Team Lead (Equities Transactional Systems)

Millennium is looking for an exceptional individual to join the Equities Transactional Systems Core Technology Team as a Senior Engineering Lead with an AI focus. This team is responsible for the firm's equity transaction data platform, including trade lifecycle event processing, enrichment, and PnL calculations. The role is ideal for a hands-on Senior Python/AI Engineer with prior team lead experience who enjoys building robust, high-throughput AIdriven services and data pipelines in a fast-paced, delivery-focused environment. You will lead efforts to apply ML/GenAI to equities transaction and PnL data—such as anomaly detection, intelligent alerting, automated analyses, and LLM-based tools for Operations and Middle Office —while building and mentoring a high-performing engineering team.

Principal Responsibilities

• Build and manage a high-performing team of software and AI engineers working primarily with Python (and optionally Angular for UI).
• Build and operate Python-based and ML/GenAI services that perform large-scale data transformations, calculations, and intelligent analytics on equities post trade transaction and PnL data.
• Design and implement agentic ML/GenAI use cases (e.g. anomaly detection, intelligent alerts, automated investigations, LLM-based agents and assistants), including data preparation, model integration, and productionisation.
• Identify, design, and implement internal process improvements: automation of manual processes, optimization of data and model pipelines, and re-design of infrastructure for scalability, resiliency, and AI workloads.
• Deliver software in an agile fashion using modern engineering practices: comprehensive automated testing, code review, version control, CI/CD, observability, and scheduling/orchestration patterns.
• Provide level-three production support for the AI and data services owned by the team, ensuring reliability and accuracy.
• Collaborate with peer Core Tech teams and MO/Ops to define the strategic path forward for AI-enabled solutions across the equities transaction platform.
  
  

Required Skills

• Minimum 10+ years of professional Python development experience in capital markets or a fintech firm.
• Minimum 2 years leading high-performing development / AI engineering teams.
• Demonstrable experience delivering solutions for equities post trade lifecycle domain for Operations and Middle Office teams.
• Strong hands-on experience with Python data and ML/AI ecosystems (e.g., pandas, NumPy, polars, plus major ML/GenAI frameworks such as PyTorch, TensorFlow, or Hugging Face).
• Experience designing and integrating ML/GenAI systems in production (e.g., model inference services, RAG/LLM-based tools, anomaly detection pipelines, or intelligent alerting).
• Experience building REST services using frameworks such as FastAPI and/or Flask.
• Strong SQL skills and experience working with relational databases in production environments.
• Understanding of modern SDLC and MLOps practices (testing strategy, CI/CD, release management, observability, model monitoring, and operational ownership).
• Explicit bias to leverage AI-assisted development tools to improve developer productivity
• Delivery-oriented: understands the importance of shipping enhancements iteratively in an agile way.
• Detail-oriented, with strong ownership and a focus on accuracy, reliability, and production quality.
• Strong communication and interpersonal skills with a desire to work in a highly collaborative environment.
  
  

Preferred Skills

• Hands-on experience with containerized deployments and modern infrastructure tooling (Docker, Kubernetes) and familiarity with AWS platforms & services
• Hands-on UI development, including but not limited to Angular, TypeScript, ag-Grid.
• Experience with Kafka (or equivalent streaming/messaging platforms) and schema-based event publishing (e.g., AVRO).
• Bachelor's degree in Computer Science or another quantitative field from a Tier-1 college.

Skills Required
Docker, Kafka, Typescript, Kubernetes, Flask, Pandas, Tensorflow, Numpy, FastAPI, Pytorch, Sql, Aws, Python