AI Software Engineer

3 weeks ago

Gurugram Gurugram India Impronics Technologies Full time

Job Description About The Role 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 (34 Years) - Develop and maintain AI-powered applications using frameworks like TensorFlow, PyTorch, 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., TensorFlow, PyTorch, 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.

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