolving AI landscapes and emerging technologies
• Strong time and project management skills in a fast-paced, collaborative environment