Software Engineer - 3 (Gen AI & Speech)

Software Engineer 3 - Gen AI & Speech

About Us

Exotel is a leading provider of AI transformation to enterprises for customer engagement and experience. With over 20 billion annual conversations across Omni channel, voice, agents and bots, Exotel is trusted by more than 7000 clients worldwide, spanning industries such as BFSI, Logistics, Consumer Durables, E-commerce, Healthcare and Education.

Customer expectations are evolving and businesses face the challenge of balancing the need for increased revenue, optimized costs, and exceptional customer experience (CX). Exotel steps forward as your transformative partner, offering an AI-powered communication solution to address all three!

Tech @ Exotel

Exotel engineering solves some really cool infrastructure level problems with the goal of ensuring no one misses a call or an SMS.

• Our focus is on building very fault-tolerant, loosely coupled, scalable and real-time distributed systems
• We emphasize a lot on clean abstractions of code, loosely coupled services and good coding practices
• We are very strong believers in “you built it, you own it!”. And running a distributed system is very different from just building one!
• We are crazy about high availability

The Role

You’ll be part of the team building Exotel’s AI and speech platform, powering products like Conversation Quality Analysis, AI Voice Agents, and AI Chat Agents. This means working across large language models, speech processing, and distributed backend systems to process and understand millions of enterprise conversations at scale.

This is an engineering role first. You’ll design, build, deploy, and operate production services, and own them end-to-end.

What You’ll Do

• Build and optimize LLM-powered pipelines for analyzing conversations at scale, managing cost, latency, and quality tradeoffs across model providers.
• Work on speech processing: improving transcription accuracy, handling multilingual audio, and solving real-world audio quality challenges.
• Design and build AI agents that reason over enterprise data and deliver actionable answers with appropriate guardrails.
• Develop and scale high-throughput, multi-tenant backend services with focus on reliability and performance.
• Own cost and observability for AI workloads: usage tracking, cost attribution, and quality monitoring. Model optimization and self-hosting are active areas of investment.
• Take end-to-end ownership of the software development lifecycle: requirements, design, development, testing, deployment, and monitoring.

What You Bring

Must-have

• Bachelor’s or Master’s degree in Computer Science or equivalent.
• 5-8 years of software engineering experience.
• Proficiency in at least one backend language (Python, Java, Go, or similar). Ability to pick up new languages quickly; the language matters less than the engineering thinking behind it.
• Strong understanding of data structures, algorithms, multi-threading, and concurrency.
• Good understanding of software engineering concepts design patterns, modularity, scalability.
• Experience with microservices architecture and distributed systems designing, building, and operating them.
• Experience designing and developing RESTful APIs and async job-processing architectures.
• Production experience with databases, caching layers, message brokers, and search/analytics systems , including data modeling and scaling.
• Hands-on experience with LLM APIs (OpenAI, Gemini, Azure, or similar): prompt engineering, structured output, cost management. If you haven’t worked with LLMs yet but have strong engineering fundamentals and a willingness to learn, that works too.
• Experience with major cloud platforms (AWS, GCP, or Azure).
• Experience with containers and orchestration (Docker, Kubernetes) and CI/CD pipelines.
• Strong analytical and problem-solving skills.
• Excellent written and verbal communication skills.
• Team player, comfortable working across teams (product, data, infrastructure) in a fast-paced environment.

Good-to-have

• Understanding of RAG patterns embeddings, vector stores, retrieval strategies.
• Comfortable with Linux , shell scripting, and developing Linux-based applications.
• Familiarity with monitoring and observability tools such as Grafana, Kibana, Elasticsearch.
• Strong **networking…