About the role
Requirements:
- 4+ years of software engineering experience, preferably in backend-heavy roles.
- Strong experience with Python and building scalable backend applications.
- Prior experience building LLM-based applications; experience with AI agents is a strong plus.
- Working knowledge of LLMs, voice models, prompt workflows, tool calling, and agent orchestration.
- Strong understanding of system design, APIs, distributed systems, queues, background jobs, and production reliability.
- Experience with relational databases like MySQL and NoSQL databases like MongoDB.
- Experience with AWS services and cloud-native architecture.
- Ability to build fast without compromising on reliability, security, and maintainability.
- Strong problem-solving ability and comfort with ambiguity.
- High ownership mindset; you should be able to take a problem statement and drive it to shipped production outcomes.
You Will Thrive Here If:
- You want to build real AI products, not just wrappers around APIs.
- You enjoy working in fast-paced, high-intensity startup environments.
- You are excited by agents, voice AI, automation, and applied LLM systems.
- You like owning problems end-to-end instead of waiting for detailed instructions.
- You care about business impact and want your engineering work to directly influence revenue.
- You can work closely with founders, product teams, and customers to build fast and improve continuously.
- You are comfortable with chaos, speed, and high standards.
Good to Have:
- Experience with LangChain, LlamaIndex, CrewAI, AutoGen, OpenAI, Anthropic, Gemini, or similar LLM ecosystems.
- Experience building voice AI workflows using models/APIs like ElevenLabs, Deepgram, Twilio, OpenAI Realtime, or similar.
- Experience with MCP servers, tool calling, RAG, embeddings, vector databases, evals, or agent memory.
- Experience in sales-tech, marketing-tech, CRM, lead qualification, or revenue automation.
- Experience working in early-stage or growth-stage startups.