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Tech Lead — Conversational AI & Driver Automation

Snoonu
Doha, QAT
Full Time
Lead
4 weeks ago
AWS BedrockConversational AIIVR SystemsMulti Agent SystemsPythonBackend Development
Free

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Welcome to Your Next Adventure!

  • 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.

What You’ll Get Your Hands On

  • 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.

Agentic AI & SOP Automation

  • 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.

AWS Infrastructure & MLOps

  • Own the cloud backbone for AI services: Lambda, ECS/Fargate, SQS/SNS, DynamoDB, MongoDB, S3, CloudWatch, 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.

R&D & Innovation

  • Evaluate frontier LLMs (Claude Sonnet/Opus, open weight models) and orchestration frameworks (Bedrock Agents, LangGraph, 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 team wide use.

The Magic You Bring

  • Bachelor's or Master's degree in Computer Science, AI, Software Engineering, or a related field.
  • 6–10 years of software engineering experience, with at least 3 years in a tech lead or engineering management role.
  • Demonstrated track record of shipping production conversational AI, IVR, or agentic systems end to end — not just models, but the full stack from architecture to monitoring.
  • Hands on experience with multi agent orchestration on AWS Bedrock or equivalent agentic frameworks (LangGraph, CrewAI, AutoGen).
  • Prior experience leading a team of 3–8 engineers, with a coaching first approach to technical growth.
  • Strong Python and backend development skills; able to write, review, and hold the bar on production grade code.
  • Engineering multiplier: makes every engineer on the team faster and better through design guidance, code reviews, and clear technical direction.
  • Ownership without ego: defines problems, architects solutions, ships results — accountable for outcomes across the full platform, not just assigned tickets.
  • Operational intelligence: understands the business context of driver support, logistics operations, and the real cost of failure in real time systems.
  • Senior communicator: articulates trade offs (agent reliability vs. automation rate, cost vs. latency) clearly to non engineers and influences roadmap decisions through clarity of thought.
  • Structured under ambiguity: brings process and rigor to fast moving R&D environments where requirements evolve alongside the build.
  • Bias for action: prototypes fast, validates early, and ships iteratively — while maintaining the quality bars that prevent production incidents.

Conversational AI & LLMs (Core)

  • Deep experience with AWS Bedrock — Agents, Knowledge Bases, Guardrails, and model invocation; strong preference for Claude Sonnet/Opus via Bedrock.
  • Multi agent system design: orchestration patterns, agents as tools, inter agent handoffs, context propagation, and failure isolation.
  • Prompt engineering: system prompt design, structured output, tool use, multi turn reasoning, eval driven iteration, and red teaming for safety.
  • Structured rules engines: condition/operator/value schemas for deterministic, non interpretive decision logic — mandatory in production agentic systems.
  • RAG pipelines: embedding models, vector databases (OpenSearch, Pinecone, pgvector), hybrid retrieval, and knowledge base tuning.

IVR & Voice

  • IVR architecture: call flow design, intent/slot management, DTMF handling, escalation to human routing, and SLA monitoring.
  • Experience with STT/TTS pipelines or voice bot platforms is a strong plus.

AWS Services (Core)

  • Lambda, API Gateway, SQS/SNS, Step Functions, DynamoDB, S3, CloudWatch — event driven and serverless architectures.
  • AWS Bedrock Agents: agent creation, alias management, tool action group configuration, and Guardrail policy management.
  • IAM, VPC, Secrets Manager — security and environment best practices for AI service deployments.
  • CI/CD for AI services: prompt versioning, agent config deployment pipelines, automated evals, and rollback gates.

Backend & Engineering

  • Python — async, OOP, clean code; REST API design with FastAPI or Flask.
  • MongoDB and DynamoDB — schema design, indexing, querying, and operational monitoring.
  • Docker, ECS/Fargate; Git, automated testing, and CI/CD workflows.
  • Salesforce integration (APIs, events, data sync) is a strong plus.

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