Gen AI Engineer - Generative AI, Agentic AI & Innovation Leadership

Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, AI, or related field
• Certifications in AI, machine learning, or cloud AI platforms are advantageous
• Continued professional development in emerging AI technologies and best practices
• Professional Competencies
• Critical thinking and innovative problem solving in complex technical challenges
• Strong leadership skills and ability to manage technical teams effectively
• Excellent communication skills to articulate technical concepts to non-technical audiences
• Adaptability to rapid technological changes and evolving business needs
• Keen interest in emerging AI trends with a focus on sustainable and ethical AI development
• Strong organizational skills for managing multiple projects and deadlines
• S YNECHRON'S DIVERSITY & INCLUSION STATEMENT

Benefits

Additional Information

Job Summary Synechron is seeking an experienced Gen AI Engineer to lead innovative projects focused on emerging generative AI and agentic AI technologies. This role involves designing, developing, and implementing AI solutions tailored to transforming business processes, particularly in banking and financial services. The successful candidate will guide technical teams, stay abreast of industry advancements, and contribute to strategic technology adoption to drive organizational growth. Software Requirements Required Software Skills: In-depth expertise in Generative AI and Agentic AI technologies Programming proficiency in Python, with experience in frameworks such as PyTorch, TensorFlow, or similar for AI model development Familiarity with cloud AI services like AWS SageMaker, Azure Machine Learning, or GCP AI platform Understanding of APIs and integrations for deploying AI models effectively Experience with data management tools and version control systems like Git Preferred Skills: Knowledge of blockchain and IoT as they relate to AI deployment Experience using automation and orchestration tools in AI workflows Overall Responsibilities Lead the end-to-end development of generative AI solutions that improve business functionalities and customer experiences 5years of hands-on experience in Gen Ai/Agentic Ai. Mentor and guide core team members and junior engineers on AI best practices and project execution Evaluate and innovate new AI technologies, models, and tools to optimize processes Collaborate with cross-functional teams, including business stakeholders, data scientists, and development groups, to align AI initiatives with organizational strategies Stay current with advancements in generative AI, agentic AI, and related emerging fields to maintain a competitive edge Manage project timelines and deliverables to ensure timely implementation of AI solutions Document technical designs, best practices, and project insights for ongoing knowledge sharing Technical Skills (By Category) Programming Languages: Python (required), R, Java (preferred) AI Frameworks & Libraries: PyTorch, TensorFlow, GPT/Transformers, OpenAI API, Hugging Face (required) Data Management: Data preprocessing, management, and model training data pipelines Cloud Technologies: AWS, Azure, GCP (preferred) Model Deployment & APIs: REST API development, containerization with Docker, orchestration with Kubernetes Tools & Methodologies: Agile, CI/CD pipelines, Git version control, model versioning tools Security & Ethics: Data privacy, AI fairness, and compliance considerations Experience Requirements At least 5-7 years of experience in software development and leading technology projects Proven track record of delivering AI solutions that enhance business operations Experience mentoring engineering teams in AI project execution Industry experience in banking, finance, or enterprise environments preferred Alternative experience: extensive innovation in AI, natural language processing, or digital transformation initiatives Day-to-Day Activities Lead AI model development, training, and deployment activities Provide technical mentorship and oversee project execution phases Collaborate with cross-disciplinary teams to define AI project scope and success metrics Conduct research on cutting-edge AI techniques and incorporate them into organizational solutions Evaluate emerging AI tools and recommend improvements for efficiency and scalability Document processes, train stakeholders, and ensure ethical AI practices are followed

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