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Experience
7 - 14 Years
Job Location
Education
Masters in Computer Application(Computers), Master of Technology/Engineering(Computers), Master of Science(Computers), Ph.D/Doctorate(Computer Science)
Nationality
Any Nationality
Gender
Any
Vacancy
1 Vacancy
Job Description
Roles & Responsibilities
- Architect & implement AI microservices (e.g., SRV-LLM, SRV-RAG, SRV-EMB) as Kubernetes-native, GPU-optimized workloads using C# (NET) and Python, with schema-bound APIs (OpenAPI/JSON), rigorous testing, and zero-downtime deployment patterns (blue/green, canary).
- Operationalize the full AI lifecycle: from data ingestion (PII-aware redaction, chunking) ? model training/fine-tuning (PEFT/LoRA) ? prompt engineering ? RAG orchestration ? serving ? monitoring ? drift-aware upgrades.
- Deploy and manage hybrid AI inference infrastructure, including on-prem NVIDIA NIM–style microservices (vLLM/Triton on H100/A6000) with policy-based routing to Azure or vendor backends via the ADEO AI Gateway.
- Enforce Arabic-first & RAG-first principles: grounded generation, citation enforcement, bilingual evaluation parity, and morphology-aware retrieval.
- Integrate with platform registries: version and promote models (MLflow), prompts, and datasets with approval workflows, canary rollouts, and one-click rollback.
- Embed safety & compliance by design: data-class–aware controls (RBAC, mTLS, redaction), content filters, audit logging, and runtime policy gates aligned to ADEO’s risk tiers (L0–L3).
- Drive performance & cost efficiency: benchmark latency (TTFT/TBT), optimize token usage, implement caching, quantization (AWQ/GPTQ), and FinOps telemetry per Service ID.
- Collaborate across the gated lifecycle (G0?G4): contribute to Service Design Docs, NFR validation, UAT sign-offs, and Operate/Improve reviews with evidence-backed KPIs (grounding ?80%, RAGAS, WER, etc.).
- Support hybrid architectures: compose GenAI with classical ML (scikit-learn/XGBoost), rules engines, and external tools (SQL, GIS, KG) via MCP or function calling.
Desired Candidate Profile
- 7+ years in software engineering, with 4+ years in AI/ML engineering or MLOps in production environments.
- Expert in C# (NET Minimal APIs) and Python (FastAPI, LangChain, LlamaIndex, PyTorch).
- Proven experience building AI microservices on Kubernetes with GPU scheduling, service mesh (Istio/Linkerd), and infrastructure-as-code (Helm/Terraform).
- Hands-on deployment of on-prem LLM inference stacks (vLLM, TGI, Triton) and replication of cloud/NVIDIA NIM patterns in private data centers.
- Strong grasp of MLOps: model/prompt/dataset versioning, CI/CD for AI, shadow/canary deployments, drift detection, and SLO-driven alerting.
- Experience with RAG systems: embedding models (Qwen, Jina), vector DBs (Qdrant, FAISS), rerankers (ColBERT), and retrieval evaluation (hit-rate, RAGAS).
- Familiarity with evaluation-by-design: automated scoring, human-in-the-loop validation, and promotion gates.
- Understanding of security & compliance: zero-trust networking, PII handling, auditability, and risk-tiered governance.
- Excellent algorithmic thinking, system design skills, and a performance-first mindset.
Preferred Qualifications
- Experience fine-tuning Arabic LLMs (AraBERT, Qwen-Arabic) or working with Gulf dialects.
- Contributions to open-source AI tooling or MLOps platforms.
- Knowledge of NET for AI scenarios (ML NET, gRPC interop with Python services).
- Exposure to agent frameworks (LangGraph) and multi-step agentic workflows.
- Experience in government, defense, or highly regulated sectors with strict data sovereignty requirements.
Employment Type
- Full Time
Company Industry
- IT - Software Services
Department / Functional Area
- Engineering
Keywords
- Production Environment
- Data Science Engineer
- Deep Learning
- AI Platform Engineer
- Cloud Computing
- Machine Learning
- Model Deployment
- AI Solutions Architect
- AI Systems Engineer
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Halian
www.halian.com
Arshad Ayub Shaik - Recruitment Consultant
street 6 102, First Floor, Building 4 Dubai Outsource City AL NAKHEEL, United Arab Emirates (UAE)