Lead AI Engineer

Venture AI is seeking an experienced AI Engineering Lead to drive the technical vision and execution of its conversational AI products. This role involves ownership of the real-time voice stack, large language model (LLM) orchestration, telephony integrations, and conversational analytics that provide clients with detailed insights from every call. You will lead a team of AI and backend engineers, set architectural standards, write and review code, conduct client demos, and ensure successful delivery. Additionally, you will contribute to other client projects, including a HIPAA-compliant healthcare CRM, leveraging your AI and data expertise to enhance automation and analytics. This is a hands-on leadership position combining deep technical responsibility with team and client outcome management.

Key Responsibilities

- Own the architecture and development of the real-time voice AI stack, including LiveKit components (rooms, tracks, agents framework, SIP) and streaming pipelines for speech-to-text (STT), LLM, and text-to-speech (TTS).
- Design for conversational quality by managing latency budgets, voice activity detection, turn-taking, interruption handling, endpointing, and recovery from audio issues such as silence or noise.
- Evaluate and integrate STT and TTS providers (e.g., Deepgram, AssemblyAI, Whisper, ElevenLabs) based on accuracy, latency, cost, and language support, including Arabic and accented English for US and Gulf clients.
- Develop and refine LLM-driven dialogue systems with prompt and tool design, function calling, structured outputs, guardrails, fallbacks, and human handoff mechanisms.
- Architect telephony orchestration for inbound and outbound calls across SIP trunks and CPaaS providers (such as Twilio, Telnyx), including call routing, transfers, event webhooks, retries, and reconciliation.
- Integrate voice agents with client systems like CRMs, scheduling, ticketing, and CTI platforms to enable calls to trigger real actions.
- Ensure reliable voice workload operation at scale, managing concurrency, autoscaling, failover, and cost control per call minute.
- Build conversational analytics layers that include transcription post-processing, summarization, intent and topic extraction, sentiment analysis, compliance, QA scoring, and outcome tracking.
- Design retrieval-augmented generation (RAG) pipelines with chunking, embeddings, hybrid retrieval, reranking, grounding, and citation to provide accurate, client-specific knowledge in real time and post-call insights.
- Develop agentic workflows using LangGraph, LangChain, or similar frameworks, ensuring clear state management, tools, and testable behavior.
- Establish evaluation and observability for LLM and voice systems through offline test sets, LLM-as-judge scoring, regression suites, tracing, and monitoring tools (e.g., Langfuse, LangSmith).
- Lead and mentor AI, backend, and frontend engineers by planning work, reviewing code, and raising team standards.
- Manage client milestone demos, scope adherence, risk tracking, and delivery timelines.
- Estimate and scope new phases and change requests for fixed-price, milestone-based projects.
- Deploy and operate systems on AWS with isolated environments, CI/CD pipelines, security, audit logging, and data privacy controls.
- Support other Venture AI projects, including a HIPAA-compliant healthcare CRM built with FastAPI, PostgreSQL, and Airflow, applying consistent engineering standards.

Required Qualifications

- Minimum of 6 years of professional software engineering experience, including at least 2 years in a leadership role and 2 years working on production AI or LLM-based systems.
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
- Hands-on experience with voice AI technologies, including real-time STT, LLM, and TTS pipelines, balancing latency, quality, and cost.
- Strong expertise with LiveKit or comparable real-time communication stacks such as WebRTC.
- Practical knowledge of telephony systems, including SIP, PSTN, call flows, and integration with CPaaS or carriers like Twilio or Telnyx.
- Proficiency in LLM application development: prompt engineering, function calling, structured outputs, and evaluation.
- Experience building RAG systems and agentic workflows using LangGraph, LangChain, or similar, including vector search technologies like pgvector or managed vector stores.
- Advanced Python backend skills with frameworks such as FastAPI, async and streaming APIs, WebSockets, Pydantic, and automated testing.
- Solid understanding of PostgreSQL, data pipelines, and production AWS environments with Docker and CI/CD tools (e.g., GitHub Actions).
- Strong grasp of application security, including authentication, role-based authorization, audit logging, and secrets management.
- Proven track record of delivering client projects on time with excellent communication skills in English.
- Availability to overlap with US Central Time for meetings and demos.

Preferred Qualifications and Benefits

- Experience with large-scale conversation analytics, including call QA, speaker diarization, sentiment analysis, topic clustering, and dashboard creation.
- Familiarity with Arabic or multilingual voice agents, including dialect handling.
- Knowledge of fine-tuning or distillation of speech or dialogue models, including open-source and self-hosted solutions.
- Experience working with HIPAA-regulated systems or other environments handling PHI/PII, as well as healthcare data standards such as EHR, ICD-10, or Medicare programs.
- Background with CTI or contact center platforms.
- Frontend development skills sufficient to review junior engineers’ work and make UI architecture decisions.

Why Join Venture AI

This role offers the opportunity to lead the technical direction of a live voice AI product actively used by clients. You will engage with the full modern voice and LLM technology stack, working directly with US and Gulf clients on critical systems. The position provides real ownership over architecture, team leadership, and project delivery. Venture AI offers competitive compensation, including performance bonuses, learning allowances, and medical benefits.