AI Engineer

ADABA PTE. LTD.; Singapore; On-site; SGD 90,000 - 120,000; Full time

Job summary

A tech-focused company in Singapore is seeking a Senior Software Engineer to design and implement production-grade GenAI systems. The ideal candidate will have over 6 years in software engineering and strong proficiency in containerization and cloud technologies. Key responsibilities include developing APIs, performing data management, and mentoring team members on AI practices. This role offers a dynamic work environment and the opportunity to drive substantial technological innovations.

Qualifications

• 6+ years in software engineering, including leading small projects.
• Strong in one systems language (Python, TypeScript, Go, Java).
• Hands-on experience with containers and Kubernetes.

Responsibilities

• Design and build agentic and GenAI systems end to end.
• Implement tool adapters and model gateway integrations.
• Mentor engineers on AI as software practices.

Skills

Software engineering

Python

TypeScript

Containerization

CI/CD

LLM experience

Data design

Security basics

Tools

Kubernetes

Docker

Terraform

Azure

Job description

Job Overview & Expectations

Design, build, and operate production‑grade agentic and GenAI systems end to end. You’ll ship services (not just notebooks): robust APIs, reusable components, and secure pipelines that connect LLMs, tools, knowledge, and enterprise systems. You’ll pair strongTOFTWARE engineering with modern AI practices (RAG, agent orchestration, policy chains, evals) to deliver measurable business outcomes at scale.

1. 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.

2. 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.

3. 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.

4. 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.

5. 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.
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6. Integration & Enterprise Workflows

• Ship connectors and events for SAP/CRM/ITSM and Kafka topics; design idempotent, retry‑safe processors.
• Automatenormal business workflows with pro‑code services first; expose low‑code surfaces only where appropriate.

7. 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.

Preferred Qualifications

• 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).

Tech Stack (Illustrative)

• Languages: Python, TypeScript/Node.js (plus Go/Java bonus)
• Frameworks: FastAPI/Express, LangGraph/Semantic Kernel, Ray/Celery, Airflow/Prefect
• Storage/Search mev : Postgres, Redis, S3/Blob; pgvector/Pinecone/Weaviate; OpenSearch/Azure AI Search
• Open ward/ Azure OpenAI/ Bock/ 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

If you are keen to have a preliminary chat, please send your CV directly to [e-mail]

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Adaba Pte Ltd EA Licence: 25C2727 Reg No: R25157283