Tech Lead — Conversational AI & Driver Automation

Tech Lead — Conversational AI & Driver Automation

7+ Years

Remote

Full-Time

We are looking for an Engineering Lead to own and drive Snoonu’s Conversational AI and Driver Automation platform – a portfolio spanning IVR systems, multi-channel chatbots, and a production‑grade multi‑agent Agentic AI framework built on AWS Bedrock. You will lead a focused team of AI Engineers and Python Backend Engineers, turning operational SOPs into autonomous, reliable workflows that serve drivers in real time across Qatar.

In this role you will set the technical direction, establish engineering standards, and own delivery end‑to‑end – from architecture decisions and code reviews to observability and cost governance. You will work directly with the R&D Director and Product to shape what gets built next, then lead your team to ship it with excellence.

• Lead, mentor, and grow a cross‑functional team of AI Engineers and Python Backend Engineers – driving technical quality, delivery velocity, and engineering culture.
• Own sprint planning, technical scope definition, and delivery commitments for the conversational AI and driver automation domain.
• Conduct design reviews, define coding standards, and maintain engineering quality across IVR, chatbot, and agentic system codebases.
• Act as the primary technical interface between Engineering, Product, and Operations for all driver‑facing automation initiatives.
• Partner with the R&D Director to shape the team's technical roadmap, evaluate emerging AI capabilities, and surface the next high‑leverage bets.

• Own the architecture and continuous improvement of Snoonu’s IVR system, ensuring reliability, low latency, and clean escalation paths for driver calls.
• Drive design decisions for call flow logic, intent/slot management, DTMF routing, and voice‑to‑action fulfillment.
• Define and monitor SLAs for IVR uptime, misroute rate, and escalation‑to‑human ratios.

• Lead the design and delivery of Snoonu’s multi‑agent AI chatbot service for driver support across real‑time chat channels.
• Own the four‑agent architecture – Coordinator, Data Collector, Rules Agent, and Action Executor – running on AWS Bedrock Agents or similar architecture.
• Ensure chatbot flows handle driver intents reliably: order removal, vehicle mismatch, ETA extensions, merchant disputes, and escalations.
• Drive LLM evaluation cycles, prompt strategy, and Bedrock Guardrail design to ensure responses are consistent, safe, and operationally correct.

• Lead the buildout and operation of the SOPs‑as‑Code framework – encoding operational SOPs as machine‑readable policies executed by the multi‑agent system.
• Own the Config File architecture and Config Reader Agent pipeline that converts PDF‑based SOPs into deployable agent configurations on AWS Bedrock.
• Govern the structured rules engine (condition/operator/value schema) to ensure deterministic, auditable decisions with no LLM interpretation ambiguity.
• Design and enforce human‑in‑the‑loop checkpoints, escalation triggers, confidence thresholds, and operator override capabilities.
• Establish versioning, rollback, and safe deployment practices for SOP configuration changes in production.

• Own the cloud backbone for AI services:
  Lambda, ECS/Fargate, SQS/SNS, DynamoDB, MongoDB, S3, Cloud Watch, and AWS Bedrock.
• Build and maintain CI/CD pipelines for prompt versioning, agent configuration rollout, and automated eval gates before production deployment.
• Define observability standards – per‑agent‑turn latency SLAs, Bedrock cost tracking, drift detection, and failure alerting.
• Lead capacity and cost planning as interaction volumes scale across driver and operations channels.
• Evaluate frontier LLMs (Claude Sonnet/Opus, open‑weight models) and orchestration frameworks (Bedrock Agents, Lang Graph, CrewAI) against Snoonu’s operational constraints.
• Identify and prototype the next AI capability Snoonu should dominate – from experiment to validated proof‑of‑concept with clear go/no‑go criteria.
• Produce architecture decision records, prompt engineering playbooks, and technical documentation for…