AI Forward Deploy Engineer

ArangoDB; Paris; Sur place; EUR 60 000 - 80 000; Plein temps

Résumé du poste

arangodb is seeking an AI Forward Deploy Engineer in Paris, France, to work closely with customers, delivering production-grade AI solutions across various sectors. The successful candidate will define success metrics, build prototypes, and ensure operational readiness while collaborating with engineers and users.

The ideal applicant should have over 4 years of software engineering experience, possess strong AI and Python skills, and be familiar with modern AI tooling. Fluency in both French and English is essential for effective communication.

Qualifications

• 4+ years of software engineering experience building and operating production systems.
• Strong database skills including Graph, NoSQL, Key Value.
• Hands-on experience with modern LLMs and tooling.

Responsabilités

• Partner with customer sponsors to identify high-value AI use cases.
• Define success metrics, SLAs/SLOs, and a delivery plan.
• Build end-to-end prototypes and productionize services.

Connaissances

AI

Python

Database management

Cloud & containers

Observability

Excellent communication

Outils

OpenAI

Hugging Face

Docker

Kubernetes

Terraform

Description du poste

Arango is looking for an AI Forward Deploy Engineer to embed with our customers and deliver real, production‑grade AI solutions—fast. You’ll run discovery, design and prototype systems, ship secure and reliable services, and ensure adoption and measurable business impact. Think full‑stack AI + MLOps + product sense, delivered side‑by‑side with users.

This is a hands‑on, customer‑facing role for engineers who are as comfortable whiteboarding with executives as they are profiling latency in a retrieval pipeline.

Location: France – only applicants living in France will be considered (Must be fluent in French and English)

Key Responsibilities:

• Partner with customer sponsors, SMEs, and operators to identify high‑value AI use cases.
• Define success metrics, SLAs/SLOs, data access needs, and a delivery plan (PoV → pilot → production).
• Build end‑to‑end prototypes (data connectors, RAG pipelines, prompts/tools, UIs/APIs).
• Productionize into secure, observable services with CI/CD, infrastructure‑as‑code, and proper testing.
• Implement retrieval‑augmented generation (chunking, embeddings, ranking, caching) and tool/call orchestration.
• Evaluate and iterate prompts, models, and retrieval strategies using offline/online metrics and A/B tests.
• Where needed, fine‑tune or adapt models (LoRA/PEFT, preference optimization/DPO, distillation) and optimize inference (quantization, batching, vLLM/TGI/TensorRT‑LLM).
• Build robust data pipelines (ETL/ELT), vector indices, and metadata governance.
• Monitor quality, drift, hallucination/guardrail events, latency, and cost; set up alerting and dashboards.
• Implement role‑based access, secrets management, audit logging, PII redaction, and content safety filters.
• Align solutions to customer requirements (e.g., SOC2/ISO 27001, GDPR/CCPA, HIPAA as applicable).
• Document architectures and playbooks; train customer engineers and end users.
• Capture product feedback and influence Arango’s roadmap with field learnings.

Required Qualifications:

• 4+ years of software engineering experience building and operating production systems (or equivalent).
• Strong AI, Python skills; solid understanding of data structures, networking, concurrency, and systems design.
• Strong database skills; Graph, NoSQL, Key Value.
• Hands‑on experience with modern LLMs and tooling (e.g., OpenAI/Anthropic/Llama, Hugging Face, LangChain/LlamaIndex, function/tool calling).
• Retrieval and vector databases (FAISS, pgvector, Pinecone, Weaviate, or similar).
• Cloud & containers (AWS/GCP/Azure), Docker/Kubernetes, IaC (Terraform/CloudFormation), and CI/CD.
• Observability (metrics, logs, traces) and performance tuning for latency‑sensitive services.
• Excellent communication; experience working directly with customers or cross‑functional stakeholders.

Nice to have:

• Front‑end or full‑stack experience (TypeScript/React, Next.js) for light UI prototyping.
• Search/IR fundamentals (BM25, hybrid retrieval, re‑ranking).
• MLOps platforms (MLflow, Weights & Biases), evaluation frameworks (Ragas, promptfoo, DeepEval).
• Inference optimization (vLLM, Text Generation Inference, Triton, TensorRT‑LLM, quantization).
• Domain experience in finance, healthcare, public sector, manufacturing, retail.
• Security/compliance familiarity; prior work with data residency, KMS/HSM, or private networking.
• French Government/industry experiences.

What Success Looks Like (6–12 months):

• 2–4 customer use cases deployed to production with agreed‑upon uptime, latency, and cost targets.
• Demonstrable quality lifts (e.g., task accuracy, deflection rate, cycle time) backed by evals and telemetry.
• Reusable building blocks (templates/operators/connectors) adopted by the broader delivery team.
• Customer enablement completed (runbooks, docs, training) with strong satisfaction/NPS.

Our Toolset:

• Models & SDKs: OpenAI, Anthropic, Meta Llama, Hugging Face.
• Retrieval: FAISS, pgvector, Pinecone, Weaviate; rerankers (ColBERT, cross‑encoders).
• Pipelines & Orchestration: LangChain, LlamaIndex, Ray, Airflow.
• MLOps & Evals: MLflow, Weights & Biases, Ragas, promptfoo, Great Expectations.
• Serving & Infra: vLLM, TGI, FastAPI/gRPC, Docker/K8s, Terraform, GitHub Actions.
• Observability & Guardrails: OpenTelemetry, Prometheus/Grafana, Llama Guard/Content Safety, custom filters.
• Data: Postgres/BigQuery/Snowflake; Kafka; object storage.

Why Join Arango:

• Contributing to cutting‑edge AI and data infrastructure.
• Collaborating with experienced engineers, marketers, and product leaders.
• Helping shape how enterprises build AI‑powered applications.

If you're excited about the intersection of AI, data, and social media, we’d love to hear from you.