DWP Engineer Senior

Delhi - India

Monthly Salary: Not Disclosed

Posted on: Yesterday

Vacancies: 1 Vacancy

Job Summary

At EY were all in to shape your future with confidence.

Well help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.

Join EY and help to build a better working world.

Designation - AI Integration Engineer

Job Description

Build endtoend AI/ML pipelines (training evaluation deployment) using MLflow/Kubeflow/Databricks/Weights & Biases with experiment tracking and model registries.
Develop models with Python using PyTorch TensorFlow JAX scikitlearn and Hugging Face Transformers package as reproducible services.
Implement LLM/RAG systems with LangChain LlamaIndex Semantic Kernel and vector DBs (Pinecone Weaviate Milvus FAISS Chroma) for semantic retrieval and grounding.
Finetune and optimize models using PEFT/LoRA/QLoRA DeepSpeed/Accelerate distillation and quantization; export/optimize via ONNX Runtime/TorchScript/TensorRT.
Engineer scalable model serving with KServe Seldon Core BentoML Ray Serve NVIDIA Triton supporting A/B canary shadow deployments.
Build evaluation harnesses (offline/online) with Ragas TruLens Promptfoo golden datasets and regression gates integrated into CI/CD.
Construct feature stores (e.g. Feast) and data contracts (Protobuf/Avro/Pydantic); enforce data quality with Great Expectations/Deequ.
Orchestrate eventdriven pipelines with Airflow/Prefect/Dagster; streaming/messaging via Kafka/RabbitMQ/NATS and schema registries.
Design Python microservices using FastAPI/gRPC; integrate with downstream systems via REST/GraphQL; write robust automation in Python/Bash/PowerShell and SQL for data ops.
Use notebooks (Jupyter) and packaging (Poetry/pip/conda) with virtualenvs environment locking and artifacts suitable for promotion across stages.
Apply testing & quality: pytest unit/integration/e2e tests propertybased (hypothesis) linters/formatters (ruff/flake8 black) type checks (mypy/pyright) precommit.
Deliver IaC with Terraform/Pulumi; manage config via Helm/Kustomize; implement GitOps with Argo CD/Flux on managed/selfhosted Kubernetes.
Build secure CI/CD (GitHub Actions/GitLab CI/Jenkins/Azure DevOps) for app/data/ML artifacts artifact promotion provenance and automated rollbacks.
Embed DevSecOps: SAST/DAST/IAST (Snyk/Checkmarx/SonarQube) container & IaC scanning (Trivy) dependency hygiene (Dependabot/Renovate) SBOM (Syft/CycloneDX).
Enforce policyascode (OPA/Gatekeeper Kyverno) image signing/verification (Sigstore/cosign) supplychain standards (SLSA intoto).
Manage secrets/KMS with Vault and native managers; adopt shortlived workload identities mTLS and leastprivilege RBAC/ABAC in clusters and pipelines.
Implement AI safety & governance: promptinjection defenses output filtering PII redaction guardrails ( Guardrails/Presidio) policy checks.
Monitor model/data drift bias and performance with Evidently/WhyLabs/Arize/Fiddler; unify telemetry via OpenTelemetry Prometheus Grafana ELK/Loki Jaeger.
Optimize compute/GPU: CUDA/cuDNN/NCCL HPA/VPA/KEDA efficient batching caching concurrency control; track cost and latency SLOs.
Implement progressive delivery for services/models (blue/green canary shadow) using Argo Rollouts/Flagger with instant rollback and health checks.
Operate API gateways and service mesh (Kong/NGINX/Envoy Istio/Linkerd) for rate limiting mTLS authN/Z and zerotrust patterns.
Ensure privacy/compliance (GDPR/CCPA/DPDP/ISO 27001): data minimization masking/tokenization DLP lineage (OpenLineage/Marquez) model cards/data sheets.
Collaborate with security data and platform teams to publish golden paths templates and reference implementations for repeatable AI delivery.
Contribute to code/design reviews and SRE practices (SLIs/SLOs/error budgets) oncall readiness incident response and blameless postmortems.

Desired Profile

Looking for a DevSecOps & AI Engineer with 47 years of handson experience in cloud platforms automation and AI/ML engineering workflows.
Strong expertise in Terraform Kubernetes Helm Docker and modern CI/CD pipelines using GitHub Actions GitLab CI Jenkins or Azure DevOps.
Proficient in Python with experience in FastAPI ML libraries (PyTorch/TensorFlow) and scripting using Bash or PowerShell for automation.
Solid experience in DevSecOps practices including SAST/DAST container/IaC scanning secrets scanning SBOM and policy-as-code frameworks.
Handson exposure to MLOps and AI integration using tools like MLflow Kubeflow Weights & Biases KServe Seldon Core or BentoML.
Experience building or integrating RAG/LLM pipelines using LangChain LlamaIndex or vector databases (Pinecone/FAISS/Weaviate).
Strong cloud fundamentals across AWS/Azure/GCP with ability to architect secure automated infrastructure via IaC and GitOps (Argo CD/Flux).
Familiarity with monitoring and observability stacks (Prometheus Grafana OpenTelemetry ELK/Loki) for application and model performance.
Strong troubleshooting problemsolving and system debugging skills with a collaborative engineeringfirst mindset.
Excellent communication skills with ability to work crossfunctionally with Data AI/ML DevOps Security and Platform Engineering teams.

Experience 4 to 7 years

Education . / BS in Computer Science

Technical Skills & Certifications

Terraform Pulumi and IaC for automated cloud and platform provisioning.
Kubernetes Docker/Podman Helm and Kustomize for container orchestration and packaging.
CI/CD pipelines using GitHub Actions GitLab CI Jenkins and Azure DevOps.
Proficient in Python (FastAPI ML/LLM libraries) and scripting with Bash/PowerShell.
DevSecOps tooling: Snyk SonarQube Trivy Checkmarx GitLeaks and secret scanning.
MLOps platforms: MLflow Kubeflow W&B Azure ML Vertex AI for model lifecycle management.
Model serving frameworks: KServe Seldon Core BentoML Ray Serve for scalable inference.
RAG/LLM integration: LangChain LlamaIndex vector DBs (Pinecone Weaviate FAISS Chroma).
Monitoring & observability: Prometheus Grafana ELK/Loki OpenTelemetry Jaeger.
GitOps tools (Argo CD Flux) configuration management (Ansible/Puppet) and serverless functions.

EY Building a better working world

EY is building a better working world by creating new value for clients people society and the planet while building trust in capital markets.

Enabled by data AI and advanced technology EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.

EY teams work across a full spectrum of services in assurance consulting tax strategy and transactions. Fueled by sector insights a globally connected multi-disciplinary network and diverse ecosystem partners EY teams can provide services in more than 150 countries and territories.

Required Experience:

At EY were all in to shape your future with confidence.Well help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.Join EY and help to build a better working world.Designation - AI Integration EngineerJob DescriptionBuild endtoend AI/ML ...