What are the responsibilities and job description for the Senior AI Engineer - Applied AI Team position at Balyasny Asset Management L.P.?
The Applied AI team plays a pivotal role in BAM's sustained growth and success. As the financial landscape evolves, the ability to effectively leverage data becomes more critical to the firm's core business operations. The Applied AI team is at the forefront of this transformation, providing cutting-edge analytical expertise that enhances decision-making processes and drives innovation. By developing and implementing advanced AI solutions, the team not only supports BAM's strategic objectives but also strengthens its competitive advantage in the market. Their work ensures that BAM remains agile and responsive to emerging opportunities and challenges, solidifying its position as a leader in the intersection of finance and technology.
Role Overview
We are looking for a highly skilled Senior AI Engineer to join our Applied AI team and help develop innovative AI-driven investment solutions. In this role, you will contribute to pioneering projects that shape how portfolio managers, analysts, and researchers utilize AI to enhance their workflows. You will be responsible for designing robust AI systems and conducting advanced data analysis, with a focus on delivering user-friendly, high-performance applications that integrate sophisticated AI technologies.
The ideal candidate will have a proven track record of architecting and deploying production-grade AI solutions, particularly those involving large-scale data processing and integration. A strong foundation in computer science is essential, with expertise in databases, computer networks, and distributed systems. Deep experience in knowledge graph design is highly valued, including hands-on work with graph databases such as Neo4j or Amazon Neptune, and the ability to model complex relationships across diverse data sources to bridge unstructured and structured data. Exceptional problem-solving skills, a collaborative mindset, and the ability to communicate complex technical concepts clearly to both technical and non-technical audiences are critical for success in this role.
Key Responsibilities
- Design and develop the world's best financial data retrieval system
- Collaborate with frontend engineers to optimize the integration of the data retrieval system into production applications
- Collaborate with ML researchers to prototype, develop and deploy new ML products
- Participate in the full software development lifecycle from requirements gathering through deployment and support
- Mentor junior engineers and contribute to technical architecture decisions
- Participate in on-call rotations to support critical AI infrastructure
Minimum Qualifications
- 8 years of professional software development experience with at least 3 years in backend AI solutions
- Experience with Knowledge Graphs and Graph Databases (Neo4j)
- Expert-level proficiency in python and ML packages
- Strong experience with SQL and NoSQL databases
- Strong experience with RestAPI and gPRC or JPRC
- Familiarity with containerization (Docker) and orchestration (Kubernetes)
- Strong understanding of software engineering best practices, CI/CD, and infrastructure as code
Preferred Qualifications
- Experience integrating LLMs and AI models into production applications
- Familiarity with OpenAI APIs, Anthropic Claude, or similar AI services
- Experience with Graph Database
- Experience with vector databases and RAG systems
- Knowledge of financial markets and investment workflows
- Experience with cloud platforms (AWS preferred)
- Familiarity with message queuing systems (Kafka, RabbitMQ)
- Understanding of AI agent architectures and multi-agent systems
- Experience with monitoring and observability tools (Sentry, Grafana)
