Snr Consultant, Data & AI Engineering
Snr Consultant, Data & AI Engineering
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Job Description
NCS is a leading technology services firm that operates across the Asia Pacific region in over 20 cities providing consulting digital services technology solutions and more. We believe in harnessing the power of technology to achieve extraordinary things creating lasting value and impact for our communities partners and people. Our diverse workforce of 13000 has delivered large-scale mission critical and multi-platform projects for governments and enterprises in Singapore and the APAC region.
As a Senior Consultant Data & AI Engineering you will be designing building and operating production-grade agentic and GenAI systemsend to end. Youll ship services (not just notebooks): robust APIs reusable components and secure pipelines that connect LLMs tools knowledge and enterprise systems. Youll pair strong software engineering with modern AI practices (RAG agent orchestration policy chains evals) to deliver measurable business outcomes at scale.
What you will do:
- Agent & Application Engineering
- Design multi-agent systems (MAS) with planning tool-use and delegation (e.g. LangGraph/Semantic Kernel); expose them via REST/gRPC APIs (FastAPI/Express/Java/Go).
- Implement tool adapters (SQL search document stores web calls code exec) with strict type contracts and safe sandboxes.
- Build model gateway integrations (OpenAI/Azure OpenAI/Bedrock/Vertex; self-hosted vLLM/TGI) with routing rate-limits retries and fallback chains
- Retrieval Data & Knowledge
- Stand up RAG services: chunking enrichment embeddings indexing hybrid/vector search (pgvector/Pinecone/Weaviate; OpenSearch/Azure AI Search).
- Implement ingestion pipelines (Airflow/Prefect/Celery/Ray) for docs tickets chat and ERP/CRM data; handle PII redaction and metadata governance.
- Optimize retrieval quality (chunking strategies re-rankers query rewriting) with offline/online evaluation and A/B tests.
- Quality Testing & Evaluation
- Treat prompts and graphs as code: version diff and test them (unit tests for prompts/tools; golden sets; regression suites).
- Build evaluation harnesses (latency cost accuracy toxicity hallucination guardrail hit-rates); wire into CI.
- Add drift detection for conversational systems; implement safe shutdown and auto-rollback.
- Platform & Operations
- Package services as containers; deploy to Kubernetes with Helm/Argo CD; configure autoscaling HPA/VPA and resource quotas.
- Implement policy chains and guardrails (OPA/Gatekeeper for policy Presidio for PII Trivy for image scanning).
- Instrument deep observability: tracing (OpenTelemetry) metrics (Prometheus) logs (ELK/OPENSEARCH) cost meters per request/model.
- Security & Compliance
- Manage secrets (HashiCorp Vault/KMS) signed images SBOMs; enforce least-privilege IAM.
- Build tenant isolation and data residency controls; implement red/blue team prompts and jailbreak defenses
- Integration & Enterprise Workflows
- Ship connectors and events for SAP/CRM/ITSM and Kafka topics; design idempotent retry-safe processors.
- Automate business workflows with pro-code services first; expose low-code surfaces only where appropriate.
- Collaboration & Leadership
- Partner with Product Data and Platform teams to define SLAs/SLOs and success metrics.
- Mentor engineers on AI as software practices; run design reviews and postmortems.
The ideal candidate should possess:
- 6 years in software engineering (prod services not just prototypes) including 1 year leading small projects.
- Strong in one systems language (Python/TypeScript/Go/Java) and comfortable in a second.
- Hands-on with containers Kubernetes CI/CD (GitHub Actions/GitLab/Jenkins) IaC (Terraform) and cloud (Azure/AWS/GCP).
- Practical LLM experience: building RAG/agent apps prompt design tool-use and safety patterns.
- Data skills: designing schemas batch/stream pipelines and search indexes; proficiency with SQL and one vector DB.
- Testing mindset: unit/integration tests load tests golden datasets for LLM evals.
- Security basics: secrets policies scanning and least-privilege IAM.
- Agent orchestration (LangGraph Semantic Kernel) and distributed compute (Ray) in production.
- Search/retrieval tuning (BM25 vector hybrid re-ranking query planning).
- Observability at scale with OpenTelemetry; cost/perf optimization across model/router layers.
- Experience in regulated or high-throughput domains (e.g. telco finance healthcare); multi-tenant and data-residency patterns.
- Domain integrations (SAP/CRM/ITSM) event-driven architectures (Kafka/Debezium) and policy enforcement (OPA/Gatekeeper).
- Familiarity with TM Forum APIs / BSS-OSS patterns is a plus (if in telco context).
- Languages: Python TypeScript/ (plus Go/Java bonus)
- Frameworks: FastAPI/Express LangGraph/Semantic Kernel Ray/Celery Airflow/Prefect
- Storage/Search: Postgres Redis S3/Blob; pgvector/Pinecone/Weaviate; OpenSearch/Azure AI Search
- LLM Runtime: OpenAI/Azure OpenAI/Bedrock/Vertex; vLLM/TGI; inference routers/gateways
- Platform: Docker Kubernetes Helm Argo CD Terraform Vault Istio
- Observability: OpenTelemetry Prometheus/Grafana ELK/OpenSearch
- Quality & Safety: pytest/Jest prompt/unit test harnesses guardrails Presidio Trivy
Required Experience:
Contract
Employment Type
Full-Time
