Conga is looking to solve the problem of accelerating the customer’s journey to becoming a more connected and intelligent business by defining, designing, and evolving the architectural foundation of their next-generation AI/GenAI products and solutions.
Requirements
- Deep expertise in distributed systems architecture, microservices, and cloud-native design patterns
- Advanced knowledge of AI/ML system architecture, including training infrastructure, model serving, and MLOps pipelines
- Extensive experience with cloud platforms (GCP, AWS, Azure) and container orchestration (Kubernetes, Docker)
- Deep expertise in Python and frameworks such as TensorFlow, PyTorch, FastAPI, LangChain, LangGraph, and KubeFlow
- Strong understanding of data architecture, including real-time and batch processing systems, data lakes, and analytical platforms
- Experience with AI governance frameworks, model risk management, and responsible AI architectures
- Knowledge of advanced AI techniques including multi-modal models, reinforcement learning, and distributed training systems
Responsibilities
- Defining and driving the overall architectural vision for the AI platform, including system design, technology choices, and long-term technical roadmap
- Providing architectural leadership for complex, large-scale AI systems
- Acting as a thought leader in AI technologies, influencing cross-functional technical decisions and long-term strategies
- Driving architectural standards and best practices across all AI/GenAI products and services
- Having ownership of high-impact projects, shaping the future of Conga’s products while mentoring engineers, fostering a culture of continuous learning and technical excellence
- Utilizing deep technical expertise combined with strategic thinking to drive architectural decisions that will shape the future of the AI platform for years to come
- Leading architectural strategy across multiple teams and product lines, ensuring AI systems can scale to meet enterprise demands while maintaining the highest standards of performance, reliability, and security
Other
- 12+ years of professional software development experience, including 7+ years in AI/ML systems architecture
- Bachelor’s and Master’s degree in Computer Science, Engineering, or a related technical field
- Strong communication and interpersonal skills
- Ability to navigate ambiguity and deliver impactful solutions
- Experience with enterprise architecture frameworks and methodologies (TOGAF, Zachman, etc.)
