Responsabilidades
🤓As a Senior Software Engineer, the company expects you to perform the following tasks:
- Design, build, and launch production-grade conversational AI solutions for enterprise clients, from rapid prototypes to scalable deployments.
- Collaborate cross-functionally with product managers, designers, and enterprise partners to define user journeys, performance goals, and success metrics.
- Leverage and contribute to Connectly’s AI platform, working with engineering teams in San Francisco to integrate new capabilities and influence platform direction.
- Experiment with AI-driven features, including LLM-based agents, retrieval systems, and automation pipelines to continuously improve customer engagement.
- Develop and maintain backend systems using Python, AWS, Kafka, Postgres, and DynamoDB for scalability and reliability.
- Establish, track, and iterate on AI performance metrics, leveraging data to optimize outcomes and drive measurable business results.
- Plan and manage your workstream, making thoughtful tradeoffs between deadlines, quality, and innovation.
- Mentor teammates, contribute to code reviews, and uphold engineering best practices in a fast-moving, distributed environment.
Requisitos
✨You are the person they are looking for if you have:
- BS or MS in Computer Science or related technical field.
- 5+ years of experience in hands-on software engineering roles.
- Proven track record building and scaling enterprise systems using Python, AWS, Kafka, Postgres, and/or DynamoDB.
- Experience with frontend engineering (React, TypeScript, etc.) is a plus.
- Prior experience developing or deploying conversational AI applications is a strong plus.
- Experience working in fast-paced, customer-centric environments, ideally in a startup or high-growth tech company.
💜They will be more enthusiastic about you if you also have:
- Exceptional communication skills with both technical and non-technical stakeholders.
- Deep attention to detail paired with strong system-level thinking — you can zoom out to strategy and dive deep into code.
- A bias for action and results, with comfort navigating ambiguity and evolving product needs.
- Genuine curiosity and a drive to stay ahead of the rapidly changing AI landscape.
- Balance of product sense and technical rigor — you care as much about user experience as you do about system performance.
- Hands-on experience with prompt design, agent evaluation, and LLM-based system integration is a significant plus.