Description
We are seeking an experienced AI Tech Lead to lead the design and development of scalable backend systems and production-grade AI applications.
This is a hands-on technical leadership role combining deep Python/backend engineering expertise with proven experience building and deploying GenAI applications and AI agents used by end users in production.
Key Responsibilities
- Lead the architecture and development of scalable Python backend systems, services, and APIs.
- Design distributed systems and microservices with a focus on performance, scalability, reliability, and security.
- Remain hands-on with architecture, coding, code reviews, and complex technical problem-solving.
- Define engineering best practices across backend and AI development.
AI & Agentic Engineering
- Design and build production-grade GenAI applications and AI agents used by end users.
- Build agentic workflows including LLM orchestration, tool calling, context management, memory, and service integrations.
- Integrate LLMs and other AI models into scalable production applications.
- Build solutions using technologies such as Amazon Bedrock, OpenAI, LangChain, and LangGraph.
- Implement LLM evaluation, tracing, monitoring, and observability.
- Optimize AI solutions for quality, latency, reliability, scalability, and cost.
- Take AI capabilities from experimentation and POC through to production and end-user adoption.
Team Leadership & Delivery
- Lead, mentor, and provide technical guidance to backend and/or full-stack engineers.
- Partner with Product, AI/Data, DevOps, and Architecture teams to define and deliver technical solutions.
- Drive complex projects from design through deployment and production monitoring.
- Foster a strong engineering culture focused on ownership, innovation, and quality.
Required Qualifications
- 8+ years of software engineering experience with strong backend development expertise.
- Strong hands-on Python experience, particularly building production backend services and applications.
- 2+ years in a technical leadership or Tech Lead role.
- Proven experience designing large-scale distributed systems and microservices.
- Hands-on experience building and deploying GenAI applications and AI agents in production.
- Experience taking LLM/agentic solutions beyond POC into applications used by end users.
- Experience with LLMs, agent orchestration, tool calling, context management, and AI/backend integrations.
- Experience with Amazon Bedrock, OpenAI, LangChain, LangGraph, or similar technologies.
- Understanding of production AI considerations including evaluation, observability, latency, reliability, scalability, and cost.
- Experience with cloud platforms, preferably AWS, as well as Docker and Kubernetes.
- Strong system design and problem-solving skills.