AI Software Engineer

3 weeks ago

Gurugram, India Impronics Technologies Full time
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 (3–4 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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