About Us:
We're building AI-powered talent products that help organizations hire, manage
performance, and grow their people. Our Nova platform enables human-like AI conversations
across phone, chat, and video including AI-led candidate interviews and talent interactions at
scale.
The Role
We are looking for a hands-on Lead Backend Engineer – Voice AI to build and own the
backend foundations of our Voice AI product.
This is a high-ownership, 0 to 1 role. You will work closely with Product, Design, AI/ML, and
Engineering teams to turn ambiguous problem statements into reliable, delightful, and scalable
customer experiences. You will influence both product direction and technical architecture while
building systems that power real-time, human-like AI conversations.
What You’ll Do
● Lead the design, development, and evolution of backend systems that power real-time
Voice AI experiences.
● Build reliable, low-latency services for telephony, audio streaming, conversation
orchestration, session management, and post-call workflows.
● Develop and operate Voice AI integrations using platforms such as Live Kit, Vapi, Twilio,
Web RTC, or similar technologies.
● Integrate speech-to-text, text-to-speech, LLMs, retrieval systems, and AI evaluation
pipelines into robust production workflows.
● Build agentic and conversational workflows using tools such as Lang Chain,
Lang Graph, or equivalent frameworks.
● Design scalable APIs, event-driven workflows, data models, background jobs, and
fault-tolerant systems.
● Own backend services built with Python, Fast API, Postgre SQL, Redis, queues, and
cloud infrastructure.
● Lead, mentor, and grow a high-performing team of talented engineers; create clarity, set
a high execution bar, and enable the team to deliver ambitious outcomes in a
fast-moving environment.
● Partner with Product and Design to identify customer problems, define requirements, run
experiments, and ship end-to-end features.
● Make thoughtful trade-offs across speed, product experience, latency, reliability, security,
scalability, and cost.
● Establish strong observability across the platform, including logging, monitoring, alerting,
tracing, and meaningful product/quality metrics.
● Define and improve metrics such as call success rate, latency, conversation completion,
AI quality, and user satisfaction.
● Raise the engineering bar through architecture reviews, code reviews, documentation,
and mentorship.
What We’re Looking For
● 5–8 years of backend engineering experience, including ownership of customer-facing
production systems.
● Strong proficiency in Python and backend frameworks such as Fast API.
● Strong experience with relational databases, especially Postgre SQL, along with caching
and asynchronous processing using tools such as Redis, queues, and background
workers.
● Experience designing scalable APIs, distributed systems, asynchronous workflows, and
event-driven architectures.
● Hands-on experience with Voice AI, conversational AI, telephony, Web RTC, real-time
communications, or audio/video streaming systems.
● Experience with platforms or tools such as Live Kit, Vapi, Twilio, or similar Voice AI and
communications technologies.
● Practical experience building LLM-powered applications, including prompt orchestration,
tool calling, RAG, structured outputs, and AI evaluation/monitoring.
● Experience with Lang Chain, Lang Graph, or comparable agentic workflow frameworks.
● Familiarity with cloud infrastructure, Docker, CI/CD, monitoring, logging, tracing, and
production incident debugging.
● Strong product mindset: you care deeply about user experience, customer outcomes,
and business impact, not just clean code.
● Ability to thrive in ambiguity, independently define a path forward, and take ideas from
zero to production.
● Strong communication skills and the ability to work effectively across Engineering,
Product, Design, and AI/ML teams.
● Demonstrated experience leading or managing a strong engineering team, including
technical direction, prioritization, mentoring, performance coaching, and creating an
environment of high ownership and accountability.
Nice to Have
● Experience building high-scale Saa S products.
● Experience with multi-tenant systems, role-based access controls, and enterprise-grade
security.
● Experience evaluating speech, LLM, and conversational quality through automated and
human-in-the-loop feedback systems.
● Exposure to recruiting, HR tech, talent management, or workflow automation products.
● Experience leading technical initiatives or mentoring engineers in a fast-paced startup
environment.
Why Join Us
● Build a foundational Voice AI product from the ground up.
● Own meaningful technical and product decisions with high autonomy.
● Work on AI experiences that directly shape how companies hire, engage, and grow
talent.
● Collaborate with a highly driven team operating at the intersection of AI and enterprise
Saa S.
● Make a visible impact in an environment that values initiative, speed, learning, and
ownership.