Executive Director Principal Software Engineer - Agentic Engineering
Role details
Job location
Tech stack
Job description
- Own the multi-year agentic platform strategy: agent toolchains, RAG pipelines, memory/state architectures, context management, evaluation, and feedback/reinforcement loops.
- Architect scalable multi-agent systems using LangChain, LangGraph, AutoGen, or equivalent frameworks-and define when to use simpler primitives.
- Design distributed ingestion and workflow systems (batch + streaming) with data contracts, lineage, and strong data-quality patterns.
- Establish standards for the agentic development lifecycle: context engineering, automated evals, observability, security, and release readiness.
- Contribute directly in Python (services, concurrency, performance, reliability) and set the bar via reference implementations.
- Lead design and code reviews; engage directly in incident response and production hardening.
- Build reusable agent components: planning/decomposition, tool/function calling, self-critique/reflection loops, state management, multi-agent coordination, and safety controls.
- Partner with MLOps/platform on deployment, monitoring, and retraining pipelines (MLflow, SageMaker, Vertex AI, Azure ML, etc.).
Requirements
- 10+ years in software engineering, including 5+ years leading senior technical teams and driving architecture for large systems.
- Expert Python; working proficiency in TypeScript, Go, or Rust.
- Deep familiarity with agentic frameworks (LangChain, LangGraph, AutoGen, or equivalent).
- Strong command of RAG, prompt/context design, tool/function calling, and multi-step reasoning patterns.
- Distributed systems and data platform experience: Kafka, Spark, gRPC/REST, Docker/Kubernetes.
- Cloud fluency (AWS/Azure/GCP) and MLOps tooling (MLflow, Kubeflow, SageMaker, Vertex AI).
- Familiarity with vector databases, knowledge graphs, and semantic retrieval patterns.
- Strong executive communication-able to align stakeholders on trade-offs, timelines, and risk.
- Platform mindset: builds durable systems, not fragile demos.
Preferred qualifications, capabilities, and skills
- kdb+/q, ClickHouse, or other time-series/analytical data stores.
- Financial services domain (trading infrastructure, derivatives, fixed income).
- Publications, talks, or open-source contributions in agentic AI.
- Experience designing "agentic SDLC" / software-delivery automation.
Benefits & conditions
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.