Senior AI Solutions Engineer

Job Summary

AceNet Consulting is looking for a highly skilled Senior AI Solutions Engineer with 6–8 years of experience in Artificial Intelligence, Machine Learning, and Solution Architecture. The ideal candidate will be responsible for designing, developing, and deploying enterprise-grade AI solutions that address complex business challenges. You will work closely with cross-functional teams to build scalable, secure, and high-performing AI applications while ensuring adherence to architecture governance, coding standards, and best practices.

Key Responsibilities

Design, architect, and implement scalable AI and Machine Learning solutions for enterprise applications.

Develop AI-powered applications using modern AI frameworks and cloud technologies.

Build and integrate AI solutions with enterprise platforms, data lakes, APIs, and business applications.

Collaborate with business stakeholders, architects, data engineers, and development teams to understand requirements and deliver innovative AI solutions.

Ensure solution scalability, security, reliability, and performance through architecture governance and technical best practices.

Design and implement data pipelines supporting AI and machine learning workloads.

Integrate AI models with enterprise systems using REST APIs and middleware technologies.

Leverage cloud platforms, containerization, and DevOps practices for AI solution deployment.

Mentor technical teams and contribute to architecture reviews, code quality, and engineering standards.

Stay updated with emerging AI technologies and recommend innovative approaches for business transformation.

Required Skills

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Engineering, or a related field.

6–8 years of experience in AI, Machine Learning, and Solution Architecture.

Strong programming expertise in Python, Java, or C++.

Hands-on experience with Microsoft Azure and AI cloud services.

Experience with AI frameworks and platforms including OpenAI APIs, LangChain, Hugging Face, and Foundry.

Strong understanding of Machine Learning algorithms, Deep Learning, data processing, and enterprise AI solutions.

Experience with cloud infrastructure, Docker, Kubernetes, and DevOps practices.

Knowledge of data architecture, ETL pipelines, Microsoft Fabric/Data Lakehouse concepts, and enterprise data integration.

Experience integrating AI solutions with Salesforce CRM, CMS platforms, data lakes, and RESTful APIs.

Strong understanding of AI security, governance, privacy, and architecture best practices.

Excellent analytical, problem-solving, communication, and stakeholder management skills.

Good to Have

Experience with Reinforcement Learning, Natural Language Processing (NLP), or Computer Vision.

Knowledge of AI ethics, responsible AI, and bias mitigation strategies.

Experience working in enterprise-scale digital transformation initiatives.

Leadership experience mentoring technical teams and driving architectural decisions.