Ai software engineer / architect
Summary
Design and build AI-driven enterprise solutions using Python, TensorFlow/PyTorch, and cloud platforms; lead architecture, model selection, and MLOps for scalable deployments.
We are seeking a highly skilled AI Software Engineer / Architect to join our global delivery team. You will be responsible for designing, developing, and implementing AI-driven solutions for enterprise-scale applications. This role requires deep technical expertise in AI/ML, strong software engineering fundamentals, and proven experience leading end-to-end solution architecture. Key Responsibilities: Architect Role (8+ years):
Define and own the AI architecture strategy, ensuring scalability, performance, and security.
Design AI/ML systems that integrate with existing enterprise platforms (cloud/on-premise).
Lead technical discussions with clients and stakeholders to gather requirements and provide architectural guidance.
Select appropriate AI/ML models, frameworks, and tools based on business needs.
Collaborate with data scientists, engineers, and product teams to bring AI solutions from concept to deployment.
Review code, mentor engineering teams, and enforce best practices in AI and software development.
Create architectural documentation and support pre-sales or proposal activities when required.
Software Engineer Role (3–4 years):Develop and maintain AI-powered applications using frameworks like Tensor Flow, Py Torch, or scikit-learn.
Work with REST APIs, cloud services (AWS, Azure, GCP), and integrate ML models into production systems.
Collaborate with cross-functional teams to understand requirements and implement features.
Optimize AI models for performance and scalability in production environments.
Conduct unit and integration testing, ensure high code quality, and participate in code reviews.
Required Skills & Qualifications:Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
Proven experience in AI/ML solution architecture and full-stack AI software development.
Strong knowledge of Python and AI frameworks (e.g., Tensor Flow, Py Torch, Keras, etc.).
Experience with MLOps, model deployment pipelines, and cloud-native architectures.
Familiarity with containerization tools (Docker, Kubernetes).
Exposure to data engineering tools and pipelines (Spark, Kafka, etc.) is a plus.
Excellent communication and leadership skills, with experience in client-facing roles.
Ability to work in a fast-paced, agile environment with global delivery teams. #J-18808-Ljbffr