GenAI Architect

Job Title: Engineering Architect (Scalable Systems & Generative AI)

Location: Hyderabad

Job Type: [Full-time]

Job Description

We are seeking an experienced Engineering Architect to design and build highly scalable and reliable systems that leverage cutting-edge Generative AI technologies. This role demands expertise in system architecture, cloud infrastructure, and a deep understanding of Gen AI APIs and their ecosystem. You will play a pivotal role in shaping our technical direction and delivering innovative solutions that scale seamlessly.

Key Responsibilities:

• Design and develop highly scalable, distributed, and fault-tolerant systems to handle large-scale data and requests.
• Architect end-to-end solutions integrating Generative AI APIs and frameworks to meet business requirements.
• Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to define technical requirements.
• Evaluate and select appropriate technologies, tools, and frameworks for scalability, performance, and security.
• Create and maintain architectural documentation, design patterns, and best practices.
• Optimize system performance, reliability, and cost efficiency, ensuring scalability to handle peak loads.
• Stay updated on emerging Gen AI technologies, APIs, and industry trends, and assess their potential impact.
• Lead technical discussions, mentor engineering teams, and drive the adoption of architectural best practices.
• Work closely with DevOps teams to implement CI/CD pipelines, monitoring, and incident management systems.

Qualifications:

Required Skills:

• Proven experience in designing and implementing highly scalable, distributed systems.
• Strong expertise in cloud platforms like AWS, Azure, or GCP, with a focus on scaling and performance optimization.
• Solid understanding of Generative AI technologies, APIs (e.g., OpenAI, Anthropic, Google PaLM, etc.), and deployment strategies.
• Proficiency in programming languages such as Python, Node.js, Java, or Go.
• Deep knowledge of microservices architecture, API design, and asynchronous communication patterns.
• Experience with containerization (e.g., Docker) and orchestration tools (e.g., Kubernetes).
• Strong understanding of data storage solutions (SQL, NoSQL, and distributed databases).
• Familiarity with security best practices in distributed systems and cloud architectures.

Preferred Skills:

• Experience with Machine Learning pipelines, model serving, and inference optimization.
• Knowledge of AI frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers.
• Hands-on experience with monitoring and observability tools like Prometheus, Grafana, or New Relic.
• Exposure to event-driven architectures and message brokers like Kafka or RabbitMQ.
• Background in optimizing cost and performance for high-traffic systems.

Education & Experience:

• Bachelors or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience).
• 10+ years of experience in system architecture, distributed systems, and scalable application development.