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- Senior Software Engineer - AI & ML (Based in Dubai)
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Job Title: Senior Software Engineer – AI & ML
Role Summary:
Lead end‑to‑end development of AI‑powered full‑stack applications and backend services that enhance user experience and internal tools. Design, deploy, and maintain scalable, cloud‑native infrastructures for AI/ML workloads while ensuring high availability, observability, and compliance with security and responsible AI standards.
Expectations:
- Deliver production‑ready ML/GenAI solutions such as Retrieval‑Augmented Generation, recommendation, classification, and semantic search.
- Own service lifecycle from design to on‑call support, ensuring reliability and performance.
- Mentor junior engineers and collaborate closely with cross‑functional teams (Product, Data Science, Data Engineering, Design, DevOps/SRE).
- Keep technology stack modern by evaluating emerging AI/ML practices and advocating improvements.
Key Responsibilities:
- Architect and implement AI‑enabled backend services in Python, Golang, or Node.js.
- Productionize ML models, build RAG pipelines, and manage embedding/feature stores and vector search infrastructure.
- Configure CI/CD pipelines (GitHub Actions, Jenkins) and IaC for AWS (ECS/EKS, Docker).
- Implement observability: metrics, logs, traces, dashboards, alerts.
- Apply security, data protection, and responsible AI guardrails.
- Conduct code reviews, establish engineering best practices, and maintain documentation.
- Mentor peers and occasionally data scientists on software design and reliable ML deployment.
Required Skills:
- 7+ years of professional software engineering with strong experience in backend and distributed systems.
- Proficient in Golang, Node.js, or Python; solid in relational and NoSQL database design/optimization.
- Deep understanding of AWS cloud architecture, containerization, and DevOps (CI/CD, IaC).
- Experience with MLOps: model deployment, monitoring, data drift detection, and CI/CD for ML.
- Knowledge of vector databases (Pinecone, Weaviate, Milvus, Opensearch) and building semantic search.
- Familiarity with fine‑tuning transformer models and building RAG pipelines.
- Excellent problem‑solving, communication, and teamwork abilities in Agile environments.
Required Education & Certifications:
- Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).
- Relevant certifications in AWS, DevOps, or ML Ops preferred but not mandatory.