Overview
My client, an established investment management firm, is seeking a Senior AI Software Engineer to join their Tooling and Automation team. This team is focused on building advanced Agentic AI solutions that enhance how artificial intelligence is used to generate insights and drive automation across the organization.
This role involves designing, developing, and deploying cutting-edge Generative AI (GenAI) systems, integrating diverse data sources, and collaborating closely with Product, Data, Engineering, and Compliance teams. The ideal candidate is passionate about AI, highly self-motivated, and committed to building scalable, responsible, and high-performance AI solutions.
Key Responsibilities
Design, develop, and deploy Agentic AI solutions using modern AI frameworks
Integrate structured and unstructured data sources into GenAI systems to expand capabilities and generate actionable insights
Leverage MCP tooling to ingest and manage diverse datasets for agent-based applications
Collaborate with cross-functional teams to define and deliver new GenAI use cases
Build and maintain robust APIs and data pipelines for efficient data processing and model interaction
Stay up to date with advancements in Generative AI and Large Language Models (LLMs) and apply relevant innovations
Document system architectures, experiments, and processes to support reproducibility and knowledge sharing
Optimize AI solutions for scalability, performance, and responsible/ethical use
Write unit tests and participate in code reviews to ensure high-quality, maintainable code
Continuously evaluate emerging tools, frameworks, and methodologies in AI and apply them to improve systems
Experience with MLOps, infrastructure-as-code tools (e.g., Terraform, Ansible, CloudFormation), or CI/CD platforms (e.g., GitLab)
Hands-on experience with Generative AI, LLMs (e.g., LLaMA), and RAG architectures
Qualifications
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field
5+ years of programming experience, with strong proficiency in Python
Proven experience designing and deploying machine learning, GenAI, or LLM-based solutions
Strong analytical, problem-solving, and critical-thinking skills
Experience integrating both structured and unstructured data into AI/ML systems
Familiarity with AI/ML frameworks such as PyTorch, TensorFlow, or Hugging Face
Experience building and maintaining data pipelines and RESTful APIs
Solid understanding of data structures, algorithms, and system architecture
Experience with containerization tools such as Docker and Kubernetes
Experience with cloud platforms (e.g., AWS) for deploying AI/ML workloads