Tech S And T - AI Integration Engineer Senior - GDSN02
Ernst and Young20 hours ago
Bengaluru, IndiaSenior
Responsibilities
- Build end-to-end AI/ML pipelines covering training, evaluation, deployment, experiment tracking, and model registries.
- Develop, fine-tune, optimize, package, and serve models and LLM/RAG applications using Python and the listed ML, LLM, and model-serving frameworks.
- Create evaluation harnesses, golden datasets, regression gates, feature stores, data contracts, and data-quality controls.
- Build event-driven, streaming, microservice, API, automation, and data-operations workflows using Python, Bash, PowerShell, SQL, and the listed orchestration and messaging tools.
- Deliver infrastructure as code, Kubernetes configuration, GitOps workflows, secure CI/CD, artifact promotion, rollbacks, and progressive delivery.
- Implement DevSecOps controls including security scanning, SBOMs, policy as code, image signing, secrets management, workload identity, and least-privilege access.
- Implement AI safety, governance, privacy, compliance, prompt-injection defenses, output filtering, PII redaction, guardrails, lineage, model cards, and data sheets.
- Monitor model and data drift, bias, performance, telemetry, cost, latency, reliability, and service health; contribute to SRE practices, on-call readiness, incident response, and post-mortems.
- Operate API gateways and service meshes with rate limiting, authentication and authorization, mutual TLS, and zero-trust patterns.
- Collaborate with security, data, AI/ML, DevOps, and platform teams to publish golden paths, templates, and reference implementations and participate in code and design reviews.
Requirements
- 4–7 years of hands-on experience in cloud platforms, automation, AI/ML engineering workflows, and related engineering practices.
- B.Tech. or BS in Computer Science.
- Strong expertise with Terraform, Kubernetes, Helm, Docker, and modern CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or Azure DevOps.
- Proficiency in Python, FastAPI, PyTorch or TensorFlow, and Bash or PowerShell scripting.
- Hands-on DevSecOps experience with SAST/DAST, container and infrastructure scanning, secrets scanning, SBOMs, and policy-as-code frameworks.
- Experience with MLOps and AI integration tools such as MLflow, Kubeflow, Weights & Biases, KServe, Seldon Core, or BentoML.
- Experience building or integrating RAG/LLM pipelines using LangChain, LlamaIndex, or vector databases such as Pinecone, FAISS, or Weaviate.
- Strong cloud fundamentals across AWS, Azure, and GCP, with the ability to design secure automated infrastructure through IaC and GitOps.
- Familiarity with Prometheus, Grafana, OpenTelemetry, ELK/Loki, and related application and model observability stacks.
- Strong troubleshooting, problem-solving, system-debugging, collaboration, communication, and cross-functional engineering skills.
Tech Stack
AmbassadorAnsibleApache AirflowApache KafkaArgo CDAWSAzureBashDatabricksDockerFastAPIGitHub ActionsGitLab CI/CDGoogle Cloud PlatformGrafanaGraphQLgRPCHelmHugging Face TransformersIstioJenkinsKubernetesMLflowPowerShellPrometheusPuppetpytestPythonPyTorchRabbitMQscikit-learnSonarQubeSQLTensorFlowTerraformVault
Categories
About Ernst and Young
Ernst & Young (EY) provides audit/assurance, tax, consulting, strategy and transactions services to enterprises, financial institutions, and public‑sector clients. Structured as a global network of partner‑owned member firms, it sells professional services on a fee basis, including a dedicated Financial Services Organization for banking, insurance, and capital markets. Headquartered in London, EY was formed in 1989 from the merger of Ernst & Whinney and Arthur Young, and operates in 150+ countries.