CES Family of Companies

Senior AI Engineer

CES Family of Companies

full-time

Posted on:

Location Type: Remote

Location: United States

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Job Level

Senior

Tech Stack

AWSAzureCloudGoogle Cloud PlatformGraphQLGRPCPrometheusPythonPyTorch

About the role

  • Own end-to-end development of LLM features: problem framing, data prep, prototyping, offline/online evaluation, deployment, and monitoring.
  • Build retrieval-augmented generation (RAG) pipelines with vector search (e.g., FAISS, Pinecone, OpenSearch/KNN) and document orchestration.
  • Implement prompt strategies, tool use/function calling, and guardrails for safety, bias, and privacy.
  • Integrate models in production services (REST/GraphQL/gRPC), including auth, rate limiting, and observability.
  • Stand up evals and experiment frameworks (A/B tests, golden sets, regression suites) with clear success metrics.
  • Optimize for latency, cost, and quality: prompt compression, caching, model selection, fine-tuning/LoRA, distillation where appropriate.
  • Collaborate with DevOps/MLOps/Platform to automate CI/CD, data/version management, and feature flags.
  • Embed with CX/Support to mine tickets, chats, and call transcripts; convert VOC into training/eval datasets and backlog priorities.
  • Instrument user journeys and define online/offline evals (win rate, hallucination rate, TTR, CSAT/NPS); run A/B tests and ship iterative improvements.
  • Build feedback loops (thumbs-up/down, rationale capture, escalation) and human-in-the-loop fallbacks that protect quality.
  • Own reliability and UX details that matter for customers: latency budgets, safe fallbacks, clear handoff to human agents, accessibility.
  • Partner with Trust/Legal/Security to ensure privacy-by-design and compliant data handling; implement guardrails and red-team mitigations.

Requirements

  • 4–6 years in applied ML/AI or backend engineering with measurable production impact.
  • Strong Python and software engineering fundamentals (testing, types, CI/CD).
  • Practical LLM experience: OpenAI/Anthropic, or cloud providers (AWS Bedrock, Azure OpenAI, GCP Vertex).
  • Experience with at least one deep learning or LLM framework (PyTorch, Transformers, vLLM) and one orchestration library (LangChain, LlamaIndex, Guidance, or custom).
  • RAG and data pipelines: chunking/embedding strategies, vector DBs, metadata filtering, and document QA.
  • Monitoring/telemetry for AI systems (e.g., MLflow, Weights & Biases, Prometheus, custom eval dashboards).
  • Security & privacy awareness (PII handling, redaction, data retention).
Benefits
  • Flexible working hours to create a work-life balance.
  • Opportunity to work on advanced tools and technologies.
  • Global exposure to not only collaborate with the team, but also to connect with the client portfolio and build professional relationships.
  • Highly encouraged for any innovative ideas & thoughts and we support in executing the same.
  • Periodical and on-spot rewards and recognitions on your performance.
  • Provides a better platform for enhancing skills via many different L&D programs.
  • Enabling and empowering atmosphere to work along.
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
PythonLLM developmentdeep learningRAG pipelinesdata preparationA/B testingprompt engineeringmodel fine-tuningCI/CDmonitoring
Soft Skills
collaborationproblem framingcommunicationuser experience focusreliabilitysafety awarenessprivacy awarenessdata handlingfeedback loop creationiterative improvement