AI Engineer (LLM & Voice Pipeline)

About the job

Experience: 2.00 + years Salary: Confidential (based on experience) Expected Notice Period: 15 Days Shift: (GMT+04:00) Asia/Dubai (GST) Opportunity Type: Remote Placement Type: Full Time Permanent position(Payroll and Compliance to be managed by: ADNA) What do you need for this opportunity? Must have skills required: Helix, live traffic shadowing, Managed golden sets, or prompt regression testing., Ragas or built custom eval tooling., Set up CI for prompt evaluation or had a hand in LLMOps pipelines., Trulens, Used Langfuse, Worked with latency-sensitive systems (real-time or streaming pipelines)., and debug model behavior like it’s backend logic., and experience integrating with LLM APIs (OpenAI, and fallback orchestration., Anthropic...), Azure). Job Description – AI Engineer (LLM & Voice Pipeline) 🎯 What You’ll Do You’ll be responsible for making sure our AI brains work, scale, and improve. That means: • Owning the full AI pipeline orchestration: STT → LLM → TTS. • Implementing and monitoring prompt flows, fallback strategies, and recovery logic. • Measuring and improving conversational quality: latency, hallucination, success rate, barge-in. • Building test sets, running A/B experiments, catching regressions before users do. • Working closely with the Tech Lead and Voice UX designer to align model behavior with real-world conversations. 🧩 What You Bring • Solid Python skills, and experience integrating with LLM APIs (OpenAI, Anthropic...) • You’ve shipped or maintained a product that uses LLMs in production. • Familiarity with STT/TTS tools (e.g. Whisper, ElevenLabs, Coqui, Google, Azure). • Experience with prompt engineering, context control, session state, and fallback orchestration. • You know how to log, trace, and debug model behavior like it’s backend logic. ✅ Bonus Points If You’ve • Used Langfuse, TruLens, Helix, Ragas or built custom eval tooling. • Worked with latency-sensitive systems (real-time or streaming pipelines). • Set up CI for prompt evaluation or had a hand in LLMOps pipelines. • Managed golden sets, live traffic shadowing, or prompt regression testing. 🧠 What You’ll Get • Ownership over AI behavior and quality across the entire product. • A team that values pragmatism, iteration, and clean architecture. • Input into how our agents sound, think, and adapt over time. • The chance to shape an AI system that actually talks to people — and gets judged on every sentence. 🚫 What This Role Is Not • It’s not prompt monkey work or “make it sound nicer” QA tasks. • It’s not about training foundation models or tuning a llama from scratch. • It’s not a research role. 👉 This is for someone who wants to ship LLM-powered voice agents that hold up under real-world load and get better over time. How to apply for this opportunity? • Step 1: Click On Apply! And Register or Login on our portal. • Step 2: Complete the Screening Form & Upload updated Resume • Step 3: Increase your chances to get shortlisted & meet the client for the Interview!

Requirements

• Python
• LLMs
• Voice Pipeline

Preferred Technologies

• Python
• LLMs
• Voice Pipeline

Benefits

• Ownership over AI behavior and quality across the entire product

About the company

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