Artificial Intelligence Architect

16 hours ago

Pune, Maharashtra, India Seven Full time
Job Title

AI Solutions Design and Delivery Lead

Job Overview:

At Seven, we are seeking a highly experienced AI Solutions Design and Delivery Lead with over 12 years of deep technical expertise in Artificial Intelligence, particularly with extensive experience in Generative AI (GenAI) architecture, development, and delivery.

Key Responsibilities:

  1. Architect and oversee the end-to-end development of AI solutions, focusing on Generative AI (GenAI) technologies to drive innovation.
  2. Design AI frameworks that support large-scale machine learning (ML) models and algorithms, ensuring alignment with enterprise goals.
  3. Define AI strategies, solution roadmaps, and best practices that align with organizational needs, performance requirements, and security protocols.
  4. Stay ahead of AI advancements and emerging technologies to evaluate and integrate the latest tools and methodologies.

Generative AI (GenAI) Implementation:

  1. Lead the development and deployment of GenAI models for real-world applications across various industry domains such as healthcare, finance, manufacturing, and retail.
  2. Design and deploy deep learning models and natural language processing (NLP) solutions, leveraging transformer models, GPT-based frameworks, and large language models (LLMs).
  3. Evaluate the effectiveness of GenAI algorithms and models, ensuring optimal performance, accuracy, and scalability.

Technical Leadership & Collaboration:

Work closely with data engineers, ML engineers, and software developers to design robust data pipelines for AI model training, testing, and deployment.

Provide technical leadership and mentorship to AI teams, ensuring seamless collaboration between architecture, data science, and software development functions.

Manage external partnerships with AI vendors and research institutions, integrating third-party AI tools, APIs, and platforms into existing ecosystems.

AI Systems Optimization & Scalability:

  1. Develop scalable AI architectures that support high-volume data streams, complex data structures, and diverse industry-specific use cases.
  2. Ensure AI models are optimized for real-time applications, high-performance processing, and reduced latency.
  3. Leverage cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes) for AI deployment in scalable and fault-tolerant infrastructures.

AI Governance, Ethics & Compliance:

  1. Establish governance frameworks to ensure responsible AI usage, including fairness, transparency, interpretability, and privacy.
  2. Implement robust security protocols to safeguard AI models and data from adversarial attacks and vulnerabilities.
  3. Ensure AI systems are compliant with regulatory requirements and ethical standards for data usage, AI bias, and data protection.

Key Requirements:

  1. Education: Bachelor's/Master's/PhD in Computer Science, AI, Machine Learning, Data Science, or a related field.
  2. Experience: 12+ years of hands-on experience in AI, with at least 5 years of direct experience in AI architecture design and delivery.
  3. Deep expertise in Generative AI (GenAI), transformer models (GPT), natural language processing (NLP), computer vision, and deep learning.
  4. Proven experience in leading the design, implementation, and delivery of AI solutions at scale.
  5. Strong expertise in ML frameworks such as TensorFlow, PyTorch, Keras, Hugging Face, or similar.
  6. Experience with cloud computing platforms such as AWS, Azure, or GCP, and AI/ML services within these platforms.
  7. Expertise in model deployment techniques, including MLOps pipelines, containerization (Docker/Kubernetes), and cloud-native AI infrastructure.

Skills:

  1. Strong coding skills in Python, Java, Scala, R, or other programming languages relevant to AI/ML.
  2. Excellent knowledge of algorithms, data structures, and advanced machine learning techniques.
  3. Strong leadership and project management skills, with experience leading AI teams and projects.
  4. Strong communication and presentation skills, with the ability to convey complex AI concepts to both technical and non-technical stakeholders.

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