Senior AI Engineer - Chatbot & Agentic AI

Role overview

This position sits within Snoonu’s R&D function and is intended for an experienced AI engineer who can serve as the technical lead for conversational AI and agent-based automation. The role focuses on building production-ready chatbot experiences using AWS and leading frontier LLMs, with Claude as the primary model family, while also designing autonomous AI workflows that reflect Snoonu’s operational procedures across support, order validation, and logistics.

In addition to hands-on development, the role includes setting engineering direction, establishing technical quality standards, mentoring junior team members, and helping shape the next wave of AI capabilities the team should pursue.

Technical leadership and architecture

• Take ownership of the full architecture for the company’s chatbot and agentic automation stack, covering model choice, prompting approach, cloud design, and observability.
• Create engineering guidelines, design patterns, and development standards, while reviewing solution designs and ensuring a high bar for quality.
• Coach junior and mid-level engineers through code reviews, technical feedback, and capability-building around LLM engineering.
• Work closely with the R&D Director to assess new technologies, define technical priorities, and present recommendations with clear trade-off reasoning.

Conversational AI and chatbot delivery

• Build and ship multi-channel chatbot experiences for web, WhatsApp, and app environments using AWS Lex, Bedrock, API Gateway, and Claude or similar models.
• Solve advanced conversation design problems such as multi-turn reasoning, context retention, intent clarification, and fallback handling.
• Connect chat interfaces with internal systems such as order management, CRM, and logistics through secure and scalable RESTful or event-driven integrations.
• Run model and prompt evaluation cycles, comparing versions, retrieval setups, and prompt strategies against quality and cost goals in production.

Agentic AI workflows

• Design agent-based systems that convert SOPs into autonomous multi-step workflows for customer support, order verification, and logistics operations.
• Choose the right orchestration framework for each use case, such as LangGraph, CrewAI, Bedrock Agents, or Step Functions, based on reliability, debugging, and scalability needs.
• Build memory handling, context control, tool-use logic, and guardrails so agents behave consistently even in difficult or adversarial scenarios.
• Set up human review points, confidence thresholds, and escalation flows so automation supports human decision-making in sensitive situations.

AWS infrastructure and MLOps

• Own the infrastructure foundation for AI services using Lambda, ECS/Fargate, SQS/SNS, DynamoDB, S3, CloudWatch, and Bedrock, with attention to reliability, scale, and cost.
• Create CI/CD workflows for prompt versioning, model rollout, A/B testing, and automated evaluations before release.
• Define monitoring practices for drift, latency, cost, and failure rates across deployed AI systems.

Research and innovation

• Lead evaluation of frontier and emerging models, including Claude, GPT, LLaMA, Mistral, and open-weight alternatives, against Snoonu’s real-world use cases and constraints.
• Prototype new high-impact AI capabilities, moving ideas through proof-of-concept stage with clear success and stop criteria.
• Document architecture decisions, experiment findings, and prompt engineering guidance for wider team use.

Experience and working style

The ideal candidate brings deep software engineering experience, a strong production mindset, and a research-driven approach to turning new AI capabilities into practical business outcomes. This person should be comfortable leading in ambiguity, making sound technical judgments, and communicating complex trade-offs to both technical and non-technical stakeholders.

Success in this role also requires ownership, direct collaboration, and a willingness to challenge assumptions early when risk or better options are identified.

Education

• A bachelor’s or master’s degree in Computer Science, AI, Software Engineering, or a closely related discipline is expected.

Experience requirements

• 5 to 8 years of practical software engineering experience.
• At least 3 years of that experience should be centered on LLM-based systems, conversational AI, or agentic architectures.
• Proven ownership of production AI products from API layer through monitoring and operations is required; a portfolio, GitHub profile, or detailed case studies are expected.
• Experience in a senior individual contributor or tech lead position, including design reviews and mentoring responsibilities.

Core technical expectations

• Strong Python development skills and solid backend engineering experience, with FastAPI or Flask preferred.
• Hands-on experience with Anthropic Claude through API and AWS Bedrock, including prompting, tool usage, and multi-turn reasoning.
• Working knowledge of OpenAI GPT models and open-weight models such as LLaMA 3, Mistral, and Phi, with fine-tuning, quantization, or local inference as a plus.
• Practical experience with retrieval-augmented generation, including vector stores such as OpenSearch, Pinecone, or pgvector, as well as embeddings and hybrid search.
• Familiarity with agent frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or AWS Bedrock Agents.
• Experience with prompt engineering, system prompt design, evaluation workflows, and red-teaming for production safety.
• Knowledge of AWS services including Amazon Bedrock, Amazon Lex v2, Lambda, API Gateway, Step Functions, SQS/SNS, DynamoDB, S3, CloudWatch, IAM, VPC, and Secrets Manager.
• Comfort working with serverless and event-driven architectures, Docker, and container orchestration platforms such as ECS or EKS.
• Experience with Git, CI/CD pipelines, automated testing, and prompt versioning practices.

About Snoonu

Snoonu is a Qatar-based super app focused on delivery, shopping, and everyday convenience. The organization describes itself as a technology-led team with global ambitions, aiming to reshape how people live through innovation and connected digital experiences.

Values and culture

The company highlights a culture built around customer focus, integrity, curiosity, ownership, speed, and teamwork. It emphasizes collaboration, initiative, and delivering practical results with accountability.

Perks and work culture

The organization offers a global working environment, access to learning resources, autonomy over your work, flexible time off, and an agile way of working across product and operations teams.

Recognition and certifications

Snoonu states that it is Great Place to Work® certified. It also mentions ISO 9001:2015 and ISO 45001:2018 certifications, reflecting its focus on quality, workplace safety, and employee wellbeing.

Community and inclusion

The company says it supports sustainability, community contribution, and CSR efforts. It also presents itself as an equal opportunity workplace that welcomes people from all backgrounds and emphasizes fairness, inclusion, and belonging.

Application note

Interested candidates are encouraged to apply to be part of the team and contribute to the company’s AI initiatives.